id	sid	tid	token	lemma	pos
cana-1862	1	1	communications	communication	NOUN
cana-1862	1	2	on	on	ADP
cana-1862	1	3	applied	apply	VERB
cana-1862	1	4	nonlinear	nonlinear	ADJ
cana-1862	1	5	analysis	analysis	NOUN
cana-1862	1	6	issn	issn	NOUN
cana-1862	1	7	:	:	PUNCT
cana-1862	1	8	1074	1074	NUM
cana-1862	1	9	-	-	PUNCT
cana-1862	1	10	133x	133x	NUM
cana-1862	1	11	vol	vol	NOUN
cana-1862	1	12	32	32	NUM
cana-1862	1	13	no	no	NOUN
cana-1862	1	14	.	.	NOUN
cana-1862	1	15	2	2	NUM
cana-1862	1	16	(	(	PUNCT
cana-1862	1	17	2025	2025	NUM
cana-1862	1	18	)	)	PUNCT
cana-1862	1	19	692	692	NUM
cana-1862	1	20	https://internationalpubls.com	https://internationalpubls.com	NUM
cana-1862	1	21	advanced	advanced	ADJ
cana-1862	1	22	deep	deep	ADJ
cana-1862	1	23	learning	learning	NOUN
cana-1862	1	24	techniques	technique	NOUN
cana-1862	1	25	for	for	ADP
cana-1862	1	26	information	information	NOUN
cana-1862	1	27	security	security	NOUN
cana-1862	1	28	vulnerability	vulnerability	NOUN
cana-1862	1	29	detection	detection	NOUN
cana-1862	1	30	using	use	VERB
cana-1862	1	31	machine	machine	NOUN
cana-1862	1	32	learning	learn	VERB
cana-1862	1	33	champa	champa	PROPN
cana-1862	1	34	tanga1	tanga1	NOUN
cana-1862	1	35	,	,	PUNCT
cana-1862	1	36	madhukar	madhukar	NOUN
cana-1862	1	37	mulpuri2	mulpuri2	PROPN
cana-1862	1	38	,	,	PUNCT
cana-1862	1	39	dr.a	dr.a	NOUN
cana-1862	1	40	.	.	PUNCT
cana-1862	2	1	mahalakshmi3	mahalakshmi3	ADJ
cana-1862	2	2	,	,	PUNCT
cana-1862	2	3	p.k	p.k	PROPN
cana-1862	2	4	.	.	PROPN
cana-1862	2	5	hemalatha4	hemalatha4	PROPN
cana-1862	2	6	,	,	PUNCT
cana-1862	2	7	dr	dr	PROPN
cana-1862	2	8	.	.	PROPN
cana-1862	2	9	gurwinder	gurwinder	PROPN
cana-1862	2	10	singh5	singh5	PROPN
cana-1862	2	11	,	,	PUNCT
cana-1862	2	12	tareek	tareek	PROPN
cana-1862	2	13	pattewar6	pattewar6	NOUN
cana-1862	2	14	,	,	PUNCT
cana-1862	2	15	nargis	nargis	ADJ
cana-1862	2	16	parveen7	parveen7	PROPN
cana-1862	2	17	1	1	NUM
cana-1862	2	18	assistant	assistant	NOUN
cana-1862	2	19	professor	professor	NOUN
cana-1862	2	20	,	,	PUNCT
cana-1862	2	21	department	department	NOUN
cana-1862	2	22	:	:	PUNCT
cana-1862	2	23	electronics	electronic	NOUN
cana-1862	2	24	and	and	CCONJ
cana-1862	2	25	and	and	CCONJ
cana-1862	2	26	communications	communication	NOUN
cana-1862	2	27	engineering	engineering	PROPN
cana-1862	2	28	rajiv	rajiv	PROPN
cana-1862	2	29	gandhi	gandhi	PROPN
cana-1862	2	30	university	university	PROPN
cana-1862	2	31	,	,	PUNCT
cana-1862	2	32	arunachal	arunachal	PROPN
cana-1862	2	33	pradesh	pradesh	PROPN
cana-1862	2	34	.	.	PUNCT
cana-1862	3	1	champa.tanga@gmail.com	champa.tanga@gmail.com	X
cana-1862	4	1	2senior	2senior	NUM
cana-1862	4	2	staff	staff	NOUN
cana-1862	4	3	engineer	engineer	NOUN
cana-1862	4	4	,	,	PUNCT
cana-1862	4	5	nium	nium	PROPN
cana-1862	4	6	inc	inc	PROPN
cana-1862	4	7	,	,	PUNCT
cana-1862	4	8	connectmadhukar@gmail.com	connectmadhukar@gmail.com	PROPN
cana-1862	4	9	3associate	3associate	NUM
cana-1862	4	10	professor	professor	NOUN
cana-1862	4	11	,	,	PUNCT
cana-1862	4	12	department	department	NOUN
cana-1862	4	13	of	of	ADP
cana-1862	4	14	management	management	NOUN
cana-1862	4	15	studies	study	NOUN
cana-1862	4	16	,	,	PUNCT
cana-1862	4	17	m	m	PROPN
cana-1862	4	18	s	s	PART
cana-1862	4	19	ramaiah	ramaiah	PROPN
cana-1862	4	20	institute	institute	PROPN
cana-1862	4	21	of	of	ADP
cana-1862	4	22	technology	technology	PROPN
cana-1862	4	23	,	,	PUNCT
cana-1862	4	24	bangalore	bangalore	NOUN
cana-1862	4	25	,	,	PUNCT
cana-1862	4	26	mahalakshmi.a@msrit.edu	mahalakshmi.a@msrit.edu	PROPN
cana-1862	4	27	4assistant	4assistant	NUM
cana-1862	4	28	professor	professor	NOUN
cana-1862	4	29	,	,	PUNCT
cana-1862	4	30	dept	dept	NOUN
cana-1862	4	31	of	of	ADP
cana-1862	4	32	mathematics	mathematic	NOUN
cana-1862	4	33	,	,	PUNCT
cana-1862	4	34	vel	vel	PROPN
cana-1862	4	35	tech	tech	PROPN
cana-1862	4	36	rangarajan	rangarajan	PROPN
cana-1862	4	37	dr	dr	PROPN
cana-1862	4	38	sagunthala	sagunthala	PROPN
cana-1862	4	39	r	r	PROPN
cana-1862	4	40	&	&	CCONJ
cana-1862	4	41	d	d	PROPN
cana-1862	4	42	institute	institute	PROPN
cana-1862	4	43	of	of	ADP
cana-1862	4	44	science	science	NOUN
cana-1862	4	45	and	and	CCONJ
cana-1862	4	46	technology	technology	NOUN
cana-1862	4	47	,	,	PUNCT
cana-1862	4	48	chennai	chennai	PROPN
cana-1862	4	49	,	,	PUNCT
cana-1862	4	50	india	india	PROPN
cana-1862	4	51	,	,	PUNCT
cana-1862	4	52	pkhemalathamsc@gmail.com	pkhemalathamsc@gmail.com	X
cana-1862	5	1	5associate	5associate	NUM
cana-1862	5	2	professor	professor	NOUN
cana-1862	5	3	,	,	PUNCT
cana-1862	5	4	department	department	NOUN
cana-1862	5	5	of	of	ADP
cana-1862	5	6	ait	ait	PROPN
cana-1862	5	7	-	-	PROPN
cana-1862	5	8	cse	cse	PROPN
cana-1862	5	9	chandigarh	chandigarh	PROPN
cana-1862	5	10	university	university	PROPN
cana-1862	5	11	,	,	PUNCT
cana-1862	5	12	gharuan	gharuan	PROPN
cana-1862	5	13	,	,	PUNCT
cana-1862	5	14	punjab	punjab	PROPN
cana-1862	5	15	,	,	PUNCT
cana-1862	5	16	india	india	PROPN
cana-1862	5	17	email	email	NOUN
cana-1862	5	18	:	:	PUNCT
cana-1862	5	19	singh1001maths@gmail.com	singh1001maths@gmail.com	X
cana-1862	6	1	6assistant	6assistant	NUM
cana-1862	6	2	professor	professor	NOUN
cana-1862	6	3	,	,	PUNCT
cana-1862	6	4	department	department	NOUN
cana-1862	6	5	of	of	ADP
cana-1862	6	6	computer	computer	NOUN
cana-1862	6	7	engineering	engineering	NOUN
cana-1862	6	8	,	,	PUNCT
cana-1862	6	9	vishwakarma	vishwakarma	PROPN
cana-1862	6	10	university	university	NOUN
cana-1862	6	11	pune	pune	NOUN
cana-1862	6	12	,	,	PUNCT
cana-1862	6	13	tareek.pattewar@vupune.ac.in	tareek.pattewar@vupune.ac.in	X
cana-1862	6	14	7department	7department	NUM
cana-1862	6	15	of	of	ADP
cana-1862	6	16	computer	computer	NOUN
cana-1862	6	17	science	science	NOUN
cana-1862	6	18	,	,	PUNCT
cana-1862	6	19	faculty	faculty	NOUN
cana-1862	6	20	of	of	ADP
cana-1862	6	21	computing	computing	NOUN
cana-1862	6	22	and	and	CCONJ
cana-1862	6	23	information	information	NOUN
cana-1862	6	24	technology	technology	NOUN
cana-1862	6	25	,	,	PUNCT
cana-1862	6	26	northern	northern	ADJ
cana-1862	6	27	border	border	NOUN
cana-1862	6	28	university	university	NOUN
cana-1862	6	29	,	,	PUNCT
cana-1862	6	30	kingdom	kingdom	NOUN
cana-1862	6	31	of	of	ADP
cana-1862	6	32	saudi	saudi	PROPN
cana-1862	6	33	arabia	arabia	PROPN
cana-1862	6	34	,	,	PUNCT
cana-1862	6	35	nargis.norulhaq@nbu.edu.sa	nargis.norulhaq@nbu.edu.sa	PROPN
cana-1862	6	36	article	article	NOUN
cana-1862	6	37	history	history	NOUN
cana-1862	6	38	:	:	PUNCT
cana-1862	6	39	received	receive	VERB
cana-1862	6	40	:	:	PUNCT
cana-1862	6	41	18	18	NUM
cana-1862	6	42	-	-	SYM
cana-1862	6	43	07	07	NUM
cana-1862	6	44	-	-	PUNCT
cana-1862	6	45	2024	2024	NUM
cana-1862	6	46	revised	revise	VERB
cana-1862	6	47	:	:	PUNCT
cana-1862	6	48	08	08	NUM
cana-1862	6	49	-	-	SYM
cana-1862	6	50	09	09	NUM
cana-1862	6	51	-	-	PUNCT
cana-1862	6	52	2024	2024	NUM
cana-1862	6	53	accepted	accept	VERB
cana-1862	6	54	:	:	PUNCT
cana-1862	6	55	29	29	NUM
cana-1862	6	56	-	-	SYM
cana-1862	6	57	09	09	NUM
cana-1862	6	58	-	-	PUNCT
cana-1862	6	59	2024	2024	NUM
cana-1862	6	60	abstract	abstract	NOUN
cana-1862	6	61	:	:	PUNCT
cana-1862	6	62	the	the	DET
cana-1862	6	63	increasing	increase	VERB
cana-1862	6	64	rate	rate	NOUN
cana-1862	6	65	on	on	ADP
cana-1862	6	66	the	the	DET
cana-1862	6	67	complexity	complexity	NOUN
cana-1862	6	68	and	and	CCONJ
cana-1862	6	69	amount	amount	NOUN
cana-1862	6	70	of	of	ADP
cana-1862	6	71	security	security	NOUN
cana-1862	6	72	threats	threat	NOUN
cana-1862	6	73	demand	demand	VERB
cana-1862	6	74	more	more	ADV
cana-1862	6	75	advanced	advanced	ADJ
cana-1862	6	76	information	information	NOUN
cana-1862	6	77	security	security	NOUN
cana-1862	6	78	vulnerability	vulnerability	NOUN
cana-1862	6	79	detection	detection	NOUN
cana-1862	6	80	techniques	technique	NOUN
cana-1862	6	81	.	.	PUNCT
cana-1862	7	1	traditional	traditional	ADJ
cana-1862	7	2	methods	method	NOUN
cana-1862	7	3	have	have	VERB
cana-1862	7	4	limited	limit	VERB
cana-1862	7	5	capability	capability	NOUN
cana-1862	7	6	to	to	PART
cana-1862	7	7	respond	respond	VERB
cana-1862	7	8	to	to	ADP
cana-1862	7	9	such	such	ADJ
cana-1862	7	10	diverse	diverse	ADJ
cana-1862	7	11	and	and	CCONJ
cana-1862	7	12	evolving	evolve	VERB
cana-1862	7	13	threats	threat	NOUN
cana-1862	7	14	in	in	ADP
cana-1862	7	15	real	real	ADJ
cana-1862	7	16	-	-	PUNCT
cana-1862	7	17	time	time	NOUN
cana-1862	7	18	.	.	PUNCT
cana-1862	8	1	this	this	DET
cana-1862	8	2	paper	paper	NOUN
cana-1862	8	3	presents	present	VERB
cana-1862	8	4	a	a	DET
cana-1862	8	5	complete	complete	ADJ
cana-1862	8	6	solution	solution	NOUN
cana-1862	8	7	by	by	ADP
cana-1862	8	8	using	use	VERB
cana-1862	8	9	new	new	ADJ
cana-1862	8	10	machine	machine	NOUN
cana-1862	8	11	learning	learning	NOUN
cana-1862	8	12	models	model	NOUN
cana-1862	8	13	in	in	ADP
cana-1862	8	14	combine	combine	NOUN
cana-1862	8	15	with	with	ADP
cana-1862	8	16	advanced	advanced	ADJ
cana-1862	8	17	mathematical	mathematical	ADJ
cana-1862	8	18	approaches	approach	NOUN
cana-1862	8	19	to	to	PART
cana-1862	8	20	organize	organize	VERB
cana-1862	8	21	the	the	DET
cana-1862	8	22	early	early	ADJ
cana-1862	8	23	detection	detection	NOUN
cana-1862	8	24	and	and	CCONJ
cana-1862	8	25	prediction	prediction	NOUN
cana-1862	8	26	of	of	ADP
cana-1862	8	27	vulnerabilities	vulnerability	NOUN
cana-1862	8	28	that	that	PRON
cana-1862	8	29	later	later	ADV
cana-1862	8	30	content	content	NOUN
cana-1862	8	31	will	will	AUX
cana-1862	8	32	be	be	AUX
cana-1862	8	33	about	about	ADP
cana-1862	8	34	the	the	DET
cana-1862	8	35	information	information	NOUN
cana-1862	8	36	security	security	NOUN
cana-1862	8	37	systems	system	NOUN
cana-1862	8	38	.	.	PUNCT
cana-1862	9	1	we	we	PRON
cana-1862	9	2	investigate	investigate	VERB
cana-1862	9	3	the	the	DET
cana-1862	9	4	accuracy	accuracy	NOUN
cana-1862	9	5	of	of	ADP
cana-1862	9	6	different	different	ADJ
cana-1862	9	7	models	model	NOUN
cana-1862	9	8	(	(	PUNCT
cana-1862	9	9	with	with	ADP
cana-1862	9	10	an	an	DET
cana-1862	9	11	emphasis	emphasis	NOUN
cana-1862	9	12	on	on	ADP
cana-1862	9	13	modern	modern	ADJ
cana-1862	9	14	approaches	approach	NOUN
cana-1862	9	15	that	that	PRON
cana-1862	9	16	go	go	VERB
cana-1862	9	17	beyond	beyond	ADP
cana-1862	9	18	the	the	DET
cana-1862	9	19	standard	standard	ADJ
cana-1862	9	20	svm	svm	PROPN
cana-1862	9	21	,	,	PUNCT
cana-1862	9	22	cnn	cnn	PROPN
cana-1862	9	23	,	,	PUNCT
cana-1862	9	24	and	and	CCONJ
cana-1862	9	25	gnn	gnn	PROPN
cana-1862	9	26	)	)	PUNCT
cana-1862	9	27	.	.	PUNCT
cana-1862	10	1	it	it	PRON
cana-1862	10	2	initiates	initiate	VERB
cana-1862	10	3	with	with	ADP
cana-1862	10	4	bayesian	bayesian	NOUN
cana-1862	10	5	networks	network	NOUN
cana-1862	10	6	that	that	PRON
cana-1862	10	7	use	use	VERB
cana-1862	10	8	probabilistic	probabilistic	ADJ
cana-1862	10	9	graphical	graphical	ADJ
cana-1862	10	10	models	model	NOUN
cana-1862	10	11	for	for	ADP
cana-1862	10	12	showing	show	VERB
cana-1862	10	13	the	the	DET
cana-1862	10	14	interactions	interaction	NOUN
cana-1862	10	15	of	of	ADP
cana-1862	10	16	diverse	diverse	ADJ
cana-1862	10	17	security	security	NOUN
cana-1862	10	18	characteristics	characteristic	NOUN
cana-1862	10	19	to	to	PART
cana-1862	10	20	support	support	VERB
cana-1862	10	21	reasoning	reasoning	NOUN
cana-1862	10	22	about	about	ADP
cana-1862	10	23	vulnerabilities	vulnerability	NOUN
cana-1862	10	24	as	as	ADP
cana-1862	10	25	a	a	DET
cana-1862	10	26	function	function	NOUN
cana-1862	10	27	on	on	ADP
cana-1862	10	28	the	the	DET
cana-1862	10	29	conditional	conditional	ADJ
cana-1862	10	30	dependencies	dependency	NOUN
cana-1862	10	31	.	.	PUNCT
cana-1862	11	1	decision	decision	NOUN
cana-1862	11	2	trees	tree	NOUN
cana-1862	11	3	and	and	CCONJ
cana-1862	11	4	ensemble	ensemble	ADJ
cana-1862	11	5	techniques	technique	NOUN
cana-1862	11	6	like	like	ADP
cana-1862	11	7	extreme	extreme	ADJ
cana-1862	11	8	gradient	gradient	NOUN
cana-1862	11	9	boosting	boost	VERB
cana-1862	11	10	(	(	PUNCT
cana-1862	11	11	xgboost	xgboost	X
cana-1862	11	12	)	)	PUNCT
cana-1862	11	13	are	be	AUX
cana-1862	11	14	able	able	ADJ
cana-1862	11	15	to	to	PART
cana-1862	11	16	deal	deal	VERB
cana-1862	11	17	with	with	ADP
cana-1862	11	18	both	both	CCONJ
cana-1862	11	19	heterogeneous	heterogeneous	ADJ
cana-1862	11	20	data	datum	NOUN
cana-1862	11	21	types	type	NOUN
cana-1862	11	22	and	and	CCONJ
cana-1862	11	23	are	be	AUX
cana-1862	11	24	more	more	ADV
cana-1862	11	25	capable	capable	ADJ
cana-1862	11	26	of	of	ADP
cana-1862	11	27	modelling	model	VERB
cana-1862	11	28	complex	complex	ADJ
cana-1862	11	29	interaction	interaction	NOUN
cana-1862	11	30	between	between	ADP
cana-1862	11	31	security	security	NOUN
cana-1862	11	32	features	feature	NOUN
cana-1862	11	33	.	.	PUNCT
cana-1862	12	1	for	for	ADP
cana-1862	12	2	unsupervised	unsupervised	ADJ
cana-1862	12	3	cases	case	NOUN
cana-1862	12	4	,	,	PUNCT
cana-1862	12	5	we	we	PRON
cana-1862	12	6	use	use	VERB
cana-1862	12	7	things	thing	NOUN
cana-1862	12	8	like	like	ADP
cana-1862	12	9	isolation	isolation	NOUN
cana-1862	12	10	forests	forest	NOUN
cana-1862	12	11	for	for	ADP
cana-1862	12	12	anomaly	anomaly	NOUN
cana-1862	12	13	detection	detection	NOUN
cana-1862	12	14	and	and	CCONJ
cana-1862	12	15	gaussian	gaussian	ADJ
cana-1862	12	16	mixture	mixture	NOUN
cana-1862	12	17	models	model	NOUN
cana-1862	12	18	(	(	PUNCT
cana-1862	12	19	gmm	gmm	NOUN
cana-1862	12	20	)	)	PUNCT
cana-1862	12	21	to	to	PART
cana-1862	12	22	detect	detect	VERB
cana-1862	12	23	rare	rare	ADJ
cana-1862	12	24	patterns	pattern	NOUN
cana-1862	12	25	in	in	ADP
cana-1862	12	26	network	network	NOUN
cana-1862	12	27	packets	packet	NOUN
cana-1862	12	28	that	that	PRON
cana-1862	12	29	may	may	AUX
cana-1862	12	30	be	be	AUX
cana-1862	12	31	a	a	DET
cana-1862	12	32	sign	sign	NOUN
cana-1862	12	33	of	of	ADP
cana-1862	12	34	security	security	NOUN
cana-1862	12	35	attacks	attack	NOUN
cana-1862	12	36	.	.	PUNCT
cana-1862	13	1	we	we	PRON
cana-1862	13	2	further	far	ADV
cana-1862	13	3	investigate	investigate	VERB
cana-1862	13	4	the	the	DET
cana-1862	13	5	possibility	possibility	NOUN
cana-1862	13	6	of	of	ADP
cana-1862	13	7	reinforcement	reinforcement	NOUN
cana-1862	13	8	learning	learning	NOUN
cana-1862	13	9	(	(	PUNCT
cana-1862	13	10	i.e.	i.e.	X
cana-1862	13	11	,	,	PUNCT
cana-1862	13	12	q	q	X
cana-1862	13	13	-	-	PUNCT
cana-1862	13	14	learning	learning	NOUN
cana-1862	13	15	)	)	PUNCT
cana-1862	13	16	to	to	PART
cana-1862	13	17	continue	continue	VERB
cana-1862	13	18	to	to	PART
cana-1862	13	19	evolve	evolve	VERB
cana-1862	13	20	with	with	ADP
cana-1862	13	21	network	network	NOUN
cana-1862	13	22	changes	change	NOUN
cana-1862	13	23	and	and	CCONJ
cana-1862	13	24	identify	identify	VERB
cana-1862	13	25	threats	threat	NOUN
cana-1862	13	26	in	in	ADP
cana-1862	13	27	real	real	ADJ
cana-1862	13	28	-	-	PUNCT
cana-1862	13	29	world	world	NOUN
cana-1862	13	30	threatening	threaten	VERB
cana-1862	13	31	environment	environment	NOUN
cana-1862	13	32	.	.	PUNCT
cana-1862	14	1	the	the	DET
cana-1862	14	2	learning	learning	NOUN
cana-1862	14	3	process	process	NOUN
cana-1862	14	4	is	be	AUX
cana-1862	14	5	streamlined	streamline	VERB
cana-1862	14	6	and	and	CCONJ
cana-1862	14	7	the	the	DET
cana-1862	14	8	interpretability	interpretability	NOUN
cana-1862	14	9	of	of	ADP
cana-1862	14	10	results	result	NOUN
cana-1862	14	11	is	be	AUX
cana-1862	14	12	improved	improve	VERB
cana-1862	14	13	by	by	ADP
cana-1862	14	14	integrating	integrate	VERB
cana-1862	14	15	mathematical	mathematical	ADJ
cana-1862	14	16	techniques	technique	NOUN
cana-1862	14	17	such	such	ADJ
cana-1862	14	18	as	as	ADP
cana-1862	14	19	markov	markov	NOUN
cana-1862	14	20	chains	chain	NOUN
cana-1862	14	21	(	(	PUNCT
cana-1862	14	22	for	for	ADP
cana-1862	14	23	modelling	model	VERB
cana-1862	14	24	probabilistic	probabilistic	ADJ
cana-1862	14	25	transitions	transition	NOUN
cana-1862	14	26	within	within	ADP
cana-1862	14	27	network	network	NOUN
cana-1862	14	28	states	state	NOUN
cana-1862	14	29	)	)	PUNCT
cana-1862	14	30	and	and	CCONJ
cana-1862	14	31	optimization	optimization	NOUN
cana-1862	14	32	methods	method	NOUN
cana-1862	14	33	like	like	ADP
cana-1862	14	34	lasso	lasso	NOUN
cana-1862	14	35	regression	regression	NOUN
cana-1862	14	36	(	(	PUNCT
cana-1862	14	37	for	for	ADP
cana-1862	14	38	feature	feature	NOUN
cana-1862	14	39	selection	selection	NOUN
cana-1862	14	40	)	)	PUNCT
cana-1862	14	41	.	.	PUNCT
cana-1862	15	1	in	in	ADP
cana-1862	15	2	addition	addition	NOUN
cana-1862	15	3	to	to	ADP
cana-1862	15	4	this	this	PRON
cana-1862	15	5	,	,	PUNCT
cana-1862	15	6	the	the	DET
cana-1862	15	7	approach	approach	NOUN
cana-1862	15	8	explores	explore	VERB
cana-1862	15	9	autoencoder	autoencoder	NOUN
cana-1862	15	10	-	-	PUNCT
cana-1862	15	11	based	base	VERB
cana-1862	15	12	models	model	NOUN
cana-1862	15	13	but	but	CCONJ
cana-1862	15	14	most	most	ADV
cana-1862	15	15	specifically	specifically	ADV
cana-1862	15	16	variational	variational	ADJ
cana-1862	15	17	autoencoders	autoencoder	NOUN
cana-1862	15	18	(	(	PUNCT
cana-1862	15	19	vaes	vaes	ADJ
cana-1862	15	20	)	)	PUNCT
cana-1862	15	21	for	for	ADP
cana-1862	15	22	their	their	PRON
cana-1862	15	23	unsupervised	unsupervised	ADJ
cana-1862	15	24	learning	learning	NOUN
cana-1862	15	25	ability	ability	NOUN
cana-1862	15	26	in	in	ADP
cana-1862	15	27	identifying	identify	VERB
cana-1862	15	28	rare	rare	ADJ
cana-1862	15	29	and	and	CCONJ
cana-1862	15	30	new	new	ADJ
cana-1862	15	31	zero	zero	NUM
cana-1862	15	32	-	-	PUNCT
cana-1862	15	33	day	day	NOUN
cana-1862	15	34	vulnerabilities	vulnerability	NOUN
cana-1862	15	35	.	.	PUNCT
cana-1862	16	1	extensive	extensive	ADJ
cana-1862	16	2	experiments	experiment	NOUN
cana-1862	16	3	on	on	ADP
cana-1862	16	4	a	a	DET
cana-1862	16	5	variety	variety	NOUN
cana-1862	16	6	of	of	ADP
cana-1862	16	7	cybersecurity	cybersecurity	NOUN
cana-1862	16	8	datasets	dataset	NOUN
cana-1862	16	9	demonstrate	demonstrate	VERB
cana-1862	16	10	the	the	DET
cana-1862	16	11	effectiveness	effectiveness	NOUN
cana-1862	16	12	and	and	CCONJ
cana-1862	16	13	efficiency	efficiency	NOUN
cana-1862	16	14	of	of	ADP
cana-1862	16	15	our	our	PRON
cana-1862	16	16	approach	approach	NOUN
cana-1862	16	17	,	,	PUNCT
cana-1862	16	18	where	where	SCONJ
cana-1862	16	19	substantial	substantial	ADJ
cana-1862	16	20	enhancements	enhancement	NOUN
cana-1862	16	21	in	in	ADP
cana-1862	16	22	detection	detection	NOUN
cana-1862	16	23	speed	speed	NOUN
cana-1862	16	24	and	and	CCONJ
cana-1862	16	25	accuracy	accuracy	NOUN
cana-1862	16	26	are	be	AUX
cana-1862	16	27	achieved	achieve	VERB
cana-1862	16	28	.	.	PUNCT
cana-1862	17	1	the	the	DET
cana-1862	17	2	cloud	cloud	NOUN
cana-1862	17	3	-	-	PUNCT
cana-1862	17	4	based	base	VERB
cana-1862	17	5	cybersecurity	cybersecurity	NOUN
cana-1862	17	6	model	model	NOUN
cana-1862	17	7	introduced	introduce	VERB
cana-1862	17	8	in	in	ADP
cana-1862	17	9	this	this	DET
cana-1862	17	10	research	research	NOUN
cana-1862	17	11	,	,	PUNCT
cana-1862	17	12	backed	back	VERB
cana-1862	17	13	by	by	ADP
cana-1862	17	14	advanced	advanced	ADJ
cana-1862	17	15	machine	machine	NOUN
cana-1862	17	16	learning	learning	NOUN
cana-1862	17	17	models	model	NOUN
cana-1862	17	18	and	and	CCONJ
cana-1862	17	19	mathematical	mathematical	ADJ
cana-1862	17	20	frameworks	framework	NOUN
cana-1862	17	21	could	could	AUX
cana-1862	17	22	mailto:champa.tanga@gmail.com	mailto:champa.tanga@gmail.com	X
cana-1862	17	23	mailto:connectmadhukar@gmail.com	mailto:connectmadhukar@gmail.com	PROPN
cana-1862	17	24	mailto:mahalakshmi.a@msrit.edu	mailto:mahalakshmi.a@msrit.edu	VERB
cana-1862	17	25	mailto:pkhemalathamsc@gmail.com	mailto:pkhemalathamsc@gmail.com	PROPN
cana-1862	17	26	mailto:tareek.pattewar@vupune.ac.in	mailto:tareek.pattewar@vupune.ac.in	PROPN
cana-1862	17	27	mailto:nargis.norulhaq@nbu.edu.sa	mailto:nargis.norulhaq@nbu.edu.sa	NOUN
cana-1862	17	28	communications	communication	NOUN
cana-1862	17	29	on	on	ADP
cana-1862	17	30	applied	apply	VERB
cana-1862	17	31	nonlinear	nonlinear	ADJ
cana-1862	17	32	analysis	analysis	NOUN
cana-1862	17	33	issn	issn	NOUN
cana-1862	17	34	:	:	PUNCT
cana-1862	17	35	1074	1074	NUM
cana-1862	17	36	-	-	PUNCT
cana-1862	17	37	133x	133x	NUM
cana-1862	17	38	vol	vol	NOUN
cana-1862	17	39	32	32	NUM
cana-1862	17	40	no	no	NOUN
cana-1862	17	41	.	.	NOUN
cana-1862	17	42	2	2	NUM
cana-1862	17	43	(	(	PUNCT
cana-1862	17	44	2025	2025	NUM
cana-1862	17	45	)	)	PUNCT
cana-1862	17	46	693	693	NUM
cana-1862	17	47	https://internationalpubls.com	https://internationalpubls.com	X
cana-1862	17	48	potentially	potentially	ADV
cana-1862	17	49	serve	serve	VERB
cana-1862	17	50	to	to	PART
cana-1862	17	51	lay	lay	VERB
cana-1862	17	52	a	a	DET
cana-1862	17	53	foundation	foundation	NOUN
cana-1862	17	54	for	for	ADP
cana-1862	17	55	the	the	DET
cana-1862	17	56	future	future	NOUN
cana-1862	17	57	of	of	ADP
cana-1862	17	58	real	real	ADJ
cana-1862	17	59	-	-	PUNCT
cana-1862	17	60	time	time	NOUN
cana-1862	17	61	cyber	cyber	NOUN
cana-1862	17	62	security	security	NOUN
cana-1862	17	63	defence	defence	NOUN
cana-1862	17	64	mechanisms	mechanism	NOUN
cana-1862	17	65	.	.	PUNCT
cana-1862	18	1	keywords	keyword	NOUN
cana-1862	18	2	:	:	PUNCT
cana-1862	18	3	complexity	complexity	NOUN
cana-1862	18	4	,	,	PUNCT
cana-1862	18	5	decision	decision	NOUN
cana-1862	18	6	,	,	PUNCT
cana-1862	18	7	unsupervised	unsupervised	ADJ
cana-1862	18	8	,	,	PUNCT
cana-1862	18	9	detection	detection	NOUN
cana-1862	18	10	,	,	PUNCT
cana-1862	18	11	datasets	dataset	NOUN
cana-1862	18	12	,	,	PUNCT
cana-1862	18	13	security	security	NOUN
cana-1862	18	14	,	,	PUNCT
cana-1862	18	15	network	network	NOUN
cana-1862	18	16	,	,	PUNCT
cana-1862	18	17	mechanisms	mechanism	NOUN
cana-1862	18	18	.	.	PUNCT
cana-1862	19	1	1	1	X
cana-1862	19	2	.	.	X
cana-1862	19	3	introduction	introduction	NOUN
cana-1862	19	4	:	:	PUNCT
cana-1862	19	5	traditional	traditional	ADJ
cana-1862	19	6	security	security	NOUN
cana-1862	19	7	mechanisms	mechanism	NOUN
cana-1862	19	8	are	be	AUX
cana-1862	19	9	being	be	AUX
cana-1862	19	10	put	put	VERB
cana-1862	19	11	to	to	ADP
cana-1862	19	12	the	the	DET
cana-1862	19	13	test	test	NOUN
cana-1862	19	14	as	as	SCONJ
cana-1862	19	15	cyber	cyber	NOUN
cana-1862	19	16	threats	threat	NOUN
cana-1862	19	17	increase	increase	VERB
cana-1862	19	18	in	in	ADP
cana-1862	19	19	complexity	complexity	NOUN
cana-1862	19	20	and	and	CCONJ
cana-1862	19	21	volume	volume	NOUN
cana-1862	19	22	,	,	PUNCT
cana-1862	19	23	making	make	VERB
cana-1862	19	24	it	it	PRON
cana-1862	19	25	much	much	ADV
cana-1862	19	26	harder	hard	ADV
cana-1862	19	27	for	for	SCONJ
cana-1862	19	28	them	they	PRON
cana-1862	19	29	to	to	PART
cana-1862	19	30	detect	detect	VERB
cana-1862	19	31	vulnerabilities	vulnerability	NOUN
cana-1862	19	32	effectively	effectively	ADV
cana-1862	19	33	.	.	PUNCT
cana-1862	20	1	the	the	DET
cana-1862	20	2	basic	basic	ADJ
cana-1862	20	3	foundation	foundation	NOUN
cana-1862	20	4	of	of	ADP
cana-1862	20	5	cyber	cyber	PROPN
cana-1862	20	6	security	security	NOUN
cana-1862	20	7	is	be	AUX
cana-1862	20	8	to	to	PART
cana-1862	20	9	identify	identify	VERB
cana-1862	20	10	and	and	CCONJ
cana-1862	20	11	remediate	remediate	VERB
cana-1862	20	12	the	the	DET
cana-1862	20	13	security	security	NOUN
cana-1862	20	14	vulnerabilities	vulnerability	NOUN
cana-1862	20	15	before	before	SCONJ
cana-1862	20	16	it	it	PRON
cana-1862	20	17	could	could	AUX
cana-1862	20	18	be	be	AUX
cana-1862	20	19	used	use	VERB
cana-1862	20	20	against	against	ADP
cana-1862	20	21	an	an	DET
cana-1862	20	22	organization	organization	NOUN
cana-1862	20	23	.	.	PUNCT
cana-1862	21	1	traditional	traditional	ADJ
cana-1862	21	2	methods	method	NOUN
cana-1862	21	3	like	like	ADP
cana-1862	21	4	signatures	signature	NOUN
cana-1862	21	5	and	and	CCONJ
cana-1862	21	6	rules	rule	NOUN
cana-1862	21	7	are	be	AUX
cana-1862	21	8	often	often	ADV
cana-1862	21	9	ill	ill	ADV
cana-1862	21	10	-	-	PUNCT
cana-1862	21	11	equipped	equipped	ADJ
cana-1862	21	12	to	to	PART
cana-1862	21	13	identify	identify	VERB
cana-1862	21	14	new	new	ADJ
cana-1862	21	15	or	or	CCONJ
cana-1862	21	16	complicated	complicated	ADJ
cana-1862	21	17	attacks	attack	NOUN
cana-1862	21	18	,	,	PUNCT
cana-1862	21	19	thus	thus	ADV
cana-1862	21	20	necessitating	necessitate	VERB
cana-1862	21	21	more	more	ADV
cana-1862	21	22	advanced	advanced	ADJ
cana-1862	21	23	means	mean	NOUN
cana-1862	21	24	of	of	ADP
cana-1862	21	25	detection	detection	NOUN
cana-1862	21	26	.	.	PUNCT
cana-1862	22	1	in	in	ADP
cana-1862	22	2	machine	machine	NOUN
cana-1862	22	3	learning	learning	NOUN
cana-1862	22	4	,	,	PUNCT
cana-1862	22	5	over	over	ADP
cana-1862	22	6	the	the	DET
cana-1862	22	7	past	past	ADJ
cana-1862	22	8	few	few	ADJ
cana-1862	22	9	years	year	NOUN
cana-1862	22	10	this	this	DET
cana-1862	22	11	concept	concept	NOUN
cana-1862	22	12	of	of	ADP
cana-1862	22	13	using	use	VERB
cana-1862	22	14	machine	machine	NOUN
cana-1862	22	15	learning	learning	NOUN
cana-1862	22	16	with	with	ADP
cana-1862	22	17	math	math	NOUN
cana-1862	22	18	techniques	technique	NOUN
cana-1862	22	19	has	have	AUX
cana-1862	22	20	gained	gain	VERB
cana-1862	22	21	a	a	DET
cana-1862	22	22	lot	lot	NOUN
cana-1862	22	23	of	of	ADP
cana-1862	22	24	traction	traction	NOUN
cana-1862	22	25	and	and	CCONJ
cana-1862	22	26	also	also	ADV
cana-1862	22	27	proven	prove	VERB
cana-1862	22	28	itself	itself	PRON
cana-1862	22	29	as	as	ADP
cana-1862	22	30	an	an	DET
cana-1862	22	31	effective	effective	ADJ
cana-1862	22	32	way	way	NOUN
cana-1862	22	33	to	to	PART
cana-1862	22	34	improve	improve	VERB
cana-1862	22	35	your	your	PRON
cana-1862	22	36	vulnerability	vulnerability	NOUN
cana-1862	22	37	detection	detection	NOUN
cana-1862	22	38	.	.	PUNCT
cana-1862	23	1	in	in	ADP
cana-1862	23	2	this	this	DET
cana-1862	23	3	paper	paper	NOUN
cana-1862	23	4	,	,	PUNCT
cana-1862	23	5	we	we	PRON
cana-1862	23	6	probe	probe	VERB
cana-1862	23	7	deeper	deeply	ADV
cana-1862	23	8	into	into	ADP
cana-1862	23	9	how	how	SCONJ
cana-1862	23	10	state	state	NOUN
cana-1862	23	11	-	-	PUNCT
cana-1862	23	12	of	of	ADP
cana-1862	23	13	-	-	PUNCT
cana-1862	23	14	the	the	DET
cana-1862	23	15	-	-	PUNCT
cana-1862	23	16	art	art	NOUN
cana-1862	23	17	machine	machine	NOUN
cana-1862	23	18	learning	learning	NOUN
cana-1862	23	19	models	model	NOUN
cana-1862	23	20	can	can	AUX
cana-1862	23	21	complement	complement	VERB
cana-1862	23	22	sophisticated	sophisticated	ADJ
cana-1862	23	23	mathematical	mathematical	ADJ
cana-1862	23	24	frameworks	framework	NOUN
cana-1862	23	25	in	in	ADP
cana-1862	23	26	the	the	DET
cana-1862	23	27	realm	realm	NOUN
cana-1862	23	28	of	of	ADP
cana-1862	23	29	information	information	NOUN
cana-1862	23	30	security	security	NOUN
cana-1862	23	31	vulnerability	vulnerability	NOUN
cana-1862	23	32	detection[1	detection[1	PROPN
cana-1862	23	33	]	]	X
cana-1862	23	34	.	.	PUNCT
cana-1862	24	1	●	●	PUNCT
cana-1862	24	2	mathematical	mathematical	ADJ
cana-1862	24	3	approaches	approach	NOUN
cana-1862	24	4	to	to	ADP
cana-1862	24	5	vulnerability	vulnerability	NOUN
cana-1862	24	6	detection	detection	NOUN
cana-1862	24	7	:	:	PUNCT
cana-1862	24	8	mathematics	mathematic	NOUN
cana-1862	24	9	is	be	AUX
cana-1862	24	10	the	the	DET
cana-1862	24	11	backbone	backbone	NOUN
cana-1862	24	12	of	of	ADP
cana-1862	24	13	many	many	ADJ
cana-1862	24	14	algorithms	algorithm	NOUN
cana-1862	24	15	and	and	CCONJ
cana-1862	24	16	methods	method	NOUN
cana-1862	24	17	in	in	ADP
cana-1862	24	18	machine	machine	NOUN
cana-1862	24	19	learning	learning	NOUN
cana-1862	24	20	and	and	CCONJ
cana-1862	24	21	data	datum	NOUN
cana-1862	24	22	analysis	analysis	NOUN
cana-1862	24	23	.	.	PUNCT
cana-1862	25	1	mathematical	mathematical	ADJ
cana-1862	25	2	methods	method	NOUN
cana-1862	25	3	play	play	VERB
cana-1862	25	4	critical	critical	ADJ
cana-1862	25	5	roles	role	NOUN
cana-1862	25	6	in	in	ADP
cana-1862	25	7	information	information	NOUN
cana-1862	25	8	security	security	NOUN
cana-1862	25	9	,	,	PUNCT
cana-1862	25	10	including	include	VERB
cana-1862	25	11	data	datum	NOUN
cana-1862	25	12	pre	pre	ADJ
cana-1862	25	13	-	-	ADJ
cana-1862	25	14	processing	processing	ADJ
cana-1862	25	15	,	,	PUNCT
cana-1862	25	16	feature	feature	NOUN
cana-1862	25	17	extraction	extraction	NOUN
cana-1862	25	18	,	,	PUNCT
cana-1862	25	19	dimension	dimension	NOUN
cana-1862	25	20	reduction	reduction	NOUN
cana-1862	25	21	,	,	PUNCT
cana-1862	25	22	anomaly	anomaly	NOUN
cana-1862	25	23	detection	detection	NOUN
cana-1862	25	24	,	,	PUNCT
cana-1862	25	25	and	and	CCONJ
cana-1862	25	26	model	model	NOUN
cana-1862	25	27	optimization	optimization	NOUN
cana-1862	25	28	.	.	PUNCT
cana-1862	26	1	important	important	ADJ
cana-1862	26	2	mathematical	mathematical	ADJ
cana-1862	26	3	methods	method	NOUN
cana-1862	26	4	applied	apply	VERB
cana-1862	26	5	in	in	ADP
cana-1862	26	6	cybersecurity[2	cybersecurity[2	PROPN
cana-1862	26	7	]	]	PUNCT
cana-1862	26	8	.	.	PUNCT
cana-1862	27	1	o	o	X
cana-1862	27	2	linear	linear	ADJ
cana-1862	27	3	algebra	algebra	NOUN
cana-1862	27	4	and	and	CCONJ
cana-1862	27	5	matrix	matrix	NOUN
cana-1862	27	6	factorization	factorization	NOUN
cana-1862	27	7	:	:	PUNCT
cana-1862	27	8	commonly	commonly	ADV
cana-1862	27	9	applied	apply	VERB
cana-1862	27	10	for	for	ADP
cana-1862	27	11	the	the	DET
cana-1862	27	12	purpose	purpose	NOUN
cana-1862	27	13	of	of	ADP
cana-1862	27	14	data	datum	NOUN
cana-1862	27	15	representation	representation	NOUN
cana-1862	27	16	,	,	PUNCT
cana-1862	27	17	linear	linear	ADJ
cana-1862	27	18	algebra	algebra	NOUN
cana-1862	27	19	can	can	AUX
cana-1862	27	20	be	be	AUX
cana-1862	27	21	used	use	VERB
cana-1862	27	22	to	to	PART
cana-1862	27	23	retain	retain	VERB
cana-1862	27	24	significant	significant	ADJ
cana-1862	27	25	variance	variance	NOUN
cana-1862	27	26	by	by	ADP
cana-1862	27	27	collapsing	collapse	VERB
cana-1862	27	28	high	high	ADJ
cana-1862	27	29	-	-	PUNCT
cana-1862	27	30	dimensional	dimensional	ADJ
cana-1862	27	31	data	datum	NOUN
cana-1862	27	32	into	into	ADP
cana-1862	27	33	lower	low	ADJ
cana-1862	27	34	dimensions	dimension	NOUN
cana-1862	27	35	.	.	PUNCT
cana-1862	28	1	such	such	ADJ
cana-1862	28	2	dimensionality	dimensionality	NOUN
cana-1862	28	3	reduction	reduction	NOUN
cana-1862	28	4	is	be	AUX
cana-1862	28	5	crucial	crucial	ADJ
cana-1862	28	6	in	in	ADP
cana-1862	28	7	large	large	ADJ
cana-1862	28	8	-	-	PUNCT
cana-1862	28	9	scale	scale	NOUN
cana-1862	28	10	network	network	NOUN
cana-1862	28	11	data	datum	NOUN
cana-1862	28	12	for	for	ADP
cana-1862	28	13	gaining	gain	VERB
cana-1862	28	14	insights	insight	NOUN
cana-1862	28	15	on	on	ADP
cana-1862	28	16	patterns	pattern	NOUN
cana-1862	28	17	reflecting	reflect	VERB
cana-1862	28	18	security	security	NOUN
cana-1862	28	19	vulnerabilities	vulnerability	NOUN
cana-1862	28	20	.	.	PUNCT
cana-1862	29	1	o	o	X
cana-1862	29	2	optimization	optimization	NOUN
cana-1862	29	3	techniques	technique	NOUN
cana-1862	29	4	:	:	PUNCT
cana-1862	29	5	machine	machine	NOUN
cana-1862	29	6	learning	learn	VERB
cana-1862	29	7	algorithms	algorithm	NOUN
cana-1862	29	8	work	work	VERB
cana-1862	29	9	on	on	ADP
cana-1862	29	10	minimizing	minimize	VERB
cana-1862	29	11	cost	cost	NOUN
cana-1862	29	12	functions	function	NOUN
cana-1862	29	13	and	and	CCONJ
cana-1862	29	14	optimization	optimization	NOUN
cana-1862	29	15	is	be	AUX
cana-1862	29	16	something	something	PRON
cana-1862	29	17	which	which	PRON
cana-1862	29	18	needs	need	VERB
cana-1862	29	19	to	to	PART
cana-1862	29	20	be	be	AUX
cana-1862	29	21	checked	check	VERB
cana-1862	29	22	on	on	ADP
cana-1862	29	23	whether	whether	SCONJ
cana-1862	29	24	model	model	NOUN
cana-1862	29	25	accuracy	accuracy	NOUN
cana-1862	29	26	would	would	AUX
cana-1862	29	27	increase	increase	VERB
cana-1862	29	28	or	or	CCONJ
cana-1862	29	29	decrease	decrease	VERB
cana-1862	29	30	.	.	PUNCT
cana-1862	30	1	some	some	PRON
cana-1862	30	2	of	of	ADP
cana-1862	30	3	the	the	DET
cana-1862	30	4	optimization	optimization	NOUN
cana-1862	30	5	techniques	technique	NOUN
cana-1862	30	6	(	(	PUNCT
cana-1862	30	7	gradient	gradient	ADJ
cana-1862	30	8	descent	descent	NOUN
cana-1862	30	9	,	,	PUNCT
cana-1862	30	10	newton	newton	PROPN
cana-1862	30	11	's	's	PART
cana-1862	30	12	method	method	NOUN
cana-1862	30	13	and	and	CCONJ
cana-1862	30	14	l	l	NOUN
cana-1862	30	15	-	-	ADJ
cana-1862	30	16	bfgs	bfgs	ADJ
cana-1862	30	17	(	(	PUNCT
cana-1862	30	18	limited	limited	ADJ
cana-1862	30	19	-	-	PUNCT
cana-1862	30	20	memory	memory	NOUN
cana-1862	30	21	broyden	broyden	NOUN
cana-1862	30	22	-	-	PUNCT
cana-1862	30	23	fletcher	fletcher	NOUN
cana-1862	30	24	-	-	PUNCT
cana-1862	30	25	goldfarb	goldfarb	NOUN
cana-1862	30	26	-	-	PUNCT
cana-1862	30	27	shanno	shanno	NOUN
cana-1862	30	28	)	)	PUNCT
cana-1862	30	29	)	)	PUNCT
cana-1862	30	30	modify	modify	VERB
cana-1862	30	31	the	the	DET
cana-1862	30	32	model	model	NOUN
cana-1862	30	33	parameters	parameter	NOUN
cana-1862	30	34	for	for	ADP
cana-1862	30	35	training	training	NOUN
cana-1862	30	36	data	datum	NOUN
cana-1862	30	37	detection	detection	NOUN
cana-1862	30	38	better	well	ADJ
cana-1862	30	39	security	security	NOUN
cana-1862	30	40	threats[3	threats[3	NUM
cana-1862	30	41	]	]	PUNCT
cana-1862	30	42	.	.	PUNCT
cana-1862	31	1	o	o	X
cana-1862	31	2	detecting	detect	VERB
cana-1862	31	3	a	a	DET
cana-1862	31	4	vulnerability	vulnerability	NOUN
cana-1862	31	5	through	through	ADP
cana-1862	31	6	probability	probability	NOUN
cana-1862	31	7	&	&	CCONJ
cana-1862	31	8	statistics	statistic	NOUN
cana-1862	31	9	:	:	PUNCT
cana-1862	31	10	vulnerability	vulnerability	NOUN
cana-1862	31	11	detection	detection	NOUN
cana-1862	31	12	often	often	ADV
cana-1862	31	13	contains	contain	VERB
cana-1862	31	14	uncertain	uncertain	ADJ
cana-1862	31	15	and	and	CCONJ
cana-1862	31	16	incomplete	incomplete	ADJ
cana-1862	31	17	information	information	NOUN
cana-1862	31	18	.	.	PUNCT
cana-1862	32	1	for	for	ADP
cana-1862	32	2	example	example	NOUN
cana-1862	32	3	,	,	PUNCT
cana-1862	32	4	one	one	PRON
cana-1862	32	5	will	will	AUX
cana-1862	32	6	then	then	ADV
cana-1862	32	7	try	try	VERB
cana-1862	32	8	to	to	PART
cana-1862	32	9	employ	employ	VERB
cana-1862	32	10	probabilistic	probabilistic	ADJ
cana-1862	32	11	models	model	NOUN
cana-1862	32	12	like	like	ADP
cana-1862	32	13	bayesian	bayesian	NOUN
cana-1862	32	14	networks	network	NOUN
cana-1862	32	15	and	and	CCONJ
cana-1862	32	16	markov	markov	NOUN
cana-1862	32	17	chains	chain	NOUN
cana-1862	32	18	to	to	PART
cana-1862	32	19	model	model	VERB
cana-1862	32	20	the	the	DET
cana-1862	32	21	probability	probability	NOUN
cana-1862	32	22	of	of	ADP
cana-1862	32	23	vulnerabilities	vulnerability	NOUN
cana-1862	32	24	given	give	VERB
cana-1862	32	25	observed	observe	VERB
cana-1862	32	26	data	datum	NOUN
cana-1862	32	27	.	.	PUNCT
cana-1862	33	1	there	there	PRON
cana-1862	33	2	is	be	VERB
cana-1862	33	3	a	a	DET
cana-1862	33	4	need	need	NOUN
cana-1862	33	5	for	for	ADP
cana-1862	33	6	statistical	statistical	ADJ
cana-1862	33	7	analysis	analysis	NOUN
cana-1862	33	8	methods	method	NOUN
cana-1862	33	9	to	to	PART
cana-1862	33	10	determine	determine	VERB
cana-1862	33	11	the	the	DET
cana-1862	33	12	significance	significance	NOUN
cana-1862	33	13	of	of	ADP
cana-1862	33	14	anomalies	anomaly	NOUN
cana-1862	33	15	,	,	PUNCT
cana-1862	33	16	including	include	VERB
cana-1862	33	17	clues	clue	NOUN
cana-1862	33	18	in	in	ADP
cana-1862	33	19	network	network	NOUN
cana-1862	33	20	traffic	traffic	NOUN
cana-1862	33	21	that	that	PRON
cana-1862	33	22	provide	provide	VERB
cana-1862	33	23	evidence	evidence	NOUN
cana-1862	33	24	on	on	ADP
cana-1862	33	25	detecting	detect	VERB
cana-1862	33	26	whether	whether	SCONJ
cana-1862	33	27	an	an	DET
cana-1862	33	28	activity	activity	NOUN
cana-1862	33	29	that	that	PRON
cana-1862	33	30	produced	produce	VERB
cana-1862	33	31	an	an	DET
cana-1862	33	32	anomaly	anomaly	NOUN
cana-1862	33	33	is	be	AUX
cana-1862	33	34	indeed	indeed	ADV
cana-1862	33	35	a	a	DET
cana-1862	33	36	benign	benign	ADJ
cana-1862	33	37	or	or	CCONJ
cana-1862	33	38	malicious	malicious	ADJ
cana-1862	33	39	.	.	PUNCT
cana-1862	34	1	o	o	NOUN
cana-1862	34	2	using	use	VERB
cana-1862	34	3	graph	graph	NOUN
cana-1862	34	4	theory	theory	NOUN
cana-1862	34	5	:	:	PUNCT
cana-1862	34	6	model	model	NOUN
cana-1862	34	7	network	network	NOUN
cana-1862	34	8	security	security	NOUN
cana-1862	34	9	can	can	AUX
cana-1862	34	10	be	be	AUX
cana-1862	34	11	well	well	ADV
cana-1862	34	12	modelled	model	VERB
cana-1862	34	13	as	as	ADP
cana-1862	34	14	graph	graph	NOUN
cana-1862	34	15	structures	structure	NOUN
cana-1862	34	16	,	,	PUNCT
cana-1862	34	17	in	in	ADP
cana-1862	34	18	which	which	PRON
cana-1862	34	19	the	the	DET
cana-1862	34	20	nodes	node	NOUN
cana-1862	34	21	corresponds	correspond	VERB
cana-1862	34	22	to	to	ADP
cana-1862	34	23	entities	entity	NOUN
cana-1862	34	24	(	(	PUNCT
cana-1862	34	25	e.g.	e.g.	ADV
cana-1862	34	26	,	,	PUNCT
cana-1862	34	27	computers	computer	NOUN
cana-1862	34	28	or	or	CCONJ
cana-1862	34	29	users	user	NOUN
cana-1862	34	30	)	)	PUNCT
cana-1862	34	31	and	and	CCONJ
cana-1862	34	32	edges	edge	NOUN
cana-1862	34	33	represent	represent	VERB
cana-1862	34	34	communication	communication	NOUN
cana-1862	34	35	relationships	relationship	NOUN
cana-1862	34	36	or	or	CCONJ
cana-1862	34	37	data	datum	NOUN
cana-1862	34	38	streams	stream	NOUN
cana-1862	34	39	.	.	PUNCT
cana-1862	35	1	in	in	ADP
cana-1862	35	2	graph	graph	NOUN
cana-1862	35	3	-	-	PUNCT
cana-1862	35	4	based	base	VERB
cana-1862	35	5	approaches	approach	NOUN
cana-1862	35	6	to	to	ADP
cana-1862	35	7	network	network	NOUN
cana-1862	35	8	measurement	measurement	NOUN
cana-1862	35	9	centrality	centrality	NOUN
cana-1862	35	10	measures	measure	NOUN
cana-1862	35	11	,	,	PUNCT
cana-1862	35	12	communications	communication	NOUN
cana-1862	35	13	on	on	ADP
cana-1862	35	14	applied	apply	VERB
cana-1862	35	15	nonlinear	nonlinear	ADJ
cana-1862	35	16	analysis	analysis	NOUN
cana-1862	35	17	issn	issn	NOUN
cana-1862	35	18	:	:	PUNCT
cana-1862	35	19	1074	1074	NUM
cana-1862	35	20	-	-	PUNCT
cana-1862	35	21	133x	133x	NUM
cana-1862	35	22	vol	vol	NOUN
cana-1862	35	23	32	32	NUM
cana-1862	35	24	no	no	NOUN
cana-1862	35	25	.	.	NOUN
cana-1862	35	26	2	2	NUM
cana-1862	35	27	(	(	PUNCT
cana-1862	35	28	2025	2025	NUM
cana-1862	35	29	)	)	PUNCT
cana-1862	35	30	694	694	NUM
cana-1862	35	31	https://internationalpubls.com	https://internationalpubls.com	X
cana-1862	35	32	communities	community	NOUN
cana-1862	35	33	can	can	AUX
cana-1862	35	34	be	be	AUX
cana-1862	35	35	used	use	VERB
cana-1862	35	36	to	to	PART
cana-1862	35	37	diagnose	diagnose	VERB
cana-1862	35	38	vulnerabilities	vulnerability	NOUN
cana-1862	35	39	and	and	CCONJ
cana-1862	35	40	honeypots	honeypot	NOUN
cana-1862	35	41	opportunities	opportunity	NOUN
cana-1862	35	42	of	of	ADP
cana-1862	35	43	the	the	DET
cana-1862	35	44	network	network	NOUN
cana-1862	35	45	topology[4,5	topology[4,5	NOUN
cana-1862	35	46	]	]	PUNCT
cana-1862	35	47	.	.	PUNCT
cana-1862	36	1	o	o	PROPN
cana-1862	36	2	math	math	PROPN
cana-1862	36	3	model	model	PROPN
cana-1862	36	4	numerical	numerical	PROPN
cana-1862	36	5	methods	method	NOUN
cana-1862	36	6	:	:	PUNCT
cana-1862	36	7	(	(	PUNCT
cana-1862	36	8	used	use	VERB
cana-1862	36	9	for	for	ADP
cana-1862	36	10	data	data	NOUN
cana-1862	36	11	exploration	exploration	NOUN
cana-1862	36	12	)	)	PUNCT
cana-1862	36	13	differential	differential	NOUN
cana-1862	36	14	equations	equation	NOUN
cana-1862	36	15	and	and	CCONJ
cana-1862	36	16	system	system	NOUN
cana-1862	36	17	of	of	ADP
cana-1862	36	18	equations	equation	NOUN
cana-1862	36	19	are	be	AUX
cana-1862	36	20	used	use	VERB
cana-1862	36	21	to	to	PART
cana-1862	36	22	model	model	VERB
cana-1862	36	23	how	how	SCONJ
cana-1862	36	24	network	network	NOUN
cana-1862	36	25	systems	system	NOUN
cana-1862	36	26	behave	behave	VERB
cana-1862	36	27	over	over	ADP
cana-1862	36	28	time	time	NOUN
cana-1862	36	29	.	.	PUNCT
cana-1862	37	1	mathematical	mathematical	ADJ
cana-1862	37	2	models	model	NOUN
cana-1862	37	3	help	help	VERB
cana-1862	37	4	to	to	PART
cana-1862	37	5	replicate	replicate	VERB
cana-1862	37	6	multiple	multiple	ADJ
cana-1862	37	7	conditions	condition	NOUN
cana-1862	37	8	in	in	ADP
cana-1862	37	9	the	the	DET
cana-1862	37	10	simulated	simulated	ADJ
cana-1862	37	11	habitation	habitation	NOUN
cana-1862	37	12	of	of	ADP
cana-1862	37	13	security	security	NOUN
cana-1862	37	14	weaknesses	weakness	NOUN
cana-1862	37	15	over	over	ADP
cana-1862	37	16	time	time	NOUN
cana-1862	37	17	.	.	PUNCT
cana-1862	38	1	●	●	PUNCT
cana-1862	38	2	machine	machine	NOUN
cana-1862	38	3	learning	learning	NOUN
cana-1862	38	4	models	model	NOUN
cana-1862	38	5	for	for	ADP
cana-1862	38	6	identifying	identify	VERB
cana-1862	38	7	detecting	detect	VERB
cana-1862	38	8	vulnerabilities	vulnerability	NOUN
cana-1862	38	9	:	:	PUNCT
cana-1862	38	10	by	by	ADP
cana-1862	38	11	leveraging	leverage	VERB
cana-1862	38	12	machine	machine	NOUN
cana-1862	38	13	learning	learning	NOUN
cana-1862	38	14	in	in	ADP
cana-1862	38	15	conjunction	conjunction	NOUN
cana-1862	38	16	with	with	ADP
cana-1862	38	17	sophisticated	sophisticated	ADJ
cana-1862	38	18	mathematical	mathematical	ADJ
cana-1862	38	19	methods	method	NOUN
cana-1862	38	20	,	,	PUNCT
cana-1862	38	21	automated	automate	VERB
cana-1862	38	22	and	and	CCONJ
cana-1862	38	23	smart	smart	ADJ
cana-1862	38	24	vulnerability	vulnerability	NOUN
cana-1862	38	25	identification	identification	NOUN
cana-1862	38	26	capabilities	capability	NOUN
cana-1862	38	27	are	be	AUX
cana-1862	38	28	realised	realise	VERB
cana-1862	38	29	.	.	PUNCT
cana-1862	39	1	model	model	NOUN
cana-1862	39	2	:	:	PUNCT
cana-1862	39	3	based	base	VERB
cana-1862	39	4	on	on	ADP
cana-1862	39	5	the	the	DET
cana-1862	39	6	problem	problem	NOUN
cana-1862	39	7	at	at	ADP
cana-1862	39	8	hand	hand	NOUN
cana-1862	39	9	and	and	CCONJ
cana-1862	39	10	the	the	DET
cana-1862	39	11	type	type	NOUN
cana-1862	39	12	of	of	ADP
cana-1862	39	13	data	datum	NOUN
cana-1862	39	14	,	,	PUNCT
cana-1862	39	15	a	a	DET
cana-1862	39	16	suitable	suitable	ADJ
cana-1862	39	17	model	model	NOUN
cana-1862	39	18	can	can	AUX
cana-1862	39	19	be	be	AUX
cana-1862	39	20	chosen	choose	VERB
cana-1862	39	21	for	for	ADP
cana-1862	39	22	security	security	NOUN
cana-1862	39	23	.	.	PUNCT
cana-1862	40	1	in	in	ADP
cana-1862	40	2	this	this	DET
cana-1862	40	3	article	article	NOUN
cana-1862	40	4	,	,	PUNCT
cana-1862	40	5	we	we	PRON
cana-1862	40	6	will	will	AUX
cana-1862	40	7	discuss	discuss	VERB
cana-1862	40	8	a	a	DET
cana-1862	40	9	few	few	ADJ
cana-1862	40	10	antivirus	antivirus	NOUN
cana-1862	40	11	machine	machine	NOUN
cana-1862	40	12	learning	learning	NOUN
cana-1862	40	13	models	model	NOUN
cana-1862	40	14	that	that	SCONJ
cana-1862	40	15	when	when	SCONJ
cana-1862	40	16	coupled	couple	VERB
cana-1862	40	17	with	with	ADP
cana-1862	40	18	mathematics	mathematic	NOUN
cana-1862	40	19	can	can	AUX
cana-1862	40	20	prove	prove	VERB
cana-1862	40	21	beneficial	beneficial	ADJ
cana-1862	40	22	as	as	ADV
cana-1862	40	23	well	well	ADV
cana-1862	40	24	and	and	CCONJ
cana-1862	40	25	have	have	VERB
cana-1862	40	26	the	the	DET
cana-1862	40	27	ability	ability	NOUN
cana-1862	40	28	to	to	PART
cana-1862	40	29	increase	increase	VERB
cana-1862	40	30	cybersecurity	cybersecurity	NOUN
cana-1862	40	31	.	.	PUNCT
cana-1862	41	1	o	o	NOUN
cana-1862	41	2	income	income	NOUN
cana-1862	41	3	:	:	PUNCT
cana-1862	41	4	using	use	VERB
cana-1862	41	5	bayesian	bayesian	NOUN
cana-1862	41	6	networks	network	NOUN
cana-1862	41	7	to	to	PART
cana-1862	41	8	model	model	VERB
cana-1862	41	9	the	the	DET
cana-1862	41	10	uncertainty	uncertainty	NOUN
cana-1862	41	11	in	in	ADP
cana-1862	41	12	your	your	PRON
cana-1862	41	13	data	data	NOUN
cana-1862	41	14	bayesian	bayesian	NOUN
cana-1862	41	15	networks	network	NOUN
cana-1862	41	16	(	(	PUNCT
cana-1862	41	17	bns	bns	PROPN
cana-1862	41	18	)	)	PUNCT
cana-1862	41	19	are	be	AUX
cana-1862	41	20	graphs	graph	NOUN
cana-1862	41	21	used	use	VERB
cana-1862	41	22	for	for	ADP
cana-1862	41	23	expressing	express	VERB
cana-1862	41	24	the	the	DET
cana-1862	41	25	probabilistic	probabilistic	ADJ
cana-1862	41	26	relationships	relationship	NOUN
cana-1862	41	27	between	between	ADP
cana-1862	41	28	a	a	DET
cana-1862	41	29	set	set	NOUN
cana-1862	41	30	of	of	ADP
cana-1862	41	31	variables	variable	NOUN
cana-1862	41	32	.	.	PUNCT
cana-1862	42	1	in	in	ADP
cana-1862	42	2	information	information	NOUN
cana-1862	42	3	security	security	NOUN
cana-1862	42	4	,	,	PUNCT
cana-1862	42	5	bns	bns	PROPN
cana-1862	42	6	can	can	AUX
cana-1862	42	7	model	model	VERB
cana-1862	42	8	the	the	DET
cana-1862	42	9	aspects	aspect	NOUN
cana-1862	42	10	of	of	ADP
cana-1862	42	11	interdependency	interdependency	NOUN
cana-1862	42	12	between	between	ADP
cana-1862	42	13	different	different	ADJ
cana-1862	42	14	security	security	NOUN
cana-1862	42	15	features	feature	NOUN
cana-1862	42	16	where	where	SCONJ
cana-1862	42	17	vulnerability	vulnerability	NOUN
cana-1862	42	18	in	in	ADP
cana-1862	42	19	one	one	NUM
cana-1862	42	20	feature	feature	NOUN
cana-1862	42	21	can	can	AUX
cana-1862	42	22	depend	depend	VERB
cana-1862	42	23	on	on	ADP
cana-1862	42	24	another	another	PRON
cana-1862	42	25	vulnerabilities[6	vulnerabilities[6	NUM
cana-1862	42	26	]	]	PUNCT
cana-1862	42	27	.	.	PUNCT
cana-1862	43	1	among	among	ADP
cana-1862	43	2	others	other	NOUN
cana-1862	43	3	,	,	PUNCT
cana-1862	43	4	a	a	DET
cana-1862	43	5	bayesian	bayesian	NOUN
cana-1862	43	6	network	network	NOUN
cana-1862	43	7	can	can	AUX
cana-1862	43	8	be	be	AUX
cana-1862	43	9	used	use	VERB
cana-1862	43	10	to	to	PART
cana-1862	43	11	represent	represent	VERB
cana-1862	43	12	which	which	DET
cana-1862	43	13	network	network	NOUN
cana-1862	43	14	traffic	traffic	NOUN
cana-1862	43	15	patterns	pattern	NOUN
cana-1862	43	16	may	may	AUX
cana-1862	43	17	suggest	suggest	VERB
cana-1862	43	18	that	that	SCONJ
cana-1862	43	19	for	for	ADP
cana-1862	43	20	example	example	NOUN
cana-1862	43	21	certain	certain	ADJ
cana-1862	43	22	safety	safety	NOUN
cana-1862	43	23	hazards	hazard	NOUN
cana-1862	43	24	are	be	AUX
cana-1862	43	25	developing	develop	VERB
cana-1862	43	26	.	.	PUNCT
cana-1862	44	1	the	the	DET
cana-1862	44	2	poster	poster	NOUN
cana-1862	44	3	mentions	mention	VERB
cana-1862	44	4	that	that	SCONJ
cana-1862	44	5	by	by	ADP
cana-1862	44	6	refreshing	refresh	VERB
cana-1862	44	7	the	the	DET
cana-1862	44	8	network	network	NOUN
cana-1862	44	9	with	with	ADP
cana-1862	44	10	new	new	ADJ
cana-1862	44	11	evidence	evidence	NOUN
cana-1862	44	12	(	(	PUNCT
cana-1862	44	13	ex	ex	NOUN
cana-1862	44	14	:	:	PUNCT
cana-1862	44	15	looked	look	VERB
cana-1862	44	16	-	-	PUNCT
cana-1862	44	17	for	for	ADP
cana-1862	44	18	knowledge	knowledge	NOUN
cana-1862	44	19	of	of	ADP
cana-1862	44	20	the	the	DET
cana-1862	44	21	running	run	VERB
cana-1862	44	22	state	state	NOUN
cana-1862	44	23	observation	observation	NOUN
cana-1862	44	24	data	datum	NOUN
cana-1862	44	25	,	,	PUNCT
cana-1862	44	26	gathered	gather	VERB
cana-1862	44	27	through	through	ADP
cana-1862	44	28	network	network	NOUN
cana-1862	44	29	monitoring	monitoring	NOUN
cana-1862	44	30	)	)	PUNCT
cana-1862	44	31	,	,	PUNCT
cana-1862	44	32	bayesian	bayesian	NOUN
cana-1862	44	33	inference	inference	NOUN
cana-1862	44	34	provides	provide	VERB
cana-1862	44	35	an	an	DET
cana-1862	44	36	ability	ability	NOUN
cana-1862	44	37	to	to	PART
cana-1862	44	38	reassign	reassign	VERB
cana-1862	44	39	the	the	DET
cana-1862	44	40	probability	probability	NOUN
cana-1862	44	41	of	of	ADP
cana-1862	44	42	suspected	suspect	VERB
cana-1862	44	43	security	security	NOUN
cana-1862	44	44	events	event	NOUN
cana-1862	44	45	and	and	CCONJ
cana-1862	44	46	helps	help	VERB
cana-1862	44	47	in	in	ADP
cana-1862	44	48	identifying	identify	VERB
cana-1862	44	49	emerging	emerge	VERB
cana-1862	44	50	vulnerabilities	vulnerability	NOUN
cana-1862	44	51	.	.	PUNCT
cana-1862	45	1	the	the	DET
cana-1862	45	2	integration	integration	NOUN
cana-1862	45	3	of	of	ADP
cana-1862	45	4	bns	bns	PROPN
cana-1862	45	5	requires	require	VERB
cana-1862	45	6	application	application	NOUN
cana-1862	45	7	of	of	ADP
cana-1862	45	8	advanced	advanced	ADJ
cana-1862	45	9	probability	probability	NOUN
cana-1862	45	10	theory	theory	NOUN
cana-1862	45	11	and	and	CCONJ
cana-1862	45	12	statistics	statistic	NOUN
cana-1862	45	13	.	.	PUNCT
cana-1862	46	1	for	for	ADP
cana-1862	46	2	example	example	NOUN
cana-1862	46	3	,	,	PUNCT
cana-1862	46	4	the	the	DET
cana-1862	46	5	expectation	expectation	NOUN
cana-1862	46	6	-	-	PUNCT
cana-1862	46	7	maximization	maximization	NOUN
cana-1862	46	8	(	(	PUNCT
cana-1862	46	9	em	em	PRON
cana-1862	46	10	)	)	PUNCT
cana-1862	46	11	algorithm	algorithm	NOUN
cana-1862	46	12	is	be	AUX
cana-1862	46	13	a	a	DET
cana-1862	46	14	common	common	ADJ
cana-1862	46	15	way	way	NOUN
cana-1862	46	16	to	to	PART
cana-1862	46	17	estimate	estimate	VERB
cana-1862	46	18	the	the	DET
cana-1862	46	19	model	model	NOUN
cana-1862	46	20	parameters	parameter	NOUN
cana-1862	46	21	in	in	ADP
cana-1862	46	22	bns	bns	PROPN
cana-1862	46	23	when	when	SCONJ
cana-1862	46	24	data	datum	NOUN
cana-1862	46	25	is	be	AUX
cana-1862	46	26	incomplete	incomplete	ADJ
cana-1862	46	27	as	as	ADV
cana-1862	46	28	well	well	ADV
cana-1862	46	29	.	.	PUNCT
cana-1862	47	1	it	it	PRON
cana-1862	47	2	allows	allow	VERB
cana-1862	47	3	us	we	PRON
cana-1862	47	4	to	to	PART
cana-1862	47	5	really	really	ADV
cana-1862	47	6	leverage	leverage	VERB
cana-1862	47	7	the	the	DET
cana-1862	47	8	power	power	NOUN
cana-1862	47	9	of	of	ADP
cana-1862	47	10	probabilistic	probabilistic	ADJ
cana-1862	47	11	models	model	NOUN
cana-1862	47	12	in	in	ADP
cana-1862	47	13	a	a	DET
cana-1862	47	14	way	way	NOUN
cana-1862	47	15	that	that	PRON
cana-1862	47	16	lets	let	VERB
cana-1862	47	17	us	we	PRON
cana-1862	47	18	quantify	quantify	VERB
cana-1862	47	19	our	our	PRON
cana-1862	47	20	uncertainties	uncertainty	NOUN
cana-1862	47	21	and	and	CCONJ
cana-1862	47	22	make	make	VERB
cana-1862	47	23	decisions	decision	NOUN
cana-1862	47	24	about	about	ADP
cana-1862	47	25	potential	potential	ADJ
cana-1862	47	26	security	security	NOUN
cana-1862	47	27	incidents	incident	NOUN
cana-1862	47	28	.	.	PUNCT
cana-1862	48	1	o	o	X
cana-1862	48	2	decision	decision	NOUN
cana-1862	48	3	trees	tree	NOUN
cana-1862	48	4	&	&	CCONJ
cana-1862	48	5	ensembles	ensemble	NOUN
cana-1862	48	6	this	this	DET
cana-1862	48	7	algorithm	algorithm	NOUN
cana-1862	48	8	is	be	AUX
cana-1862	48	9	very	very	ADV
cana-1862	48	10	intuitive	intuitive	ADJ
cana-1862	48	11	since	since	SCONJ
cana-1862	48	12	it	it	PRON
cana-1862	48	13	classify	classify	VERB
cana-1862	48	14	the	the	DET
cana-1862	48	15	data	datum	NOUN
cana-1862	48	16	by	by	ADP
cana-1862	48	17	recursively	recursively	ADV
cana-1862	48	18	partitioning	partition	VERB
cana-1862	48	19	the	the	DET
cana-1862	48	20	input	input	NOUN
cana-1862	48	21	space	space	NOUN
cana-1862	48	22	with	with	ADP
cana-1862	48	23	respect	respect	NOUN
cana-1862	48	24	to	to	ADP
cana-1862	48	25	feature	feature	VERB
cana-1862	48	26	values[7	values[7	ADJ
cana-1862	48	27	]	]	X
cana-1862	48	28	.	.	PUNCT
cana-1862	49	1	these	these	PRON
cana-1862	49	2	can	can	AUX
cana-1862	49	3	be	be	AUX
cana-1862	49	4	useful	useful	ADJ
cana-1862	49	5	when	when	SCONJ
cana-1862	49	6	the	the	DET
cana-1862	49	7	dataset	dataset	NOUN
cana-1862	49	8	consists	consist	VERB
cana-1862	49	9	of	of	ADP
cana-1862	49	10	some	some	DET
cana-1862	49	11	categorical	categorical	ADJ
cana-1862	49	12	and	and	CCONJ
cana-1862	49	13	other	other	ADJ
cana-1862	49	14	numeric	numeric	ADJ
cana-1862	49	15	features	feature	NOUN
cana-1862	49	16	.	.	PUNCT
cana-1862	50	1	dts	dt	NOUN
cana-1862	50	2	can	can	AUX
cana-1862	50	3	be	be	AUX
cana-1862	50	4	improved	improve	VERB
cana-1862	50	5	by	by	ADP
cana-1862	50	6	detection	detection	NOUN
cana-1862	50	7	system	system	NOUN
cana-1862	50	8	.	.	PUNCT
cana-1862	51	1	random	random	ADJ
cana-1862	51	2	forests	forest	NOUN
cana-1862	51	3	:	:	PUNCT
cana-1862	51	4	random	random	ADJ
cana-1862	51	5	forests	forest	NOUN
cana-1862	51	6	is	be	AUX
cana-1862	51	7	an	an	DET
cana-1862	51	8	ensemble	ensemble	ADJ
cana-1862	51	9	method	method	NOUN
cana-1862	51	10	that	that	PRON
cana-1862	51	11	trains	train	VERB
cana-1862	51	12	several	several	ADJ
cana-1862	51	13	decision	decision	NOUN
cana-1862	51	14	tree	tree	NOUN
cana-1862	51	15	models	model	NOUN
cana-1862	51	16	on	on	ADP
cana-1862	51	17	different	different	ADJ
cana-1862	51	18	subsets	subset	NOUN
cana-1862	51	19	of	of	ADP
cana-1862	51	20	the	the	DET
cana-1862	51	21	data	datum	NOUN
cana-1862	51	22	and	and	CCONJ
cana-1862	51	23	combines	combine	VERB
cana-1862	51	24	their	their	PRON
cana-1862	51	25	predictions	prediction	NOUN
cana-1862	51	26	.	.	PUNCT
cana-1862	52	1	random	random	ADJ
cana-1862	52	2	forests	forest	NOUN
cana-1862	52	3	are	be	AUX
cana-1862	52	4	less	less	ADV
cana-1862	52	5	likely	likely	ADJ
cana-1862	52	6	to	to	PART
cana-1862	52	7	over	over	ADP
cana-1862	52	8	-	-	PUNCT
cana-1862	52	9	fit	fit	NOUN
cana-1862	52	10	due	due	ADP
cana-1862	52	11	to	to	ADP
cana-1862	52	12	the	the	DET
cana-1862	52	13	use	use	NOUN
cana-1862	52	14	of	of	ADP
cana-1862	52	15	randomness	randomness	NOUN
cana-1862	52	16	in	in	ADP
cana-1862	52	17	feature	feature	NOUN
cana-1862	52	18	selection	selection	NOUN
cana-1862	52	19	and	and	CCONJ
cana-1862	52	20	data	datum	NOUN
cana-1862	52	21	sampling	sampling	NOUN
cana-1862	52	22	,	,	PUNCT
cana-1862	52	23	making	make	VERB
cana-1862	52	24	them	they	PRON
cana-1862	52	25	better	well	ADJ
cana-1862	52	26	at	at	ADP
cana-1862	52	27	finding	find	VERB
cana-1862	52	28	intricate	intricate	ADJ
cana-1862	52	29	security	security	NOUN
cana-1862	52	30	patterns	pattern	NOUN
cana-1862	52	31	.	.	PUNCT
cana-1862	53	1	gradient	gradient	ADJ
cana-1862	53	2	boosting	boosting	NOUN
cana-1862	53	3	(	(	PUNCT
cana-1862	53	4	xgboost	xgboost	ADV
cana-1862	53	5	for	for	ADP
cana-1862	53	6	instance	instance	NOUN
cana-1862	53	7	):	):	PUNCT
cana-1862	53	8	this	this	DET
cana-1862	53	9	model	model	NOUN
cana-1862	53	10	sequentially	sequentially	ADV
cana-1862	53	11	trains	train	VERB
cana-1862	53	12	shallow	shallow	ADJ
cana-1862	53	13	trees	tree	NOUN
cana-1862	53	14	as	as	ADP
cana-1862	53	15	weak	weak	ADJ
cana-1862	53	16	learners	learner	NOUN
cana-1862	53	17	and	and	CCONJ
cana-1862	53	18	combine	combine	VERB
cana-1862	53	19	them	they	PRON
cana-1862	53	20	to	to	PART
cana-1862	53	21	have	have	VERB
cana-1862	53	22	a	a	DET
cana-1862	53	23	powerful	powerful	ADJ
cana-1862	53	24	model	model	NOUN
cana-1862	53	25	at	at	ADP
cana-1862	53	26	the	the	DET
cana-1862	53	27	end	end	NOUN
cana-1862	53	28	.	.	PUNCT
cana-1862	54	1	this	this	PRON
cana-1862	54	2	makes	make	VERB
cana-1862	54	3	it	it	PRON
cana-1862	54	4	an	an	DET
cana-1862	54	5	effective	effective	ADJ
cana-1862	54	6	tool	tool	NOUN
cana-1862	54	7	for	for	ADP
cana-1862	54	8	real	real	ADJ
cana-1862	54	9	-	-	PUNCT
cana-1862	54	10	time	time	NOUN
cana-1862	54	11	bug	bug	NOUN
cana-1862	54	12	identification	identification	NOUN
cana-1862	54	13	and	and	CCONJ
cana-1862	54	14	the	the	DET
cana-1862	54	15	use	use	NOUN
cana-1862	54	16	of	of	ADP
cana-1862	54	17	techniques	technique	NOUN
cana-1862	54	18	like	like	ADP
cana-1862	54	19	regularization	regularization	NOUN
cana-1862	54	20	,	,	PUNCT
cana-1862	54	21	available	available	ADJ
cana-1862	54	22	in	in	ADP
cana-1862	54	23	xgboost	xgboost	ADV
cana-1862	54	24	allows	allow	VERB
cana-1862	54	25	improving	improve	VERB
cana-1862	54	26	generalization[8	generalization[8	NOUN
cana-1862	54	27	]	]	PUNCT
cana-1862	54	28	.	.	PUNCT
cana-1862	55	1	the	the	DET
cana-1862	55	2	mathematical	mathematical	ADJ
cana-1862	55	3	basis	basis	NOUN
cana-1862	55	4	for	for	ADP
cana-1862	55	5	these	these	DET
cana-1862	55	6	models	model	NOUN
cana-1862	55	7	is	be	AUX
cana-1862	55	8	a	a	DET
cana-1862	55	9	mix	mix	NOUN
cana-1862	55	10	of	of	ADP
cana-1862	55	11	tree	tree	NOUN
cana-1862	55	12	construction	construction	NOUN
cana-1862	55	13	based	base	VERB
cana-1862	55	14	on	on	ADP
cana-1862	55	15	information	information	NOUN
cana-1862	55	16	theory	theory	NOUN
cana-1862	55	17	(	(	PUNCT
cana-1862	55	18	eg	eg	NOUN
cana-1862	55	19	entropy	entropy	PROPN
cana-1862	55	20	and	and	CCONJ
cana-1862	55	21	information	information	NOUN
cana-1862	55	22	gain	gain	NOUN
cana-1862	55	23	)	)	PUNCT
cana-1862	55	24	and	and	CCONJ
cana-1862	55	25	optimization	optimization	NOUN
cana-1862	55	26	to	to	PART
cana-1862	55	27	incrementally	incrementally	ADV
cana-1862	55	28	tune	tune	VERB
cana-1862	55	29	the	the	DET
cana-1862	55	30	model	model	NOUN
cana-1862	55	31	accuracy	accuracy	NOUN
cana-1862	55	32	.	.	PUNCT
cana-1862	56	1	communications	communication	NOUN
cana-1862	56	2	on	on	ADP
cana-1862	56	3	applied	apply	VERB
cana-1862	56	4	nonlinear	nonlinear	ADJ
cana-1862	56	5	analysis	analysis	NOUN
cana-1862	56	6	issn	issn	NOUN
cana-1862	56	7	:	:	PUNCT
cana-1862	56	8	1074	1074	NUM
cana-1862	56	9	-	-	PUNCT
cana-1862	56	10	133x	133x	NUM
cana-1862	56	11	vol	vol	NOUN
cana-1862	56	12	32	32	NUM
cana-1862	56	13	no	no	NOUN
cana-1862	56	14	.	.	NOUN
cana-1862	56	15	2	2	NUM
cana-1862	56	16	(	(	PUNCT
cana-1862	56	17	2025	2025	NUM
cana-1862	56	18	)	)	PUNCT
cana-1862	56	19	695	695	NUM
cana-1862	56	20	https://internationalpubls.com	https://internationalpubls.com	X
cana-1862	56	21	auto	auto	NOUN
cana-1862	56	22	-	-	PUNCT
cana-1862	56	23	encoders	encoder	NOUN
cana-1862	56	24	(	(	PUNCT
cana-1862	56	25	anomaly	anomaly	NOUN
cana-1862	56	26	detection	detection	NOUN
cana-1862	56	27	):	):	PUNCT
cana-1862	56	28	auto	auto	NOUN
cana-1862	56	29	-	-	PUNCT
cana-1862	56	30	encoders	encoder	NOUN
cana-1862	56	31	are	be	AUX
cana-1862	56	32	a	a	DET
cana-1862	56	33	class	class	NOUN
cana-1862	56	34	of	of	ADP
cana-1862	56	35	neural	neural	ADJ
cana-1862	56	36	networks	network	NOUN
cana-1862	56	37	designed	design	VERB
cana-1862	56	38	for	for	ADP
cana-1862	56	39	unsupervised	unsupervised	ADJ
cana-1862	56	40	learning	learning	NOUN
cana-1862	56	41	tasks	task	NOUN
cana-1862	56	42	such	such	ADJ
cana-1862	56	43	as	as	ADP
cana-1862	56	44	anomaly	anomaly	NOUN
cana-1862	56	45	detection	detection	NOUN
cana-1862	56	46	.	.	PUNCT
cana-1862	57	1	they	they	PRON
cana-1862	57	2	are	be	AUX
cana-1862	57	3	trained	train	VERB
cana-1862	57	4	on	on	ADP
cana-1862	57	5	a	a	DET
cana-1862	57	6	compressed	compress	VERB
cana-1862	57	7	representation	representation	NOUN
cana-1862	57	8	of	of	ADP
cana-1862	57	9	the	the	DET
cana-1862	57	10	input	input	NOUN
cana-1862	57	11	data	datum	NOUN
cana-1862	57	12	(	(	PUNCT
cana-1862	57	13	encoding	encoding	NOUN
cana-1862	57	14	)	)	PUNCT
cana-1862	57	15	and	and	CCONJ
cana-1862	57	16	an	an	DET
cana-1862	57	17	attempt	attempt	NOUN
cana-1862	57	18	is	be	AUX
cana-1862	57	19	made	make	VERB
cana-1862	57	20	to	to	PART
cana-1862	57	21	reconstruct	reconstruct	VERB
cana-1862	57	22	the	the	DET
cana-1862	57	23	data	datum	NOUN
cana-1862	57	24	from	from	ADP
cana-1862	57	25	this	this	DET
cana-1862	57	26	encoding	encoding	NOUN
cana-1862	57	27	(	(	PUNCT
cana-1862	57	28	decoding	decoding	NOUN
cana-1862	57	29	)	)	PUNCT
cana-1862	57	30	.	.	PUNCT
cana-1862	58	1	this	this	PRON
cana-1862	58	2	is	be	AUX
cana-1862	58	3	used	use	VERB
cana-1862	58	4	as	as	ADP
cana-1862	58	5	a	a	DET
cana-1862	58	6	gauge	gauge	NOUN
cana-1862	58	7	to	to	PART
cana-1862	58	8	check	check	VERB
cana-1862	58	9	the	the	DET
cana-1862	58	10	anomalies	anomaly	NOUN
cana-1862	58	11	in	in	ADP
cana-1862	58	12	memory	memory	NOUN
cana-1862	58	13	,	,	PUNCT
cana-1862	58	14	which	which	PRON
cana-1862	58	15	indicate	indicate	VERB
cana-1862	58	16	the	the	DET
cana-1862	58	17	difference	difference	NOUN
cana-1862	58	18	between	between	ADP
cana-1862	58	19	the	the	DET
cana-1862	58	20	original	original	ADJ
cana-1862	58	21	data	datum	NOUN
cana-1862	58	22	and	and	CCONJ
cana-1862	58	23	its	its	PRON
cana-1862	58	24	reconstruction	reconstruction	NOUN
cana-1862	58	25	.	.	PUNCT
cana-1862	59	1	autoencoders	autoencoder	NOUN
cana-1862	59	2	are	be	AUX
cana-1862	59	3	trained	train	VERB
cana-1862	59	4	on	on	ADP
cana-1862	59	5	ordinary	ordinary	ADJ
cana-1862	59	6	network	network	NOUN
cana-1862	59	7	traffic	traffic	NOUN
cana-1862	59	8	in	in	ADP
cana-1862	59	9	the	the	DET
cana-1862	59	10	context	context	NOUN
cana-1862	59	11	of	of	ADP
cana-1862	59	12	vulnerability	vulnerability	NOUN
cana-1862	59	13	detection[9	detection[9	PROPN
cana-1862	59	14	]	]	PUNCT
cana-1862	59	15	.	.	PUNCT
cana-1862	60	1	in	in	ADP
cana-1862	60	2	other	other	ADJ
cana-1862	60	3	words	word	NOUN
cana-1862	60	4	,	,	PUNCT
cana-1862	60	5	when	when	SCONJ
cana-1862	60	6	any	any	DET
cana-1862	60	7	unusual	unusual	ADJ
cana-1862	60	8	or	or	CCONJ
cana-1862	60	9	anomaly	anomaly	NOUN
cana-1862	60	10	traffic	traffic	NOUN
cana-1862	60	11	patterns	pattern	NOUN
cana-1862	60	12	(	(	PUNCT
cana-1862	60	13	for	for	ADP
cana-1862	60	14	security	security	NOUN
cana-1862	60	15	breaches	breach	NOUN
cana-1862	60	16	)	)	PUNCT
cana-1862	60	17	are	be	AUX
cana-1862	60	18	introduced	introduce	VERB
cana-1862	60	19	in	in	ADP
cana-1862	60	20	the	the	DET
cana-1862	60	21	model	model	NOUN
cana-1862	60	22	,	,	PUNCT
cana-1862	60	23	it	it	PRON
cana-1862	60	24	then	then	ADV
cana-1862	60	25	experiences	experience	VERB
cana-1862	60	26	a	a	DET
cana-1862	60	27	spike	spike	NOUN
cana-1862	60	28	in	in	ADP
cana-1862	60	29	reconstruction	reconstruction	NOUN
cana-1862	60	30	error	error	NOUN
cana-1862	60	31	i.e.	i.e.	X
cana-1862	60	32	,	,	PUNCT
cana-1862	60	33	outliers	outlier	NOUN
cana-1862	60	34	which	which	PRON
cana-1862	60	35	could	could	AUX
cana-1862	60	36	act	act	VERB
cana-1862	60	37	as	as	ADP
cana-1862	60	38	potential	potential	ADJ
cana-1862	60	39	threats	threat	NOUN
cana-1862	60	40	and	and	CCONJ
cana-1862	60	41	can	can	AUX
cana-1862	60	42	be	be	AUX
cana-1862	60	43	recognised	recognise	VERB
cana-1862	60	44	.	.	PUNCT
cana-1862	61	1	probabilistic	probabilistic	ADJ
cana-1862	61	2	variational	variational	ADJ
cana-1862	61	3	auto	auto	NOUN
cana-1862	61	4	-	-	PUNCT
cana-1862	61	5	encoders	encoder	NOUN
cana-1862	61	6	(	(	PUNCT
cana-1862	61	7	vaes	vaes	ADV
cana-1862	61	8	):	):	PUNCT
cana-1862	61	9	vaes	vaes	NOUN
cana-1862	61	10	are	be	AUX
cana-1862	61	11	an	an	DET
cana-1862	61	12	extension	extension	NOUN
cana-1862	61	13	of	of	ADP
cana-1862	61	14	traditional	traditional	ADJ
cana-1862	61	15	auto	auto	NOUN
cana-1862	61	16	-	-	PUNCT
cana-1862	61	17	encoders	encoder	NOUN
cana-1862	61	18	which	which	PRON
cana-1862	61	19	employ	employ	VERB
cana-1862	61	20	a	a	DET
cana-1862	61	21	form	form	NOUN
cana-1862	61	22	of	of	ADP
cana-1862	61	23	probabilistic	probabilistic	ADJ
cana-1862	61	24	inference	inference	NOUN
cana-1862	61	25	in	in	ADP
cana-1862	61	26	the	the	DET
cana-1862	61	27	encoding	encoding	NOUN
cana-1862	61	28	process[10	process[10	NOUN
cana-1862	61	29	]	]	PUNCT
cana-1862	61	30	.	.	PUNCT
cana-1862	62	1	specifically	specifically	ADV
cana-1862	62	2	,	,	PUNCT
cana-1862	62	3	sparsely	sparsely	ADV
cana-1862	62	4	gated	gate	VERB
cana-1862	62	5	autoencoders	autoencoder	NOUN
cana-1862	62	6	are	be	AUX
cana-1862	62	7	the	the	DET
cana-1862	62	8	normal	normal	ADJ
cana-1862	62	9	auto	auto	NOUN
cana-1862	62	10	-	-	PUNCT
cana-1862	62	11	encoders	encoder	NOUN
cana-1862	62	12	with	with	ADP
cana-1862	62	13	a	a	DET
cana-1862	62	14	learned	learn	VERB
cana-1862	62	15	scaling	scaling	NOUN
cana-1862	62	16	factor	factor	NOUN
cana-1862	62	17	for	for	ADP
cana-1862	62	18	all	all	PRON
cana-1862	62	19	of	of	ADP
cana-1862	62	20	the	the	DET
cana-1862	62	21	activation	activation	NOUN
cana-1862	62	22	units	unit	NOUN
cana-1862	62	23	that	that	PRON
cana-1862	62	24	introduces	introduce	VERB
cana-1862	62	25	more	more	ADJ
cana-1862	62	26	stocjhas	stocjha	NOUN
cana-1862	62	27	has	have	AUX
cana-1862	62	28	ticity	ticity	NOUN
cana-1862	62	29	to	to	ADP
cana-1862	62	30	their	their	PRON
cana-1862	62	31	output	output	NOUN
cana-1862	62	32	activations	activation	NOUN
cana-1862	62	33	and	and	CCONJ
cana-1862	62	34	enables	enable	VERB
cana-1862	62	35	them	they	PRON
cana-1862	62	36	provide	provide	VERB
cana-1862	62	37	not	not	PART
cana-1862	62	38	just	just	ADV
cana-1862	62	39	1	1	NUM
cana-1862	62	40	literal	literal	ADJ
cana-1862	62	41	encoding	encoding	NOUN
cana-1862	62	42	for	for	ADP
cana-1862	62	43	each	each	DET
cana-1862	62	44	input	input	NOUN
cana-1862	62	45	but	but	CCONJ
cana-1862	62	46	also	also	ADV
cana-1862	62	47	learn	learn	VERB
cana-1862	62	48	a	a	DET
cana-1862	62	49	distribution	distribution	NOUN
cana-1862	62	50	over	over	ADP
cana-1862	62	51	possible	possible	ADJ
cana-1862	62	52	encodings	encoding	NOUN
cana-1862	62	53	,	,	PUNCT
cana-1862	62	54	resulting	result	VERB
cana-1862	62	55	in	in	ADP
cana-1862	62	56	greater	great	ADJ
cana-1862	62	57	robustness	robustness	NOUN
cana-1862	62	58	for	for	ADP
cana-1862	62	59	detecting	detect	VERB
cana-1862	62	60	anomalies	anomaly	NOUN
cana-1862	62	61	in	in	ADP
cana-1862	62	62	scenarios	scenario	NOUN
cana-1862	62	63	where	where	SCONJ
cana-1862	62	64	variations	variation	NOUN
cana-1862	62	65	of	of	ADP
cana-1862	62	66	data	datum	NOUN
cana-1862	62	67	is	be	AUX
cana-1862	62	68	inherently	inherently	ADV
cana-1862	62	69	stochastic	stochastic	ADJ
cana-1862	62	70	.	.	PUNCT
cana-1862	63	1	gaussian	gaussian	ADJ
cana-1862	63	2	mixture	mixture	NOUN
cana-1862	63	3	models	model	NOUN
cana-1862	63	4	(	(	PUNCT
cana-1862	63	5	gmm	gmm	NOUN
cana-1862	63	6	)	)	PUNCT
cana-1862	63	7	for	for	ADP
cana-1862	63	8	unsupervised	unsupervised	ADJ
cana-1862	63	9	clustering	clustering	NOUN
cana-1862	63	10	:	:	PUNCT
cana-1862	63	11	gmms	gmms	NOUN
cana-1862	63	12	are	be	AUX
cana-1862	63	13	the	the	DET
cana-1862	63	14	generatively	generatively	NOUN
cana-1862	63	15	with	with	ADP
cana-1862	63	16	unknown	unknown	ADJ
cana-1862	63	17	parameters	parameter	NOUN
cana-1862	63	18	.	.	PUNCT
cana-1862	64	1	for	for	ADP
cana-1862	64	2	example	example	NOUN
cana-1862	64	3	,	,	PUNCT
cana-1862	64	4	in	in	ADP
cana-1862	64	5	cybersecurity	cybersecurity	NOUN
cana-1862	64	6	,	,	PUNCT
cana-1862	64	7	gmms	gmms	NOUN
cana-1862	64	8	can	can	AUX
cana-1862	64	9	be	be	AUX
cana-1862	64	10	used	use	VERB
cana-1862	64	11	to	to	PART
cana-1862	64	12	cluster	cluster	NOUN
cana-1862	64	13	network	network	NOUN
cana-1862	64	14	traffic	traffic	NOUN
cana-1862	64	15	behaviors	behavior	NOUN
cana-1862	64	16	into	into	ADP
cana-1862	64	17	categories	category	NOUN
cana-1862	64	18	like	like	ADP
cana-1862	64	19	normal	normal	ADJ
cana-1862	64	20	and	and	CCONJ
cana-1862	64	21	suspicious	suspicious	ADJ
cana-1862	64	22	to	to	PART
cana-1862	64	23	find	find	VERB
cana-1862	64	24	activities	activity	NOUN
cana-1862	64	25	that	that	PRON
cana-1862	64	26	reveal	reveal	VERB
cana-1862	64	27	security	security	NOUN
cana-1862	64	28	breaches[11	breaches[11	PROPN
cana-1862	64	29	]	]	PUNCT
cana-1862	64	30	.	.	PUNCT
cana-1862	65	1	the	the	DET
cana-1862	65	2	em	em	PROPN
cana-1862	65	3	algorithm	algorithm	NOUN
cana-1862	65	4	:	:	PUNCT
cana-1862	65	5	to	to	PART
cana-1862	65	6	estimate	estimate	VERB
cana-1862	65	7	the	the	DET
cana-1862	65	8	parameters	parameter	NOUN
cana-1862	65	9	of	of	ADP
cana-1862	65	10	the	the	DET
cana-1862	65	11	gaussian	gaussian	ADJ
cana-1862	65	12	distributions	distribution	NOUN
cana-1862	65	13	,	,	PUNCT
cana-1862	65	14	allowing	allow	VERB
cana-1862	65	15	the	the	DET
cana-1862	65	16	model	model	NOUN
cana-1862	65	17	to	to	PART
cana-1862	65	18	iteratively	iteratively	ADV
cana-1862	65	19	adjust	adjust	VERB
cana-1862	65	20	these	these	DET
cana-1862	65	21	estimates	estimate	NOUN
cana-1862	65	22	while	while	SCONJ
cana-1862	65	23	refining	refine	VERB
cana-1862	65	24	its	its	PRON
cana-1862	65	25	clustering	clustering	NOUN
cana-1862	65	26	through	through	ADP
cana-1862	65	27	successive	successive	ADJ
cana-1862	65	28	iterations	iteration	NOUN
cana-1862	65	29	.	.	PUNCT
cana-1862	66	1	this	this	DET
cana-1862	66	2	unsupervised	unsupervised	ADJ
cana-1862	66	3	method	method	NOUN
cana-1862	66	4	is	be	AUX
cana-1862	66	5	especially	especially	ADV
cana-1862	66	6	helpful	helpful	ADJ
cana-1862	66	7	for	for	ADP
cana-1862	66	8	detecting	detect	VERB
cana-1862	66	9	zero	zero	NUM
cana-1862	66	10	-	-	PUNCT
cana-1862	66	11	day	day	NOUN
cana-1862	66	12	opportunities	opportunity	NOUN
cana-1862	66	13	where	where	SCONJ
cana-1862	66	14	labelled	label	VERB
cana-1862	66	15	data	datum	NOUN
cana-1862	66	16	often	often	ADV
cana-1862	66	17	does	do	AUX
cana-1862	66	18	not	not	PART
cana-1862	66	19	exist	exist	VERB
cana-1862	66	20	.	.	PUNCT
cana-1862	67	1	isolation	isolation	NOUN
cana-1862	67	2	forests	forest	NOUN
cana-1862	67	3	for	for	ADP
cana-1862	67	4	anomaly	anomaly	NOUN
cana-1862	67	5	detection	detection	NOUN
cana-1862	67	6	:	:	PUNCT
cana-1862	67	7	isolation	isolation	NOUN
cana-1862	67	8	forests	forest	NOUN
cana-1862	67	9	(	(	PUNCT
cana-1862	67	10	ifs	ifs	PROPN
cana-1862	67	11	)	)	PUNCT
cana-1862	67	12	are	be	AUX
cana-1862	67	13	unsupervised	unsupervised	ADJ
cana-1862	67	14	anomaly	anomaly	NOUN
cana-1862	67	15	detection	detection	NOUN
cana-1862	67	16	method	method	NOUN
cana-1862	67	17	which	which	PRON
cana-1862	67	18	isolates	isolate	VERB
cana-1862	67	19	instances	instance	NOUN
cana-1862	67	20	in	in	ADP
cana-1862	67	21	a	a	DET
cana-1862	67	22	dataset	dataset	NOUN
cana-1862	67	23	.	.	PUNCT
cana-1862	68	1	the	the	DET
cana-1862	68	2	main	main	ADJ
cana-1862	68	3	insight	insight	NOUN
cana-1862	68	4	is	be	AUX
cana-1862	68	5	that	that	SCONJ
cana-1862	68	6	anomalies	anomaly	NOUN
cana-1862	68	7	are	be	AUX
cana-1862	68	8	points	point	NOUN
cana-1862	68	9	that	that	PRON
cana-1862	68	10	are	be	AUX
cana-1862	68	11	more	more	ADV
cana-1862	68	12	easily	easily	ADV
cana-1862	68	13	modulated	modulate	VERB
cana-1862	68	14	than	than	ADP
cana-1862	68	15	normal	normal	ADJ
cana-1862	68	16	points	point	NOUN
cana-1862	68	17	.	.	PUNCT
cana-1862	69	1	in	in	ADP
cana-1862	69	2	this	this	DET
cana-1862	69	3	model	model	NOUN
cana-1862	69	4	,	,	PUNCT
cana-1862	69	5	the	the	DET
cana-1862	69	6	random	random	ADJ
cana-1862	69	7	decisions	decision	NOUN
cana-1862	69	8	are	be	AUX
cana-1862	69	9	decision	decision	NOUN
cana-1862	69	10	trees	tree	NOUN
cana-1862	69	11	and	and	CCONJ
cana-1862	69	12	how	how	SCONJ
cana-1862	69	13	many	many	ADJ
cana-1862	69	14	turns	turn	NOUN
cana-1862	69	15	have	have	VERB
cana-1862	69	16	to	to	PART
cana-1862	69	17	be	be	AUX
cana-1862	69	18	made	make	VERB
cana-1862	69	19	till	till	SCONJ
cana-1862	69	20	we	we	PRON
cana-1862	69	21	isolate	isolate	VERB
cana-1862	69	22	a	a	DET
cana-1862	69	23	data	data	NOUN
cana-1862	69	24	point	point	NOUN
cana-1862	69	25	is	be	AUX
cana-1862	69	26	its	its	PRON
cana-1862	69	27	anomaly	anomaly	NOUN
cana-1862	69	28	score	score	NOUN
cana-1862	69	29	.	.	PUNCT
cana-1862	70	1	the	the	DET
cana-1862	70	2	insertion	insertion	NOUN
cana-1862	70	3	of	of	ADP
cana-1862	70	4	randomness	randomness	NOUN
cana-1862	70	5	in	in	ADP
cana-1862	70	6	the	the	DET
cana-1862	70	7	partitioning	partition	VERB
cana-1862	70	8	process	process	NOUN
cana-1862	70	9	permits	permit	VERB
cana-1862	70	10	approximating	approximate	VERB
cana-1862	70	11	complex	complex	ADJ
cana-1862	70	12	relationships	relationship	NOUN
cana-1862	70	13	between	between	ADP
cana-1862	70	14	data	datum	NOUN
cana-1862	70	15	points	point	NOUN
cana-1862	70	16	to	to	PART
cana-1862	70	17	be	be	AUX
cana-1862	70	18	linearized	linearize	VERB
cana-1862	70	19	and	and	CCONJ
cana-1862	70	20	subsequently	subsequently	ADV
cana-1862	70	21	captured	capture	VERB
cana-1862	70	22	by	by	ADP
cana-1862	70	23	simple	simple	ADJ
cana-1862	70	24	tree	tree	NOUN
cana-1862	70	25	based	base	VERB
cana-1862	70	26	data	datum	NOUN
cana-1862	70	27	structure	structure	NOUN
cana-1862	70	28	such	such	ADJ
cana-1862	70	29	as	as	ADP
cana-1862	70	30	binary	binary	ADJ
cana-1862	70	31	tree	tree	NOUN
cana-1862	70	32	(	(	PUNCT
cana-1862	70	33	bst).when	bst).when	PROPN
cana-1862	70	34	a	a	DET
cana-1862	70	35	sample	sample	NOUN
cana-1862	70	36	is	be	AUX
cana-1862	70	37	isolated	isolate	VERB
cana-1862	70	38	,	,	PUNCT
cana-1862	70	39	it	it	PRON
cana-1862	70	40	implies	imply	VERB
cana-1862	70	41	that	that	SCONJ
cana-1862	70	42	at	at	ADV
cana-1862	70	43	least	least	ADJ
cana-1862	70	44	1	1	NUM
cana-1862	70	45	feature	feature	NOUN
cana-1862	70	46	value	value	NOUN
cana-1862	70	47	of	of	ADP
cana-1862	70	48	this	this	DET
cana-1862	70	49	record	record	NOUN
cana-1862	70	50	is	be	AUX
cana-1862	70	51	surprisingly	surprisingly	ADV
cana-1862	70	52	off	off	ADP
cana-1862	70	53	compared	compare	VERB
cana-1862	70	54	to	to	ADP
cana-1862	70	55	other	other	ADJ
cana-1862	70	56	records	record	NOUN
cana-1862	70	57	.	.	PUNCT
cana-1862	71	1	this	this	PRON
cana-1862	71	2	allows	allow	VERB
cana-1862	71	3	them	they	PRON
cana-1862	71	4	to	to	PART
cana-1862	71	5	be	be	AUX
cana-1862	71	6	computationally	computationally	ADV
cana-1862	71	7	fast	fast	ADJ
cana-1862	71	8	,	,	PUNCT
cana-1862	71	9	making	make	VERB
cana-1862	71	10	them	they	PRON
cana-1862	71	11	suitable	suitable	ADJ
cana-1862	71	12	for	for	ADP
cana-1862	71	13	high	high	ADJ
cana-1862	71	14	-	-	PUNCT
cana-1862	71	15	speed	speed	NOUN
cana-1862	71	16	security	security	NOUN
cana-1862	71	17	data	datum	NOUN
cana-1862	71	18	,	,	PUNCT
cana-1862	71	19	in	in	ADP
cana-1862	71	20	which	which	PRON
cana-1862	71	21	the	the	DET
cana-1862	71	22	quick	quick	ADJ
cana-1862	71	23	identification	identification	NOUN
cana-1862	71	24	of	of	ADP
cana-1862	71	25	anomalous	anomalous	ADJ
cana-1862	71	26	patterns	pattern	NOUN
cana-1862	71	27	are	be	AUX
cana-1862	71	28	essential[12	essential[12	NOUN
cana-1862	71	29	]	]	X
cana-1862	71	30	.	.	PUNCT
cana-1862	72	1	reinforcement	reinforcement	NOUN
cana-1862	72	2	learning	learning	NOUN
cana-1862	72	3	for	for	ADP
cana-1862	72	4	dynamic	dynamic	ADJ
cana-1862	72	5	security	security	NOUN
cana-1862	72	6	monitoring	monitoring	NOUN
cana-1862	72	7	:	:	PUNCT
cana-1862	72	8	in	in	ADP
cana-1862	72	9	cybersecurity	cybersecurity	NOUN
cana-1862	72	10	,	,	PUNCT
cana-1862	72	11	rl	rl	PRON
cana-1862	72	12	might	might	AUX
cana-1862	72	13	find	find	VERB
cana-1862	72	14	application	application	NOUN
cana-1862	72	15	in	in	ADP
cana-1862	72	16	,	,	PUNCT
cana-1862	72	17	e.g.	e.g.	ADV
cana-1862	72	18	,	,	PUNCT
cana-1862	72	19	dynamic	dynamic	ADJ
cana-1862	72	20	vulnerability	vulnerability	NOUN
cana-1862	72	21	management	management	NOUN
cana-1862	72	22	keeps	keep	VERB
cana-1862	72	23	changing	change	VERB
cana-1862	72	24	the	the	DET
cana-1862	72	25	strategy	strategy	NOUN
cana-1862	72	26	along	along	ADP
cana-1862	72	27	with	with	ADP
cana-1862	72	28	network	network	NOUN
cana-1862	72	29	adaptation	adaptation	NOUN
cana-1862	72	30	and	and	CCONJ
cana-1862	72	31	all	all	DET
cana-1862	72	32	new	new	ADJ
cana-1862	72	33	threats	threat	NOUN
cana-1862	72	34	.	.	PUNCT
cana-1862	73	1	q	q	X
cana-1862	73	2	-	-	PUNCT
cana-1862	73	3	learning	learning	NOUN
cana-1862	73	4	:	:	PUNCT
cana-1862	73	5	it	it	PRON
cana-1862	73	6	is	be	AUX
cana-1862	73	7	a	a	DET
cana-1862	73	8	simple	simple	ADJ
cana-1862	73	9	and	and	CCONJ
cana-1862	73	10	powerful	powerful	ADJ
cana-1862	73	11	rl	rl	NOUN
cana-1862	73	12	technique	technique	NOUN
cana-1862	73	13	,	,	PUNCT
cana-1862	73	14	with	with	ADP
cana-1862	73	15	q	q	NOUN
cana-1862	73	16	-	-	PUNCT
cana-1862	73	17	learning	learn	VERB
cana-1862	73	18	the	the	DET
cana-1862	73	19	agent	agent	NOUN
cana-1862	73	20	learns	learn	VERB
cana-1862	73	21	the	the	DET
cana-1862	73	22	best	good	ADJ
cana-1862	73	23	action	action	NOUN
cana-1862	73	24	to	to	PART
cana-1862	73	25	take	take	VERB
cana-1862	73	26	due	due	ADJ
cana-1862	73	27	to	to	ADP
cana-1862	73	28	state	state	NOUN
cana-1862	73	29	-	-	PUNCT
cana-1862	73	30	action	action	NOUN
cana-1862	73	31	combinations	combination	NOUN
cana-1862	73	32	and	and	CCONJ
cana-1862	73	33	rewards	reward	NOUN
cana-1862	73	34	are	be	AUX
cana-1862	73	35	recorded	record	VERB
cana-1862	73	36	for	for	ADP
cana-1862	73	37	actions	action	NOUN
cana-1862	73	38	taken	take	VERB
cana-1862	73	39	at	at	ADP
cana-1862	73	40	each	each	DET
cana-1862	73	41	state	state	NOUN
cana-1862	73	42	using	use	VERB
cana-1862	73	43	which	which	PRON
cana-1862	73	44	an	an	DET
cana-1862	73	45	agent	agent	NOUN
cana-1862	73	46	try	try	VERB
cana-1862	73	47	to	to	PART
cana-1862	73	48	maximize	maximize	VERB
cana-1862	73	49	reward	reward	NOUN
cana-1862	73	50	over	over	ADP
cana-1862	73	51	time[13	time[13	NOUN
cana-1862	73	52	]	]	PUNCT
cana-1862	73	53	.	.	PUNCT
cana-1862	74	1	in	in	ADP
cana-1862	74	2	the	the	DET
cana-1862	74	3	realm	realm	NOUN
cana-1862	74	4	of	of	ADP
cana-1862	74	5	network	network	NOUN
cana-1862	74	6	security	security	NOUN
cana-1862	74	7	,	,	PUNCT
cana-1862	74	8	an	an	DET
cana-1862	74	9	rl	rl	NOUN
cana-1862	74	10	agent	agent	NOUN
cana-1862	74	11	can	can	AUX
cana-1862	74	12	learn	learn	VERB
cana-1862	74	13	to	to	PART
cana-1862	74	14	react	react	VERB
cana-1862	74	15	to	to	ADP
cana-1862	74	16	security	security	NOUN
cana-1862	74	17	-	-	PUNCT
cana-1862	74	18	related	relate	VERB
cana-1862	74	19	events	event	NOUN
cana-1862	74	20	(	(	PUNCT
cana-1862	74	21	e.g.	e.g.	ADV
cana-1862	74	22	,	,	PUNCT
cana-1862	74	23	intrusion	intrusion	NOUN
cana-1862	74	24	attempts	attempt	NOUN
cana-1862	74	25	)	)	PUNCT
cana-1862	74	26	,	,	PUNCT
cana-1862	74	27	updating	update	VERB
cana-1862	74	28	its	its	PRON
cana-1862	74	29	policy	policy	NOUN
cana-1862	74	30	on	on	ADP
cana-1862	74	31	-	-	PUNCT
cana-1862	74	32	the	the	DET
cana-1862	74	33	-	-	PUNCT
cana-1862	74	34	fly	fly	NOUN
cana-1862	74	35	by	by	ADP
cana-1862	74	36	incorporating	incorporate	VERB
cana-1862	74	37	observed	observed	ADJ
cana-1862	74	38	outcomes	outcome	NOUN
cana-1862	74	39	and	and	CCONJ
cana-1862	74	40	therefore	therefore	ADV
cana-1862	74	41	improving	improve	VERB
cana-1862	74	42	real	real	ADJ
cana-1862	74	43	-	-	PUNCT
cana-1862	74	44	time	time	NOUN
cana-1862	74	45	defences	defence	NOUN
cana-1862	74	46	.	.	PUNCT
cana-1862	75	1	communications	communication	NOUN
cana-1862	75	2	on	on	ADP
cana-1862	75	3	applied	apply	VERB
cana-1862	75	4	nonlinear	nonlinear	ADJ
cana-1862	75	5	analysis	analysis	NOUN
cana-1862	75	6	issn	issn	NOUN
cana-1862	75	7	:	:	PUNCT
cana-1862	75	8	1074	1074	NUM
cana-1862	75	9	-	-	PUNCT
cana-1862	75	10	133x	133x	NUM
cana-1862	75	11	vol	vol	NOUN
cana-1862	75	12	32	32	NUM
cana-1862	75	13	no	no	NOUN
cana-1862	75	14	.	.	NOUN
cana-1862	75	15	2	2	NUM
cana-1862	75	16	(	(	PUNCT
cana-1862	75	17	2025	2025	NUM
cana-1862	75	18	)	)	PUNCT
cana-1862	76	1	696	696	NUM
cana-1862	76	2	https://internationalpubls.com	https://internationalpubls.com	X
cana-1862	76	3	a	a	DET
cana-1862	76	4	mathematically	mathematically	ADV
cana-1862	76	5	sound	sound	ADJ
cana-1862	76	6	framework	framework	NOUN
cana-1862	76	7	:	:	PUNCT
cana-1862	76	8	despite	despite	SCONJ
cana-1862	76	9	the	the	DET
cana-1862	76	10	underlying	underlie	VERB
cana-1862	76	11	complexities	complexity	NOUN
cana-1862	76	12	of	of	ADP
cana-1862	76	13	security	security	NOUN
cana-1862	76	14	,	,	PUNCT
cana-1862	76	15	reinforcement	reinforcement	NOUN
cana-1862	76	16	learning	learning	NOUN
cana-1862	76	17	models	model	NOUN
cana-1862	76	18	most	most	ADJ
cana-1862	76	19	of	of	ADP
cana-1862	76	20	its	its	PRON
cana-1862	76	21	tasks	task	NOUN
cana-1862	76	22	using	use	VERB
cana-1862	76	23	markov	markov	NOUN
cana-1862	76	24	decision	decision	NOUN
cana-1862	76	25	processes	process	NOUN
cana-1862	76	26	(	(	PUNCT
cana-1862	76	27	mdps	mdps	NOUN
cana-1862	76	28	)	)	PUNCT
cana-1862	76	29	and	and	CCONJ
cana-1862	76	30	dynamic	dynamic	ADJ
cana-1862	76	31	programming	programming	NOUN
cana-1862	76	32	for	for	ADP
cana-1862	76	33	policy	policy	NOUN
cana-1862	76	34	optimization	optimization	NOUN
cana-1862	76	35	;	;	PUNCT
cana-1862	76	36	thus	thus	ADV
cana-1862	76	37	enabling	enable	VERB
cana-1862	76	38	it	it	PRON
cana-1862	76	39	to	to	PART
cana-1862	76	40	effectively	effectively	ADV
cana-1862	76	41	be	be	AUX
cana-1862	76	42	applied	apply	VERB
cana-1862	76	43	as	as	ADP
cana-1862	76	44	a	a	DET
cana-1862	76	45	part	part	NOUN
cana-1862	76	46	of	of	ADP
cana-1862	76	47	complex	complex	ADJ
cana-1862	76	48	controlled	control	VERB
cana-1862	76	49	decision	decision	NOUN
cana-1862	76	50	making	make	VERB
cana-1862	76	51	algorithms	algorithm	NOUN
cana-1862	76	52	for	for	ADP
cana-1862	76	53	security	security	NOUN
cana-1862	76	54	dependent	dependent	ADJ
cana-1862	76	55	domains	domain	NOUN
cana-1862	76	56	.	.	PUNCT
cana-1862	77	1	●	●	PUNCT
cana-1862	77	2	combining	combine	VERB
cana-1862	77	3	mathematical	mathematical	ADJ
cana-1862	77	4	methods	method	NOUN
cana-1862	77	5	with	with	ADP
cana-1862	77	6	machine	machine	NOUN
cana-1862	77	7	learning	learn	VERB
cana-1862	77	8	mathematical	mathematical	ADJ
cana-1862	77	9	techniques	technique	NOUN
cana-1862	77	10	are	be	AUX
cana-1862	77	11	often	often	ADV
cana-1862	77	12	an	an	DET
cana-1862	77	13	important	important	ADJ
cana-1862	77	14	component	component	NOUN
cana-1862	77	15	of	of	ADP
cana-1862	77	16	a	a	DET
cana-1862	77	17	powerful	powerful	ADJ
cana-1862	77	18	vulnerability	vulnerability	NOUN
cana-1862	77	19	detection	detection	NOUN
cana-1862	77	20	system	system	NOUN
cana-1862	77	21	,	,	PUNCT
cana-1862	77	22	but	but	CCONJ
cana-1862	77	23	they	they	PRON
cana-1862	77	24	add	add	VERB
cana-1862	77	25	clutter	clutter	NOUN
cana-1862	77	26	to	to	ADP
cana-1862	77	27	the	the	DET
cana-1862	77	28	clean	clean	ADJ
cana-1862	77	29	machine	machine	NOUN
cana-1862	77	30	learning	learn	VERB
cana-1862	77	31	pipeline	pipeline	NOUN
cana-1862	77	32	.	.	PUNCT
cana-1862	78	1	counter	counter	PROPN
cana-1862	78	2	:	:	PUNCT
cana-1862	78	3	statistically	statistically	ADV
cana-1862	78	4	analysing	analyse	VERB
cana-1862	78	5	the	the	DET
cana-1862	78	6	input	input	NOUN
cana-1862	78	7	data	datum	NOUN
cana-1862	78	8	to	to	PART
cana-1862	78	9	enhance	enhance	VERB
cana-1862	78	10	its	its	PRON
cana-1862	78	11	quality	quality	NOUN
cana-1862	78	12	before	before	SCONJ
cana-1862	78	13	it	it	PRON
cana-1862	78	14	is	be	AUX
cana-1862	78	15	fed	feed	VERB
cana-1862	78	16	into	into	ADP
cana-1862	78	17	machine	machine	NOUN
cana-1862	78	18	language	language	NOUN
cana-1862	78	19	models	model	NOUN
cana-1862	78	20	(	(	PUNCT
cana-1862	78	21	better	well	ADV
cana-1862	78	22	known	know	VERB
cana-1862	78	23	as	as	ADP
cana-1862	78	24	feature	feature	NOUN
cana-1862	78	25	engineering	engineering	NOUN
cana-1862	78	26	)	)	PUNCT
cana-1862	78	27	.	.	PUNCT
cana-1862	79	1	for	for	ADP
cana-1862	79	2	example	example	NOUN
cana-1862	79	3	,	,	PUNCT
cana-1862	79	4	one	one	PRON
cana-1862	79	5	can	can	AUX
cana-1862	79	6	represent	represent	VERB
cana-1862	79	7	network	network	NOUN
cana-1862	79	8	traffic	traffic	NOUN
cana-1862	79	9	as	as	ADP
cana-1862	79	10	a	a	DET
cana-1862	79	11	graph	graph	NOUN
cana-1862	79	12	and	and	CCONJ
cana-1862	79	13	learn	learn	VERB
cana-1862	79	14	anomaly	anomaly	NOUN
cana-1862	79	15	detection	detection	NOUN
cana-1862	79	16	algorithms	algorithm	NOUN
cana-1862	79	17	(	(	PUNCT
cana-1862	79	18	e.g.	e.g.	ADV
cana-1862	79	19	,	,	PUNCT
cana-1862	79	20	autoencoders	autoencoder	NOUN
cana-1862	79	21	,	,	PUNCT
cana-1862	79	22	gmms	gmms	NOUN
cana-1862	79	23	)	)	PUNCT
cana-1862	79	24	on	on	ADP
cana-1862	79	25	graph	graph	NOUN
cana-1862	79	26	-	-	PUNCT
cana-1862	79	27	structured	structure	VERB
cana-1862	79	28	data	datum	NOUN
cana-1862	79	29	to	to	PART
cana-1862	79	30	detect	detect	VERB
cana-1862	79	31	vulnerabilities	vulnerability	NOUN
cana-1862	79	32	.	.	PUNCT
cana-1862	80	1	using	use	VERB
cana-1862	80	2	optimization	optimization	NOUN
cana-1862	80	3	methods	method	NOUN
cana-1862	80	4	to	to	PART
cana-1862	80	5	tune	tune	VERB
cana-1862	80	6	the	the	DET
cana-1862	80	7	hyper	hyper	NOUN
cana-1862	80	8	-	-	NOUN
cana-1862	80	9	parameters	parameter	NOUN
cana-1862	80	10	of	of	ADP
cana-1862	80	11	a	a	DET
cana-1862	80	12	machine	machine	NOUN
cana-1862	80	13	learning	learning	NOUN
cana-1862	80	14	model	model	NOUN
cana-1862	80	15	as	as	SCONJ
cana-1862	80	16	to	to	PART
cana-1862	80	17	prevent	prevent	VERB
cana-1862	80	18	overfitting	overfitting	NOUN
cana-1862	80	19	and	and	CCONJ
cana-1862	80	20	allow	allow	VERB
cana-1862	80	21	them	they	PRON
cana-1862	80	22	to	to	PART
cana-1862	80	23	have	have	VERB
cana-1862	80	24	good	good	ADJ
cana-1862	80	25	performance	performance	NOUN
cana-1862	80	26	on	on	ADP
cana-1862	80	27	new	new	ADJ
cana-1862	80	28	,	,	PUNCT
cana-1862	80	29	unseen	unseen	ADJ
cana-1862	80	30	data	datum	NOUN
cana-1862	80	31	.	.	PUNCT
cana-1862	81	1	in	in	ADP
cana-1862	81	2	addition	addition	NOUN
cana-1862	81	3	,	,	PUNCT
cana-1862	81	4	probabilistic	probabilistic	ADJ
cana-1862	81	5	models	model	NOUN
cana-1862	81	6	such	such	ADJ
cana-1862	81	7	as	as	ADP
cana-1862	81	8	bayesian	bayesian	NOUN
cana-1862	81	9	networks	network	NOUN
cana-1862	81	10	can	can	AUX
cana-1862	81	11	be	be	AUX
cana-1862	81	12	coordinated	coordinate	VERB
cana-1862	81	13	with	with	ADP
cana-1862	81	14	other	other	ADJ
cana-1862	81	15	algorithms	algorithm	NOUN
cana-1862	81	16	(	(	PUNCT
cana-1862	81	17	e.g.	e.g.	ADV
cana-1862	81	18	,	,	PUNCT
cana-1862	81	19	merging	merge	VERB
cana-1862	81	20	the	the	DET
cana-1862	81	21	output	output	NOUN
cana-1862	81	22	of	of	ADP
cana-1862	81	23	an	an	DET
cana-1862	81	24	autoencoder	autoencoder	NOUN
cana-1862	81	25	within	within	ADP
cana-1862	81	26	a	a	DET
cana-1862	81	27	bayesian	bayesian	NOUN
cana-1862	81	28	setting	setting	NOUN
cana-1862	81	29	)	)	PUNCT
cana-1862	81	30	in	in	ADP
cana-1862	81	31	order	order	NOUN
cana-1862	81	32	to	to	PART
cana-1862	81	33	generate	generate	VERB
cana-1862	81	34	hybrid	hybrid	ADJ
cana-1862	81	35	models	model	NOUN
cana-1862	81	36	which	which	PRON
cana-1862	81	37	improve	improve	VERB
cana-1862	81	38	the	the	DET
cana-1862	81	39	capability	capability	NOUN
cana-1862	81	40	for	for	ADP
cana-1862	81	41	accurate	accurate	ADJ
cana-1862	81	42	detection	detection	NOUN
cana-1862	81	43	.	.	PUNCT
cana-1862	82	1	although	although	SCONJ
cana-1862	82	2	the	the	DET
cana-1862	82	3	integration	integration	NOUN
cana-1862	82	4	of	of	ADP
cana-1862	82	5	high	high	ADJ
cana-1862	82	6	-	-	PUNCT
cana-1862	82	7	end	end	NOUN
cana-1862	82	8	mathematical	mathematical	ADJ
cana-1862	82	9	models	model	NOUN
cana-1862	82	10	and	and	CCONJ
cana-1862	82	11	machine	machine	NOUN
cana-1862	82	12	learning	learning	NOUN
cana-1862	82	13	is	be	AUX
cana-1862	82	14	a	a	DET
cana-1862	82	15	potentially	potentially	ADV
cana-1862	82	16	exciting	exciting	ADJ
cana-1862	82	17	method	method	NOUN
cana-1862	82	18	for	for	ADP
cana-1862	82	19	detection	detection	NOUN
cana-1862	82	20	of	of	ADP
cana-1862	82	21	information	information	NOUN
cana-1862	82	22	security	security	NOUN
cana-1862	82	23	vulnerabilities	vulnerability	NOUN
cana-1862	82	24	brings	bring	VERB
cana-1862	82	25	in	in	ADP
cana-1862	82	26	its	its	PRON
cana-1862	82	27	own	own	ADJ
cana-1862	82	28	set	set	NOUN
cana-1862	82	29	of	of	ADP
cana-1862	82	30	challenges	challenge	NOUN
cana-1862	82	31	:	:	PUNCT
cana-1862	82	32	o	o	NOUN
cana-1862	82	33	data	datum	NOUN
cana-1862	82	34	quality	quality	NOUN
cana-1862	82	35	and	and	CCONJ
cana-1862	82	36	labelling	labelling	NOUN
cana-1862	82	37	:	:	PUNCT
cana-1862	82	38	a	a	DET
cana-1862	82	39	lot	lot	NOUN
cana-1862	82	40	of	of	ADP
cana-1862	82	41	machine	machine	NOUN
cana-1862	82	42	learning	learning	NOUN
cana-1862	82	43	models	model	NOUN
cana-1862	82	44	actually	actually	ADV
cana-1862	82	45	depend	depend	VERB
cana-1862	82	46	on	on	ADP
cana-1862	82	47	high	high	ADJ
cana-1862	82	48	-	-	PUNCT
cana-1862	82	49	quality	quality	NOUN
cana-1862	82	50	,	,	PUNCT
cana-1862	82	51	labelled	label	VERB
cana-1862	82	52	data	data	NOUN
cana-1862	82	53	sets	set	NOUN
cana-1862	82	54	,	,	PUNCT
cana-1862	82	55	which	which	PRON
cana-1862	82	56	are	be	AUX
cana-1862	82	57	difficult	difficult	ADJ
cana-1862	82	58	to	to	PART
cana-1862	82	59	obtain	obtain	VERB
cana-1862	82	60	in	in	ADP
cana-1862	82	61	cyber	cyber	ADJ
cana-1862	82	62	security	security	NOUN
cana-1862	82	63	due	due	ADP
cana-1862	82	64	to	to	ADP
cana-1862	82	65	the	the	DET
cana-1862	82	66	fact	fact	NOUN
cana-1862	82	67	that	that	SCONJ
cana-1862	82	68	threats	threat	NOUN
cana-1862	82	69	evolve	evolve	VERB
cana-1862	82	70	quite	quite	ADV
cana-1862	82	71	rapidly	rapidly	ADV
cana-1862	82	72	.	.	PUNCT
cana-1862	83	1	future	future	ADJ
cana-1862	83	2	work	work	NOUN
cana-1862	83	3	will	will	AUX
cana-1862	83	4	focus	focus	VERB
cana-1862	83	5	on	on	ADP
cana-1862	83	6	exploring	explore	VERB
cana-1862	83	7	semi	semi	ADJ
cana-1862	83	8	-	-	ADJ
cana-1862	83	9	supervised	supervised	ADJ
cana-1862	83	10	and	and	CCONJ
cana-1862	83	11	unsupervised	unsupervised	ADJ
cana-1862	83	12	learning	learning	NOUN
cana-1862	83	13	methods	method	NOUN
cana-1862	83	14	to	to	PART
cana-1862	83	15	tackle	tackle	VERB
cana-1862	83	16	this	this	DET
cana-1862	83	17	problem	problem	NOUN
cana-1862	83	18	.	.	PUNCT
cana-1862	84	1	o	o	NOUN
cana-1862	84	2	scalability	scalability	NOUN
cana-1862	84	3	:	:	PUNCT
cana-1862	84	4	cybersecurity	cybersecurity	NOUN
cana-1862	84	5	solutions	solution	NOUN
cana-1862	84	6	are	be	AUX
cana-1862	84	7	dealing	deal	VERB
cana-1862	84	8	with	with	ADP
cana-1862	84	9	vast	vast	ADJ
cana-1862	84	10	amounts	amount	NOUN
cana-1862	84	11	of	of	ADP
cana-1862	84	12	real	real	ADJ
cana-1862	84	13	-	-	PUNCT
cana-1862	84	14	time	time	NOUN
cana-1862	84	15	data	datum	NOUN
cana-1862	84	16	.	.	PUNCT
cana-1862	85	1	machine	machine	NOUN
cana-1862	85	2	learning	learning	NOUN
cana-1862	85	3	models	model	NOUN
cana-1862	85	4	must	must	AUX
cana-1862	85	5	be	be	AUX
cana-1862	85	6	computationally	computationally	ADV
cana-1862	85	7	efficient	efficient	ADJ
cana-1862	85	8	to	to	PART
cana-1862	85	9	scale	scale	VERB
cana-1862	85	10	them	they	PRON
cana-1862	85	11	up	up	ADP
cana-1862	85	12	to	to	ADP
cana-1862	85	13	caches	cache	NOUN
cana-1862	85	14	storing	store	VERB
cana-1862	85	15	hundreds	hundred	NOUN
cana-1862	85	16	of	of	ADP
cana-1862	85	17	millions	million	NOUN
cana-1862	85	18	or	or	CCONJ
cana-1862	85	19	billions	billion	NOUN
cana-1862	85	20	of	of	ADP
cana-1862	85	21	pages	page	NOUN
cana-1862	85	22	on	on	ADP
cana-1862	85	23	the	the	DET
cana-1862	85	24	one	one	NUM
cana-1862	85	25	hand	hand	NOUN
cana-1862	85	26	and	and	CCONJ
cana-1862	85	27	ensure	ensure	VERB
cana-1862	85	28	high	high	ADJ
cana-1862	85	29	detection	detection	NOUN
cana-1862	85	30	accuracy	accuracy	NOUN
cana-1862	85	31	at	at	ADP
cana-1862	85	32	the	the	DET
cana-1862	85	33	same	same	ADJ
cana-1862	85	34	time	time	NOUN
cana-1862	85	35	.	.	PUNCT
cana-1862	86	1	o	o	X
cana-1862	86	2	explain	explain	NOUN
cana-1862	86	3	-	-	PUNCT
cana-1862	86	4	ability	ability	NOUN
cana-1862	86	5	:	:	PUNCT
cana-1862	86	6	since	since	SCONJ
cana-1862	86	7	deep	deep	ADJ
cana-1862	86	8	neural	neural	ADJ
cana-1862	86	9	networks	network	NOUN
cana-1862	86	10	are	be	AUX
cana-1862	86	11	able	able	ADJ
cana-1862	86	12	to	to	PART
cana-1862	86	13	model	model	VERB
cana-1862	86	14	human	human	ADJ
cana-1862	86	15	-	-	PUNCT
cana-1862	86	16	like	like	ADJ
cana-1862	86	17	cognitive	cognitive	ADJ
cana-1862	86	18	functions	function	NOUN
cana-1862	86	19	,	,	PUNCT
cana-1862	86	20	it	it	PRON
cana-1862	86	21	is	be	AUX
cana-1862	86	22	key	key	ADJ
cana-1862	86	23	that	that	SCONJ
cana-1862	86	24	decisions	decision	NOUN
cana-1862	86	25	made	make	VERB
cana-1862	86	26	by	by	ADP
cana-1862	86	27	such	such	ADJ
cana-1862	86	28	highly	highly	ADV
cana-1862	86	29	complex	complex	ADJ
cana-1862	86	30	models	model	NOUN
cana-1862	86	31	can	can	AUX
cana-1862	86	32	be	be	AUX
cana-1862	86	33	explained	explain	VERB
cana-1862	86	34	in	in	ADP
cana-1862	86	35	the	the	DET
cana-1862	86	36	context	context	NOUN
cana-1862	86	37	of	of	ADP
cana-1862	86	38	security	security	NOUN
cana-1862	86	39	operations	operation	NOUN
cana-1862	86	40	.	.	PUNCT
cana-1862	87	1	more	more	ADJ
cana-1862	87	2	investigations	investigation	NOUN
cana-1862	87	3	in	in	ADP
cana-1862	87	4	explainable	explainable	ADJ
cana-1862	87	5	ai	ai	NOUN
cana-1862	87	6	are	be	AUX
cana-1862	87	7	required	require	VERB
cana-1862	87	8	for	for	ADP
cana-1862	87	9	accounting	account	VERB
cana-1862	87	10	and	and	CCONJ
cana-1862	87	11	justifying	justify	VERB
cana-1862	87	12	these	these	DET
cana-1862	87	13	vulnerability	vulnerability	NOUN
cana-1862	87	14	detection	detection	NOUN
cana-1862	87	15	results	result	NOUN
cana-1862	87	16	.	.	PUNCT
cana-1862	88	1	o	o	X
cana-1862	88	2	continuous	continuous	ADJ
cana-1862	88	3	learning	learning	NOUN
cana-1862	88	4	:	:	PUNCT
cana-1862	88	5	as	as	SCONJ
cana-1862	88	6	attackers	attacker	NOUN
cana-1862	88	7	change	change	VERB
cana-1862	88	8	their	their	PRON
cana-1862	88	9	ways	way	NOUN
cana-1862	88	10	,	,	PUNCT
cana-1862	88	11	models	model	NOUN
cana-1862	88	12	must	must	AUX
cana-1862	88	13	always	always	ADV
cana-1862	88	14	be	be	AUX
cana-1862	88	15	up	up	ADP
cana-1862	88	16	to	to	ADP
cana-1862	88	17	date	date	NOUN
cana-1862	88	18	and	and	CCONJ
cana-1862	88	19	adapt	adapt	VERB
cana-1862	88	20	with	with	ADP
cana-1862	88	21	the	the	DET
cana-1862	88	22	threat	threat	NOUN
cana-1862	88	23	and	and	CCONJ
cana-1862	88	24	network	network	NOUN
cana-1862	88	25	conditions	condition	NOUN
cana-1862	88	26	online	online	ADV
cana-1862	88	27	.	.	PUNCT
cana-1862	89	1	in	in	ADP
cana-1862	89	2	this	this	DET
cana-1862	89	3	regard	regard	NOUN
cana-1862	89	4	,	,	PUNCT
cana-1862	89	5	work	work	NOUN
cana-1862	89	6	on	on	ADP
cana-1862	89	7	reinforcement	reinforcement	NOUN
cana-1862	89	8	learning	learning	NOUN
cana-1862	89	9	and	and	CCONJ
cana-1862	89	10	continual	continual	ADJ
cana-1862	89	11	learning	learning	NOUN
cana-1862	89	12	is	be	AUX
cana-1862	89	13	very	very	ADV
cana-1862	89	14	promising	promising	ADJ
cana-1862	89	15	.	.	PUNCT
cana-1862	90	1	the	the	DET
cana-1862	90	2	combination	combination	NOUN
cana-1862	90	3	of	of	ADP
cana-1862	90	4	modern	modern	ADJ
cana-1862	90	5	mathematical	mathematical	ADJ
cana-1862	90	6	methods	method	NOUN
cana-1862	90	7	and	and	CCONJ
cana-1862	90	8	machine	machine	NOUN
cana-1862	90	9	learning	learning	NOUN
cana-1862	90	10	provides	provide	VERB
cana-1862	90	11	a	a	DET
cana-1862	90	12	very	very	ADV
cana-1862	90	13	strong	strong	ADJ
cana-1862	90	14	weapon	weapon	NOUN
cana-1862	90	15	for	for	ADP
cana-1862	90	16	detecting	detect	VERB
cana-1862	90	17	vulnerabilities	vulnerability	NOUN
cana-1862	90	18	in	in	ADP
cana-1862	90	19	information	information	NOUN
cana-1862	90	20	security	security	NOUN
cana-1862	90	21	.	.	PUNCT
cana-1862	91	1	in	in	ADP
cana-1862	91	2	this	this	DET
cana-1862	91	3	paper	paper	NOUN
cana-1862	91	4	,	,	PUNCT
cana-1862	91	5	a	a	DET
cana-1862	91	6	novel	novel	ADJ
cana-1862	91	7	way	way	NOUN
cana-1862	91	8	to	to	PART
cana-1862	91	9	detect	detect	VERB
cana-1862	91	10	vulnerabilities	vulnerability	NOUN
cana-1862	91	11	in	in	ADP
cana-1862	91	12	highly	highly	ADV
cana-1862	91	13	dynamic	dynamic	ADJ
cana-1862	91	14	complex	complex	ADJ
cana-1862	91	15	systems	system	NOUN
cana-1862	91	16	dubbed	dub	VERB
cana-1862	91	17	bayesian	bayesian	NOUN
cana-1862	91	18	networks	network	NOUN
cana-1862	91	19	,	,	PUNCT
cana-1862	91	20	autoencoders	autoencoder	NOUN
cana-1862	91	21	,	,	PUNCT
cana-1862	91	22	gaussian	gaussian	ADJ
cana-1862	91	23	mixture	mixture	NOUN
cana-1862	91	24	models	model	NOUN
cana-1862	91	25	and	and	CCONJ
cana-1862	91	26	reinforcement	reinforcement	NOUN
cana-1862	91	27	learning	learning	NOUN
cana-1862	91	28	along	along	ADP
cana-1862	91	29	with	with	ADP
cana-1862	91	30	statistical	statistical	ADJ
cana-1862	91	31	/	/	SYM
cana-1862	91	32	probabilistic	probabilistic	ADJ
cana-1862	91	33	methods	method	NOUN
cana-1862	91	34	was	be	AUX
cana-1862	91	35	proposed	propose	VERB
cana-1862	91	36	.	.	PUNCT
cana-1862	92	1	the	the	DET
cana-1862	92	2	adoption	adoption	NOUN
cana-1862	92	3	of	of	ADP
cana-1862	92	4	these	these	DET
cana-1862	92	5	methods	method	NOUN
cana-1862	92	6	opens	open	VERB
cana-1862	92	7	the	the	DET
cana-1862	92	8	door	door	NOUN
cana-1862	92	9	to	to	ADP
cana-1862	92	10	advancing	advance	VERB
cana-1862	92	11	adaptive	adaptive	ADJ
cana-1862	92	12	-	-	PUNCT
cana-1862	92	13	security	security	NOUN
cana-1862	92	14	systems	system	NOUN
cana-1862	92	15	with	with	ADP
cana-1862	92	16	better	well	ADJ
cana-1862	92	17	ability	ability	NOUN
cana-1862	92	18	to	to	PART
cana-1862	92	19	cover	cover	VERB
cana-1862	92	20	both	both	CCONJ
cana-1862	92	21	the	the	DET
cana-1862	92	22	previously	previously	ADV
cana-1862	92	23	-	-	PUNCT
cana-1862	92	24	seen	see	VERB
cana-1862	92	25	-	-	PUNCT
cana-1862	92	26	to	to	AUX
cana-1862	92	27	-	-	PUNCT
cana-1862	92	28	known	know	VERB
cana-1862	92	29	and	and	CCONJ
cana-1862	92	30	known	know	VERB
cana-1862	92	31	-	-	PUNCT
cana-1862	92	32	to	to	ADP
cana-1862	92	33	-	-	PUNCT
cana-1862	92	34	unseen	unseen	ADJ
cana-1862	92	35	threats	threat	NOUN
cana-1862	92	36	.	.	PUNCT
cana-1862	93	1	this	this	DET
cana-1862	93	2	work	work	NOUN
cana-1862	93	3	can	can	AUX
cana-1862	93	4	potentially	potentially	ADV
cana-1862	93	5	evolve	evolve	VERB
cana-1862	93	6	the	the	DET
cana-1862	93	7	cybersecurity	cybersecurity	NOUN
cana-1862	93	8	frameworks	framework	NOUN
cana-1862	93	9	in	in	ADP
cana-1862	93	10	future	future	NOUN
cana-1862	93	11	to	to	PART
cana-1862	93	12	ensure	ensure	VERB
cana-1862	93	13	privacy	privacy	NOUN
cana-1862	93	14	and	and	CCONJ
cana-1862	93	15	security	security	NOUN
cana-1862	93	16	of	of	ADP
cana-1862	93	17	critical	critical	ADJ
cana-1862	93	18	information	information	NOUN
cana-1862	93	19	at	at	ADP
cana-1862	93	20	a	a	DET
cana-1862	93	21	time	time	NOUN
cana-1862	93	22	when	when	SCONJ
cana-1862	93	23	everything	everything	PRON
cana-1862	93	24	is	be	AUX
cana-1862	93	25	connected	connect	VERB
cana-1862	93	26	.	.	PUNCT
cana-1862	94	1	communications	communication	NOUN
cana-1862	94	2	on	on	ADP
cana-1862	94	3	applied	apply	VERB
cana-1862	94	4	nonlinear	nonlinear	ADJ
cana-1862	94	5	analysis	analysis	NOUN
cana-1862	94	6	issn	issn	NOUN
cana-1862	94	7	:	:	PUNCT
cana-1862	94	8	1074	1074	NUM
cana-1862	94	9	-	-	PUNCT
cana-1862	94	10	133x	133x	NUM
cana-1862	94	11	vol	vol	NOUN
cana-1862	94	12	32	32	NUM
cana-1862	94	13	no	no	NOUN
cana-1862	94	14	.	.	NOUN
cana-1862	94	15	2	2	NUM
cana-1862	94	16	(	(	PUNCT
cana-1862	94	17	2025	2025	NUM
cana-1862	94	18	)	)	PUNCT
cana-1862	94	19	697	697	NUM
cana-1862	94	20	https://internationalpubls.com	https://internationalpubls.com	X
cana-1862	94	21	2	2	NUM
cana-1862	94	22	.	.	X
cana-1862	94	23	related	relate	VERB
cana-1862	94	24	work	work	NOUN
cana-1862	94	25	:	:	PUNCT
cana-1862	94	26	a	a	DET
cana-1862	94	27	combined	combined	ADJ
cana-1862	94	28	effect	effect	NOUN
cana-1862	94	29	of	of	ADP
cana-1862	94	30	machine	machine	NOUN
cana-1862	94	31	learning	learning	NOUN
cana-1862	94	32	and	and	CCONJ
cana-1862	94	33	sophisticated	sophisticated	ADJ
cana-1862	94	34	statistical	statistical	ADJ
cana-1862	94	35	methods	method	NOUN
cana-1862	94	36	is	be	AUX
cana-1862	94	37	one	one	NUM
cana-1862	94	38	of	of	ADP
cana-1862	94	39	the	the	DET
cana-1862	94	40	strategies	strategy	NOUN
cana-1862	94	41	being	be	AUX
cana-1862	94	42	successfully	successfully	ADV
cana-1862	94	43	used	use	VERB
cana-1862	94	44	for	for	ADP
cana-1862	94	45	information	information	NOUN
cana-1862	94	46	security	security	NOUN
cana-1862	94	47	vulnerability	vulnerability	NOUN
cana-1862	94	48	detection	detection	NOUN
cana-1862	94	49	.	.	PUNCT
cana-1862	95	1	this	this	DET
cana-1862	95	2	section	section	NOUN
cana-1862	95	3	provides	provide	VERB
cana-1862	95	4	a	a	DET
cana-1862	95	5	compilation	compilation	NOUN
cana-1862	95	6	of	of	ADP
cana-1862	95	7	the	the	DET
cana-1862	95	8	similar	similar	ADJ
cana-1862	95	9	works	work	NOUN
cana-1862	95	10	on	on	ADP
cana-1862	95	11	vulnerability	vulnerability	NOUN
cana-1862	95	12	detection	detection	NOUN
cana-1862	95	13	with	with	ADP
cana-1862	95	14	known	know	VERB
cana-1862	95	15	mathematical	mathematical	ADJ
cana-1862	95	16	and	and	CCONJ
cana-1862	95	17	machine	machine	NOUN
cana-1862	95	18	learning	learning	NOUN
cana-1862	95	19	models	model	NOUN
cana-1862	95	20	.	.	PUNCT
cana-1862	96	1	the	the	DET
cana-1862	96	2	literatures	literature	NOUN
cana-1862	96	3	can	can	AUX
cana-1862	96	4	be	be	AUX
cana-1862	96	5	categorized	categorize	VERB
cana-1862	96	6	into	into	ADP
cana-1862	96	7	supervised	supervised	ADJ
cana-1862	96	8	learning	learning	NOUN
cana-1862	96	9	,	,	PUNCT
cana-1862	96	10	unsupervised	unsupervised	ADJ
cana-1862	96	11	learning	learning	NOUN
cana-1862	96	12	,	,	PUNCT
cana-1862	96	13	probabilistic	probabilistic	ADJ
cana-1862	96	14	model	model	NOUN
cana-1862	96	15	,	,	PUNCT
cana-1862	96	16	anomaly	anomaly	NOUN
cana-1862	96	17	detection	detection	NOUN
cana-1862	96	18	and	and	CCONJ
cana-1862	96	19	hybrid	hybrid	NOUN
cana-1862	96	20	techniques	technique	NOUN
cana-1862	96	21	based	base	VERB
cana-1862	96	22	on	on	ADP
cana-1862	96	23	the	the	DET
cana-1862	96	24	specific	specific	ADJ
cana-1862	96	25	mathematical	mathematical	ADJ
cana-1862	96	26	method	method	NOUN
cana-1862	96	27	used	use	VERB
cana-1862	96	28	to	to	PART
cana-1862	96	29	strengthen	strengthen	VERB
cana-1862	96	30	security	security	NOUN
cana-1862	96	31	.	.	PUNCT
cana-1862	97	1	●	●	PUNCT
cana-1862	97	2	supervised	supervised	ADJ
cana-1862	97	3	learning	learning	NOUN
cana-1862	97	4	for	for	ADP
cana-1862	97	5	vulnerability	vulnerability	NOUN
cana-1862	97	6	detection	detection	NOUN
cana-1862	97	7	:	:	PUNCT
cana-1862	97	8	the	the	DET
cana-1862	97	9	effectiveness	effectiveness	NOUN
cana-1862	97	10	of	of	ADP
cana-1862	97	11	supervised	supervised	ADJ
cana-1862	97	12	learning	learning	NOUN
cana-1862	97	13	models	model	NOUN
cana-1862	97	14	is	be	AUX
cana-1862	97	15	well	well	ADV
cana-1862	97	16	studied	study	VERB
cana-1862	97	17	in	in	ADP
cana-1862	97	18	the	the	DET
cana-1862	97	19	context	context	NOUN
cana-1862	97	20	of	of	ADP
cana-1862	97	21	vulnerability	vulnerability	NOUN
cana-1862	97	22	detection	detection	NOUN
cana-1862	97	23	,	,	PUNCT
cana-1862	97	24	especially	especially	ADV
cana-1862	97	25	when	when	SCONJ
cana-1862	97	26	labeled	label	VERB
cana-1862	97	27	datasets	dataset	NOUN
cana-1862	97	28	are	be	AUX
cana-1862	97	29	available	available	ADJ
cana-1862	97	30	.	.	PUNCT
cana-1862	98	1	majority	majority	NOUN
cana-1862	98	2	of	of	ADP
cana-1862	98	3	the	the	DET
cana-1862	98	4	research	research	NOUN
cana-1862	98	5	have	have	AUX
cana-1862	98	6	applied	apply	VERB
cana-1862	98	7	different	different	ADJ
cana-1862	98	8	algorithms	algorithm	NOUN
cana-1862	98	9	namely	namely	ADV
cana-1862	98	10	decision	decision	NOUN
cana-1862	98	11	trees	tree	NOUN
cana-1862	98	12	,	,	PUNCT
cana-1862	98	13	random	random	ADJ
cana-1862	98	14	forests	forest	NOUN
cana-1862	98	15	,	,	PUNCT
cana-1862	98	16	naive	naive	ADJ
cana-1862	98	17	bayes	bayes	NOUN
cana-1862	98	18	and	and	CCONJ
cana-1862	98	19	neural	neural	ADJ
cana-1862	98	20	networks	network	NOUN
cana-1862	98	21	to	to	PART
cana-1862	98	22	classify	classify	VERB
cana-1862	98	23	security	security	NOUN
cana-1862	98	24	threats	threat	NOUN
cana-1862	98	25	.	.	PUNCT
cana-1862	99	1	these	these	DET
cana-1862	99	2	models	model	NOUN
cana-1862	99	3	are	be	AUX
cana-1862	99	4	trained	train	VERB
cana-1862	99	5	on	on	ADP
cana-1862	99	6	labelled	label	VERB
cana-1862	99	7	data	datum	NOUN
cana-1862	99	8	so	so	SCONJ
cana-1862	99	9	they	they	PRON
cana-1862	99	10	are	be	AUX
cana-1862	99	11	able	able	ADJ
cana-1862	99	12	to	to	PART
cana-1862	99	13	spot	spot	VERB
cana-1862	99	14	distressed	distressed	ADJ
cana-1862	99	15	vulnerabilities	vulnerability	NOUN
cana-1862	99	16	by	by	ADP
cana-1862	99	17	learning	learn	VERB
cana-1862	99	18	their	their	PRON
cana-1862	99	19	features	feature	NOUN
cana-1862	99	20	.	.	PUNCT
cana-1862	100	1	feature	feature	NOUN
cana-1862	100	2	based	base	VERB
cana-1862	100	3	vulnerability	vulnerability	NOUN
cana-1862	100	4	detection	detection	NOUN
cana-1862	100	5	random	random	ADJ
cana-1862	100	6	forests	forest	NOUN
cana-1862	100	7	over	over	ADP
cana-1862	100	8	network	network	NOUN
cana-1862	100	9	traffic	traffic	NOUN
cana-1862	100	10	(	(	PUNCT
cana-1862	100	11	with	with	ADP
cana-1862	100	12	attribute	attribute	NOUN
cana-1862	100	13	entropy	entropy	NOUN
cana-1862	100	14	and	and	CCONJ
cana-1862	100	15	statistical	statistical	ADJ
cana-1862	100	16	moments)[14	moments)[14	NOUN
cana-1862	100	17	]	]	PUNCT
cana-1862	100	18	.	.	PUNCT
cana-1862	101	1	these	these	DET
cana-1862	101	2	extracted	extract	VERB
cana-1862	101	3	features	feature	NOUN
cana-1862	101	4	were	be	AUX
cana-1862	101	5	used	use	VERB
cana-1862	101	6	to	to	PART
cana-1862	101	7	update	update	VERB
cana-1862	101	8	a	a	DET
cana-1862	101	9	classifier	classifier	NOUN
cana-1862	101	10	which	which	PRON
cana-1862	101	11	was	be	AUX
cana-1862	101	12	then	then	ADV
cana-1862	101	13	able	able	ADJ
cana-1862	101	14	to	to	PART
cana-1862	101	15	well	well	ADV
cana-1862	101	16	identify	identify	VERB
cana-1862	101	17	known	know	VERB
cana-1862	101	18	vulnerabilities	vulnerability	NOUN
cana-1862	101	19	.	.	PUNCT
cana-1862	102	1	while	while	SCONJ
cana-1862	102	2	these	these	DET
cana-1862	102	3	models	model	NOUN
cana-1862	102	4	perform	perform	VERB
cana-1862	102	5	quite	quite	ADV
cana-1862	102	6	well	well	ADV
cana-1862	102	7	they	they	PRON
cana-1862	102	8	come	come	VERB
cana-1862	102	9	with	with	ADP
cana-1862	102	10	limitations	limitation	NOUN
cana-1862	102	11	,	,	PUNCT
cana-1862	102	12	particularly	particularly	ADV
cana-1862	102	13	when	when	SCONJ
cana-1862	102	14	it	it	PRON
cana-1862	102	15	comes	come	VERB
cana-1862	102	16	to	to	ADP
cana-1862	102	17	zero	zero	NUM
cana-1862	102	18	-	-	PUNCT
cana-1862	102	19	day	day	NOUN
cana-1862	102	20	vulnerabilities	vulnerability	NOUN
cana-1862	102	21	that	that	PRON
cana-1862	102	22	have	have	VERB
cana-1862	102	23	less	less	ADJ
cana-1862	102	24	amount	amount	NOUN
cana-1862	102	25	of	of	ADP
cana-1862	102	26	labeled	label	VERB
cana-1862	102	27	data	datum	NOUN
cana-1862	102	28	for	for	ADP
cana-1862	102	29	new	new	ADJ
cana-1862	102	30	threats	threat	NOUN
cana-1862	102	31	.	.	PUNCT
cana-1862	103	1	the	the	DET
cana-1862	103	2	efficacy	efficacy	NOUN
cana-1862	103	3	of	of	ADP
cana-1862	103	4	artificial	artificial	ADJ
cana-1862	103	5	neural	neural	ADJ
cana-1862	103	6	networks	network	NOUN
cana-1862	103	7	(	(	PUNCT
cana-1862	103	8	anns	anns	NOUN
cana-1862	103	9	)	)	PUNCT
cana-1862	103	10	deep	deep	ADJ
cana-1862	103	11	learning	learning	NOUN
cana-1862	103	12	has	have	AUX
cana-1862	103	13	been	be	AUX
cana-1862	103	14	widely	widely	ADV
cana-1862	103	15	used	use	VERB
cana-1862	103	16	in	in	ADP
cana-1862	103	17	vulnerability	vulnerability	NOUN
cana-1862	103	18	detection	detection	NOUN
cana-1862	103	19	with	with	ADP
cana-1862	103	20	fully	fully	ADV
cana-1862	103	21	connected	connect	VERB
cana-1862	103	22	neural	neural	ADJ
cana-1862	103	23	networks	network	NOUN
cana-1862	103	24	(	(	PUNCT
cana-1862	103	25	fcnns	fcnn	NOUN
cana-1862	103	26	)	)	PUNCT
cana-1862	103	27	and	and	CCONJ
cana-1862	103	28	recurrent	recurrent	ADJ
cana-1862	103	29	neural	neural	ADJ
cana-1862	103	30	networks	network	NOUN
cana-1862	103	31	(	(	PUNCT
cana-1862	103	32	rnns	rnns	PROPN
cana-1862	103	33	)	)	PUNCT
cana-1862	103	34	proposed	propose	VERB
cana-1862	103	35	in	in	ADP
cana-1862	103	36	recent	recent	ADJ
cana-1862	103	37	years	year	NOUN
cana-1862	103	38	.	.	PUNCT
cana-1862	104	1	a	a	DET
cana-1862	104	2	deep	deep	ADJ
cana-1862	104	3	learning	learning	NOUN
cana-1862	104	4	based	base	VERB
cana-1862	104	5	approach	approach	NOUN
cana-1862	104	6	with	with	ADP
cana-1862	104	7	ann	ann	PROPN
cana-1862	104	8	to	to	PART
cana-1862	104	9	forecast	forecast	VERB
cana-1862	104	10	the	the	DET
cana-1862	104	11	vulnerabilities	vulnerability	NOUN
cana-1862	104	12	using	use	VERB
cana-1862	104	13	past	past	ADJ
cana-1862	104	14	security	security	NOUN
cana-1862	104	15	data	datum	NOUN
cana-1862	104	16	.	.	PUNCT
cana-1862	105	1	with	with	ADP
cana-1862	105	2	the	the	DET
cana-1862	105	3	help	help	NOUN
cana-1862	105	4	of	of	ADP
cana-1862	105	5	mathematical	mathematical	ADJ
cana-1862	105	6	optimization	optimization	NOUN
cana-1862	105	7	algorithms	algorithm	NOUN
cana-1862	105	8	like	like	ADP
cana-1862	105	9	stochastic	stochastic	ADJ
cana-1862	105	10	gradient	gradient	ADJ
cana-1862	105	11	descent	descent	NOUN
cana-1862	105	12	(	(	PUNCT
cana-1862	105	13	sgd	sgd	PROPN
cana-1862	105	14	)	)	PUNCT
cana-1862	105	15	,	,	PUNCT
cana-1862	105	16	they	they	PRON
cana-1862	105	17	optimized	optimize	VERB
cana-1862	105	18	a	a	DET
cana-1862	105	19	big	big	ADJ
cana-1862	105	20	neural	neural	ADJ
cana-1862	105	21	network	network	NOUN
cana-1862	105	22	design	design	NOUN
cana-1862	105	23	working	work	VERB
cana-1862	105	24	on	on	ADP
cana-1862	105	25	high	high	ADJ
cana-1862	105	26	-	-	PUNCT
cana-1862	105	27	dimensional	dimensional	ADJ
cana-1862	105	28	data	datum	NOUN
cana-1862	105	29	.	.	PUNCT
cana-1862	106	1	nevertheless	nevertheless	ADV
cana-1862	106	2	,	,	PUNCT
cana-1862	106	3	model	model	NOUN
cana-1862	106	4	performance	performance	NOUN
cana-1862	106	5	was	be	AUX
cana-1862	106	6	closely	closely	ADV
cana-1862	106	7	tied	tie	VERB
cana-1862	106	8	to	to	ADP
cana-1862	106	9	the	the	DET
cana-1862	106	10	quality	quality	NOUN
cana-1862	106	11	and	and	CCONJ
cana-1862	106	12	size	size	NOUN
cana-1862	106	13	of	of	ADP
cana-1862	106	14	sources	source	NOUN
cana-1862	106	15	of	of	ADP
cana-1862	106	16	labelled	label	VERB
cana-1862	106	17	training	training	NOUN
cana-1862	106	18	data	datum	NOUN
cana-1862	106	19	but	but	CCONJ
cana-1862	106	20	this	this	PRON
cana-1862	106	21	only	only	ADV
cana-1862	106	22	emphasized	emphasize	VERB
cana-1862	106	23	one	one	NUM
cana-1862	106	24	problem	problem	NOUN
cana-1862	106	25	that	that	PRON
cana-1862	106	26	is	be	AUX
cana-1862	106	27	the	the	DET
cana-1862	106	28	limited	limited	ADJ
cana-1862	106	29	availability	availability	NOUN
cana-1862	106	30	of	of	ADP
cana-1862	106	31	good	good	ADJ
cana-1862	106	32	ground	ground	NOUN
cana-1862	106	33	truth	truth	NOUN
cana-1862	106	34	materials	material	NOUN
cana-1862	106	35	for	for	ADP
cana-1862	106	36	supervised	supervised	ADJ
cana-1862	106	37	learning	learning	NOUN
cana-1862	106	38	in	in	ADP
cana-1862	106	39	cyber	cyber	PROPN
cana-1862	106	40	security[15	security[15	NOUN
cana-1862	106	41	]	]	PUNCT
cana-1862	106	42	.	.	PUNCT
cana-1862	107	1	●	●	PUNCT
cana-1862	107	2	unsupervised	unsupervised	ADJ
cana-1862	107	3	learning	learning	NOUN
cana-1862	107	4	and	and	CCONJ
cana-1862	107	5	clustering	clustering	ADJ
cana-1862	107	6	methods	method	NOUN
cana-1862	107	7	:	:	PUNCT
cana-1862	107	8	with	with	ADP
cana-1862	107	9	the	the	DET
cana-1862	107	10	paucity	paucity	NOUN
cana-1862	107	11	of	of	ADP
cana-1862	107	12	labelled	label	VERB
cana-1862	107	13	data	datum	NOUN
cana-1862	107	14	in	in	ADP
cana-1862	107	15	cyber	cyber	ADJ
cana-1862	107	16	security	security	NOUN
cana-1862	107	17	,	,	PUNCT
cana-1862	107	18	unsupervised	unsupervised	ADJ
cana-1862	107	19	learning	learning	NOUN
cana-1862	107	20	has	have	AUX
cana-1862	107	21	gained	gain	VERB
cana-1862	107	22	significant	significant	ADJ
cana-1862	107	23	importance	importance	NOUN
cana-1862	107	24	in	in	ADP
cana-1862	107	25	vulnerability	vulnerability	NOUN
cana-1862	107	26	detection	detection	NOUN
cana-1862	107	27	.	.	PUNCT
cana-1862	108	1	such	such	ADJ
cana-1862	108	2	data	datum	NOUN
cana-1862	108	3	does	do	AUX
cana-1862	108	4	not	not	PART
cana-1862	108	5	have	have	AUX
cana-1862	108	6	predefined	predefine	VERB
cana-1862	108	7	labels	label	NOUN
cana-1862	108	8	and	and	CCONJ
cana-1862	108	9	so	so	ADV
cana-1862	108	10	these	these	DET
cana-1862	108	11	models	model	NOUN
cana-1862	108	12	are	be	AUX
cana-1862	108	13	useful	useful	ADJ
cana-1862	108	14	where	where	SCONJ
cana-1862	108	15	the	the	DET
cana-1862	108	16	edge	edge	NOUN
cana-1862	108	17	of	of	ADP
cana-1862	108	18	detection	detection	NOUN
cana-1862	108	19	is	be	AUX
cana-1862	108	20	to	to	PART
cana-1862	108	21	find	find	VERB
cana-1862	108	22	novelty	novelty	NOUN
cana-1862	108	23	or	or	CCONJ
cana-1862	108	24	zero	zero	NUM
cana-1862	108	25	-	-	PUNCT
cana-1862	108	26	day	day	NOUN
cana-1862	108	27	vulnerability	vulnerability	NOUN
cana-1862	108	28	.	.	PUNCT
cana-1862	109	1	o	o	NOUN
cana-1862	109	2	clustering	cluster	VERB
cana-1862	109	3	based	base	VERB
cana-1862	109	4	anomaly	anomaly	NOUN
cana-1862	109	5	detection	detection	NOUN
cana-1862	109	6	:	:	PUNCT
cana-1862	109	7	there	there	PRON
cana-1862	109	8	have	have	AUX
cana-1862	109	9	been	be	AUX
cana-1862	109	10	a	a	DET
cana-1862	109	11	lot	lot	NOUN
cana-1862	109	12	of	of	ADP
cana-1862	109	13	work	work	NOUN
cana-1862	109	14	carried	carry	VERB
cana-1862	109	15	out	out	ADP
cana-1862	109	16	to	to	PART
cana-1862	109	17	explore	explore	VERB
cana-1862	109	18	clustering	clustering	ADJ
cana-1862	109	19	algorithms	algorithm	NOUN
cana-1862	109	20	like	like	ADP
cana-1862	109	21	k	k	X
cana-1862	109	22	-	-	PUNCT
cana-1862	109	23	means	means	ADJ
cana-1862	109	24	,	,	PUNCT
cana-1862	109	25	hierarchical	hierarchical	ADJ
cana-1862	109	26	clustering	clustering	NOUN
cana-1862	109	27	and	and	CCONJ
cana-1862	109	28	gaussian	gaussian	ADJ
cana-1862	109	29	mixture	mixture	NOUN
cana-1862	109	30	models	model	NOUN
cana-1862	109	31	(	(	PUNCT
cana-1862	109	32	gmms	gmms	NOUN
cana-1862	109	33	)	)	PUNCT
cana-1862	109	34	for	for	ADP
cana-1862	109	35	detecting	detect	VERB
cana-1862	109	36	anomalies	anomaly	NOUN
cana-1862	109	37	which	which	PRON
cana-1862	109	38	can	can	AUX
cana-1862	109	39	be	be	AUX
cana-1862	109	40	equivalent	equivalent	ADJ
cana-1862	109	41	with	with	ADP
cana-1862	109	42	security	security	NOUN
cana-1862	109	43	threats	threat	NOUN
cana-1862	109	44	.	.	PUNCT
cana-1862	110	1	using	use	VERB
cana-1862	110	2	k	k	NOUN
cana-1862	110	3	-	-	PUNCT
cana-1862	110	4	means	mean	VERB
cana-1862	110	5	the	the	DET
cana-1862	110	6	network	network	NOUN
cana-1862	110	7	traffic	traffic	NOUN
cana-1862	110	8	data	datum	NOUN
cana-1862	110	9	is	be	AUX
cana-1862	110	10	clustered	cluster	VERB
cana-1862	110	11	into	into	ADP
cana-1862	110	12	different	different	ADJ
cana-1862	110	13	groups	group	NOUN
cana-1862	110	14	,	,	PUNCT
cana-1862	110	15	assuming	assume	VERB
cana-1862	110	16	that	that	SCONJ
cana-1862	110	17	normal	normal	ADJ
cana-1862	110	18	case	case	NOUN
cana-1862	110	19	-doses	-dose	NOUN
cana-1862	110	20	regionmakes	regionmake	VERB
cana-1862	110	21	dense	dense	ADJ
cana-1862	110	22	clusters	cluster	NOUN
cana-1862	110	23	while	while	SCONJ
cana-1862	110	24	anomalous	anomalous	ADJ
cana-1862	110	25	cases	case	NOUN
cana-1862	110	26	(	(	PUNCT
cana-1862	110	27	vulnerabilities	vulnerability	NOUN
cana-1862	110	28	)	)	PUNCT
cana-1862	110	29	lies	lie	VERB
cana-1862	110	30	on	on	ADP
cana-1862	110	31	sparse	sparse	ADJ
cana-1862	110	32	regions[16	regions[16	NOUN
cana-1862	110	33	]	]	X
cana-1862	110	34	.	.	PUNCT
cana-1862	111	1	the	the	DET
cana-1862	111	2	clustering	cluster	VERB
cana-1862	111	3	process	process	NOUN
cana-1862	111	4	can	can	AUX
cana-1862	111	5	be	be	AUX
cana-1862	111	6	mathematically	mathematically	ADV
cana-1862	111	7	described	describe	VERB
cana-1862	111	8	as	as	ADP
cana-1862	111	9	follows	follow	VERB
cana-1862	111	10	.	.	PUNCT
cana-1862	112	1	given	give	VERB
cana-1862	112	2	a	a	DET
cana-1862	112	3	dataset	dataset	NOUN
cana-1862	112	4	𝑋	𝑋	NOUN
cana-1862	112	5	=	=	SYM
cana-1862	112	6	{	{	PUNCT
cana-1862	112	7	𝑥1	𝑥1	NOUN
cana-1862	112	8	,	,	PUNCT
cana-1862	112	9	𝑥2	𝑥2	NOUN
cana-1862	112	10	,	,	PUNCT
cana-1862	112	11	…	…	PUNCT
cana-1862	112	12	,	,	PUNCT
cana-1862	112	13	𝑥𝑛	𝑥𝑛	VERB
cana-1862	112	14	}	}	PUNCT
cana-1862	112	15	where	where	SCONJ
cana-1862	112	16	each	each	DET
cana-1862	112	17	𝑥𝑖	𝑥𝑖	PROPN
cana-1862	112	18	is	be	AUX
cana-1862	112	19	a	a	DET
cana-1862	112	20	d	d	ADJ
cana-1862	112	21	-	-	ADJ
cana-1862	112	22	dimensional	dimensional	ADJ
cana-1862	112	23	data	datum	NOUN
cana-1862	112	24	point	point	NOUN
cana-1862	112	25	,	,	PUNCT
cana-1862	112	26	k	k	X
cana-1862	112	27	-	-	PUNCT
cana-1862	112	28	means	means	NOUN
cana-1862	112	29	seeks	seek	VERB
cana-1862	112	30	to	to	PART
cana-1862	112	31	minimize	minimize	VERB
cana-1862	112	32	the	the	DET
cana-1862	112	33	total	total	ADJ
cana-1862	112	34	variance	variance	NOUN
cana-1862	112	35	within	within	ADP
cana-1862	112	36	clusters	cluster	NOUN
cana-1862	112	37	:	:	PUNCT
cana-1862	112	38	communications	communication	NOUN
cana-1862	112	39	on	on	ADP
cana-1862	112	40	applied	apply	VERB
cana-1862	112	41	nonlinear	nonlinear	ADJ
cana-1862	112	42	analysis	analysis	NOUN
cana-1862	112	43	issn	issn	NOUN
cana-1862	112	44	:	:	PUNCT
cana-1862	112	45	1074	1074	NUM
cana-1862	112	46	-	-	PUNCT
cana-1862	112	47	133x	133x	NUM
cana-1862	112	48	vol	vol	NOUN
cana-1862	112	49	32	32	NUM
cana-1862	112	50	no	no	NOUN
cana-1862	112	51	.	.	NOUN
cana-1862	112	52	2	2	NUM
cana-1862	112	53	(	(	PUNCT
cana-1862	112	54	2025	2025	NUM
cana-1862	112	55	)	)	PUNCT
cana-1862	113	1	698	698	NUM
cana-1862	113	2	https://internationalpubls.com	https://internationalpubls.com	X
cana-1862	113	3	𝐽	𝐽	NOUN
cana-1862	113	4	=	=	PUNCT
cana-1862	113	5	∑	∑	PUNCT
cana-1862	113	6	𝐾	𝐾	PROPN
cana-1862	113	7	𝑗=1	𝑗=1	PROPN
cana-1862	113	8	∑	∑	PUNCT
cana-1862	113	9	𝑥𝑖∈𝐶𝑗	𝑥𝑖∈𝐶𝑗	X
cana-1862	113	10	∥	∥	X
cana-1862	113	11	𝑥𝑖	𝑥𝑖	ADP
cana-1862	113	12	−	−	NOUN
cana-1862	113	13	𝜇𝑗	𝜇𝑗	NOUN
cana-1862	113	14	∥2	∥2	PROPN
cana-1862	113	15	,	,	PUNCT
cana-1862	113	16	where	where	SCONJ
cana-1862	113	17	,	,	PUNCT
cana-1862	113	18	𝐾	𝐾	PROPN
cana-1862	113	19	is	be	AUX
cana-1862	113	20	the	the	DET
cana-1862	113	21	number	number	NOUN
cana-1862	113	22	of	of	ADP
cana-1862	113	23	clusters	cluster	NOUN
cana-1862	113	24	,	,	PUNCT
cana-1862	113	25	𝐶𝑗	𝐶𝑗	PROPN
cana-1862	113	26	is	be	AUX
cana-1862	113	27	the	the	DET
cana-1862	113	28	set	set	NOUN
cana-1862	113	29	of	of	ADP
cana-1862	113	30	points	point	NOUN
cana-1862	113	31	in	in	ADP
cana-1862	113	32	cluster	cluster	NOUN
cana-1862	113	33	𝑗	𝑗	NOUN
cana-1862	113	34	,	,	PUNCT
cana-1862	113	35	and	and	CCONJ
cana-1862	113	36	𝜇𝑗	𝜇𝑗	NOUN
cana-1862	113	37	is	be	AUX
cana-1862	113	38	the	the	DET
cana-1862	113	39	mean	mean	NOUN
cana-1862	113	40	of	of	ADP
cana-1862	113	41	points	point	NOUN
cana-1862	113	42	in	in	ADP
cana-1862	113	43	𝐶𝑗.	𝐶𝑗.	NOUN
cana-1862	113	44	this	this	DET
cana-1862	113	45	objective	objective	ADJ
cana-1862	113	46	function	function	NOUN
cana-1862	113	47	𝐽	𝐽	PROPN
cana-1862	113	48	represents	represent	VERB
cana-1862	113	49	the	the	DET
cana-1862	113	50	sum	sum	NOUN
cana-1862	113	51	of	of	ADP
cana-1862	113	52	squared	squared	ADJ
cana-1862	113	53	distances	distance	NOUN
cana-1862	113	54	between	between	ADP
cana-1862	113	55	each	each	DET
cana-1862	113	56	data	data	NOUN
cana-1862	113	57	point	point	NOUN
cana-1862	113	58	and	and	CCONJ
cana-1862	113	59	its	its	PRON
cana-1862	113	60	cluster	cluster	NOUN
cana-1862	113	61	centroid	centroid	NOUN
cana-1862	113	62	,	,	PUNCT
cana-1862	113	63	effectively	effectively	ADV
cana-1862	113	64	separating	separate	VERB
cana-1862	113	65	normal	normal	ADJ
cana-1862	113	66	data	datum	NOUN
cana-1862	113	67	from	from	ADP
cana-1862	113	68	outliers	outlier	NOUN
cana-1862	113	69	.	.	PUNCT
cana-1862	114	1	to	to	PART
cana-1862	114	2	model	model	VERB
cana-1862	114	3	the	the	DET
cana-1862	114	4	network	network	NOUN
cana-1862	114	5	traffic	traffic	NOUN
cana-1862	114	6	as	as	ADP
cana-1862	114	7	a	a	DET
cana-1862	114	8	gaussian	gaussian	ADJ
cana-1862	114	9	mixture	mixture	NOUN
cana-1862	114	10	distribution	distribution	NOUN
cana-1862	114	11	(	(	PUNCT
cana-1862	114	12	gmd	gmd	NOUN
cana-1862	114	13	)	)	PUNCT
cana-1862	114	14	,	,	PUNCT
cana-1862	114	15	we	we	PRON
cana-1862	114	16	focus	focus	VERB
cana-1862	114	17	on	on	ADP
cana-1862	114	18	using	use	VERB
cana-1862	114	19	gaussian	gaussian	ADJ
cana-1862	114	20	mixture	mixture	NOUN
cana-1862	114	21	models	model	NOUN
cana-1862	114	22	(	(	PUNCT
cana-1862	114	23	gmms	gmms	NOUN
cana-1862	114	24	)	)	PUNCT
cana-1862	114	25	.	.	PUNCT
cana-1862	115	1	gmms	gmms	NOUN
cana-1862	115	2	,	,	PUNCT
cana-1862	115	3	through	through	ADP
cana-1862	115	4	the	the	DET
cana-1862	115	5	expectation	expectation	NOUN
cana-1862	115	6	-	-	PUNCT
cana-1862	115	7	maximization	maximization	NOUN
cana-1862	115	8	(	(	PUNCT
cana-1862	115	9	em	em	PRON
cana-1862	115	10	)	)	PUNCT
cana-1862	115	11	algorithm	algorithm	NOUN
cana-1862	115	12	,	,	PUNCT
cana-1862	115	13	are	be	AUX
cana-1862	115	14	capable	capable	ADJ
cana-1862	115	15	of	of	ADP
cana-1862	115	16	iteratively	iteratively	ADV
cana-1862	115	17	finding	find	VERB
cana-1862	115	18	more	more	ADV
cana-1862	115	19	accurate	accurate	ADJ
cana-1862	115	20	parameter	parameter	NOUN
cana-1862	115	21	estimates	estimate	NOUN
cana-1862	115	22	for	for	ADP
cana-1862	115	23	the	the	DET
cana-1862	115	24	underlying	underlie	VERB
cana-1862	115	25	gaussian	gaussian	ADJ
cana-1862	115	26	distributions	distribution	NOUN
cana-1862	115	27	representing	represent	VERB
cana-1862	115	28	regions	region	NOUN
cana-1862	115	29	of	of	ADP
cana-1862	115	30	traffic	traffic	NOUN
cana-1862	115	31	in	in	ADP
cana-1862	115	32	a	a	DET
cana-1862	115	33	network	network	NOUN
cana-1862	115	34	that	that	PRON
cana-1862	115	35	may	may	AUX
cana-1862	115	36	showcase	showcase	VERB
cana-1862	115	37	unusual	unusual	ADJ
cana-1862	115	38	patterns	pattern	NOUN
cana-1862	115	39	hinting	hint	VERB
cana-1862	115	40	at	at	ADP
cana-1862	115	41	vulnerabilities	vulnerability	NOUN
cana-1862	115	42	.	.	PUNCT
cana-1862	116	1	o	o	NOUN
cana-1862	116	2	anomaly	anomaly	NOUN
cana-1862	116	3	detection	detection	NOUN
cana-1862	116	4	using	use	VERB
cana-1862	116	5	autoencoders	autoencoder	NOUN
cana-1862	116	6	an	an	DET
cana-1862	116	7	autoencoder	autoencoder	NOUN
cana-1862	116	8	is	be	AUX
cana-1862	116	9	a	a	DET
cana-1862	116	10	type	type	NOUN
cana-1862	116	11	of	of	ADP
cana-1862	116	12	neural	neural	ADJ
cana-1862	116	13	network	network	NOUN
cana-1862	116	14	used	use	VERB
cana-1862	116	15	in	in	ADP
cana-1862	116	16	unsupervised	unsupervised	ADJ
cana-1862	116	17	learning	learning	NOUN
cana-1862	116	18	with	with	ADP
cana-1862	116	19	high	high	ADJ
cana-1862	116	20	success	success	NOUN
cana-1862	116	21	,	,	PUNCT
cana-1862	116	22	as	as	ADV
cana-1862	116	23	far	far	ADV
cana-1862	116	24	as	as	SCONJ
cana-1862	116	25	cybersecurity	cybersecurity	NOUN
cana-1862	116	26	goes	go	VERB
cana-1862	116	27	.	.	PUNCT
cana-1862	117	1	they	they	PRON
cana-1862	117	2	learn	learn	VERB
cana-1862	117	3	to	to	PART
cana-1862	117	4	reconstruct	reconstruct	VERB
cana-1862	117	5	the	the	DET
cana-1862	117	6	input	input	NOUN
cana-1862	117	7	data	datum	NOUN
cana-1862	117	8	and	and	CCONJ
cana-1862	117	9	then	then	ADV
cana-1862	117	10	measure	measure	VERB
cana-1862	117	11	the	the	DET
cana-1862	117	12	reconstruction	reconstruction	NOUN
cana-1862	117	13	error	error	NOUN
cana-1862	117	14	to	to	PART
cana-1862	117	15	pick	pick	VERB
cana-1862	117	16	up	up	ADP
cana-1862	117	17	on	on	ADP
cana-1862	117	18	anomalies	anomaly	NOUN
cana-1862	117	19	.	.	PUNCT
cana-1862	118	1	to	to	PART
cana-1862	118	2	detect	detect	VERB
cana-1862	118	3	vulnerabilities	vulnerability	NOUN
cana-1862	118	4	,	,	PUNCT
cana-1862	118	5	researchers	researcher	NOUN
cana-1862	118	6	used	use	VERB
cana-1862	118	7	autoencoders	autoencoder	NOUN
cana-1862	118	8	with	with	ADP
cana-1862	118	9	reconstructed	reconstructed	ADJ
cana-1862	118	10	network	network	NOUN
cana-1862	118	11	traffic	traffic	NOUN
cana-1862	118	12	data	datum	NOUN
cana-1862	118	13	so	so	SCONJ
cana-1862	118	14	that	that	SCONJ
cana-1862	118	15	the	the	DET
cana-1862	118	16	normal	normal	ADJ
cana-1862	118	17	traffic	traffic	NOUN
cana-1862	118	18	syndicated	syndicate	VERB
cana-1862	118	19	a	a	DET
cana-1862	118	20	low	low	ADJ
cana-1862	118	21	reconstruction	reconstruction	NOUN
cana-1862	118	22	error	error	NOUN
cana-1862	118	23	and	and	CCONJ
cana-1862	118	24	the	the	DET
cana-1862	118	25	anomalous	anomalous	ADJ
cana-1862	118	26	one	one	NOUN
cana-1862	118	27	(	(	PUNCT
cana-1862	118	28	thus	thus	ADV
cana-1862	118	29	potential	potential	ADJ
cana-1862	118	30	vulnerabilities	vulnerability	NOUN
cana-1862	118	31	)	)	PUNCT
cana-1862	118	32	a	a	DET
cana-1862	118	33	high	high	ADJ
cana-1862	118	34	reconstruction	reconstruction	NOUN
cana-1862	118	35	errors[17	errors[17	PROPN
cana-1862	118	36	]	]	PUNCT
cana-1862	118	37	.	.	PUNCT
cana-1862	119	1	autoencoders	autoencoder	NOUN
cana-1862	119	2	will	will	AUX
cana-1862	119	3	use	use	VERB
cana-1862	119	4	math	math	NOUN
cana-1862	119	5	magic	magic	NOUN
cana-1862	119	6	to	to	PART
cana-1862	119	7	squeeze	squeeze	VERB
cana-1862	119	8	the	the	DET
cana-1862	119	9	data	datum	NOUN
cana-1862	119	10	into	into	ADP
cana-1862	119	11	this	this	DET
cana-1862	119	12	lower	lower	ADV
cana-1862	119	13	-	-	PUNCT
cana-1862	119	14	dimensional	dimensional	ADJ
cana-1862	119	15	latent	latent	NOUN
cana-1862	119	16	space	space	NOUN
cana-1862	119	17	and	and	CCONJ
cana-1862	119	18	then	then	ADV
cana-1862	119	19	re	re	VERB
cana-1862	119	20	-	-	VERB
cana-1862	119	21	expand	expand	VERB
cana-1862	119	22	it	it	PRON
cana-1862	119	23	back	back	ADV
cana-1862	119	24	out	out	ADP
cana-1862	119	25	to	to	ADP
cana-1862	119	26	its	its	PRON
cana-1862	119	27	original	original	ADJ
cana-1862	119	28	number	number	NOUN
cana-1862	119	29	of	of	ADP
cana-1862	119	30	dimensions	dimension	NOUN
cana-1862	119	31	.	.	PUNCT
cana-1862	120	1	in	in	ADP
cana-1862	120	2	mathematical	mathematical	ADJ
cana-1862	120	3	term	term	NOUN
cana-1862	120	4	,	,	PUNCT
cana-1862	120	5	𝐿(𝑥	𝐿(𝑥	PROPN
cana-1862	120	6	,	,	PUNCT
cana-1862	120	7	�	�	PROPN
cana-1862	120	8	̂	̂	NOUN
cana-1862	120	9	�	�	NOUN
cana-1862	120	10	)	)	PUNCT
cana-1862	120	11	=	=	PUNCT
cana-1862	120	12	∑	∑	PUNCT
cana-1862	120	13	𝑛	𝑛	PRON
cana-1862	120	14	𝑖=1	𝑖=1	PROPN
cana-1862	120	15	(	(	PUNCT
cana-1862	120	16	𝑥𝑖	𝑥𝑖	NUM
cana-1862	120	17	−	−	PROPN
cana-1862	120	18	�	�	PROPN
cana-1862	120	19	̂	̂	SYM
cana-1862	120	20	�	�	NOUN
cana-1862	120	21	𝑖)2	𝑖)2	PROPN
cana-1862	120	22	,	,	PUNCT
cana-1862	120	23	where	where	SCONJ
cana-1862	120	24	,	,	PUNCT
cana-1862	120	25	𝑥	𝑥	PROPN
cana-1862	120	26	is	be	AUX
cana-1862	120	27	the	the	DET
cana-1862	120	28	input	input	NOUN
cana-1862	120	29	data	datum	NOUN
cana-1862	120	30	,	,	PUNCT
cana-1862	120	31	�	�	PROPN
cana-1862	120	32	̂	̂	VERB
cana-1862	120	33	�	�	NOUN
cana-1862	120	34	is	be	AUX
cana-1862	120	35	the	the	DET
cana-1862	120	36	reconstructed	reconstructed	ADJ
cana-1862	120	37	data	datum	NOUN
cana-1862	120	38	,	,	PUNCT
cana-1862	120	39	and	and	CCONJ
cana-1862	120	40	𝑛	𝑛	PROPN
cana-1862	120	41	is	be	AUX
cana-1862	120	42	the	the	DET
cana-1862	120	43	number	number	NOUN
cana-1862	120	44	of	of	ADP
cana-1862	120	45	features	feature	NOUN
cana-1862	120	46	.	.	PUNCT
cana-1862	121	1	the	the	DET
cana-1862	121	2	goal	goal	NOUN
cana-1862	121	3	is	be	AUX
cana-1862	121	4	to	to	PART
cana-1862	121	5	minimize	minimize	VERB
cana-1862	121	6	this	this	DET
cana-1862	121	7	loss	loss	NOUN
cana-1862	121	8	function	function	NOUN
cana-1862	121	9	during	during	ADP
cana-1862	121	10	training	training	NOUN
cana-1862	121	11	,	,	PUNCT
cana-1862	121	12	leading	lead	VERB
cana-1862	121	13	to	to	ADP
cana-1862	121	14	the	the	DET
cana-1862	121	15	ability	ability	NOUN
cana-1862	121	16	to	to	PART
cana-1862	121	17	identify	identify	VERB
cana-1862	121	18	anomalies	anomaly	NOUN
cana-1862	121	19	when	when	SCONJ
cana-1862	121	20	reconstruction	reconstruction	NOUN
cana-1862	121	21	errors	error	NOUN
cana-1862	121	22	deviate	deviate	VERB
cana-1862	121	23	significantly	significantly	ADV
cana-1862	121	24	from	from	ADP
cana-1862	121	25	the	the	DET
cana-1862	121	26	norm	norm	NOUN
cana-1862	121	27	.	.	PUNCT
cana-1862	122	1	●	●	PUNCT
cana-1862	122	2	vulnerability	vulnerability	NOUN
cana-1862	122	3	detection	detection	NOUN
cana-1862	122	4	with	with	ADP
cana-1862	122	5	probabilistic	probabilistic	ADJ
cana-1862	122	6	modelling	model	VERB
cana-1862	122	7	one	one	NUM
cana-1862	122	8	popular	popular	ADJ
cana-1862	122	9	class	class	NOUN
cana-1862	122	10	of	of	ADP
cana-1862	122	11	models	model	NOUN
cana-1862	122	12	in	in	ADP
cana-1862	122	13	the	the	DET
cana-1862	122	14	vulnerability	vulnerability	NOUN
cana-1862	122	15	detection	detection	NOUN
cana-1862	122	16	is	be	AUX
cana-1862	122	17	probabilistic	probabilistic	ADJ
cana-1862	122	18	models	model	NOUN
cana-1862	122	19	such	such	ADJ
cana-1862	122	20	as	as	ADP
cana-1862	122	21	bayesian	bayesian	NOUN
cana-1862	122	22	networks	network	NOUN
cana-1862	122	23	,	,	PUNCT
cana-1862	122	24	hidden	hide	VERB
cana-1862	122	25	markov	markov	NOUN
cana-1862	122	26	models	model	NOUN
cana-1862	122	27	(	(	PUNCT
cana-1862	122	28	hmms	hmms	NOUN
cana-1862	122	29	)	)	PUNCT
cana-1862	122	30	,	,	PUNCT
cana-1862	122	31	which	which	PRON
cana-1862	122	32	are	be	AUX
cana-1862	122	33	particularly	particularly	ADV
cana-1862	122	34	well	well	ADV
cana-1862	122	35	-	-	PUNCT
cana-1862	122	36	suited	suited	ADJ
cana-1862	122	37	to	to	ADP
cana-1862	122	38	modelling	model	VERB
cana-1862	122	39	uncertainty	uncertainty	NOUN
cana-1862	122	40	in	in	ADP
cana-1862	122	41	security	security	NOUN
cana-1862	122	42	data[18	data[18	PROPN
cana-1862	122	43	]	]	PUNCT
cana-1862	122	44	.	.	PUNCT
cana-1862	123	1	o	o	NOUN
cana-1862	123	2	dependency	dependency	NOUN
cana-1862	123	3	modelling	modelling	NOUN
cana-1862	123	4	using	use	VERB
cana-1862	123	5	bayesian	bayesian	NOUN
cana-1862	123	6	networks	network	NOUN
cana-1862	123	7	example	example	VERB
cana-1862	123	8	:	:	PUNCT
cana-1862	123	9	bayesian	bayesian	NOUN
cana-1862	123	10	networks	network	NOUN
cana-1862	123	11	to	to	PART
cana-1862	123	12	represent	represent	VERB
cana-1862	123	13	interdependencies	interdependency	NOUN
cana-1862	123	14	of	of	ADP
cana-1862	123	15	security	security	NOUN
cana-1862	123	16	features	feature	VERB
cana-1862	123	17	infrastructures	infrastructure	NOUN
cana-1862	123	18	for	for	ADP
cana-1862	123	19	cybersecurity6	cybersecurity6	NOUN
cana-1862	123	20	can	can	AUX
cana-1862	123	21	help	help	VERB
cana-1862	123	22	model	model	VERB
cana-1862	123	23	the	the	DET
cana-1862	123	24	interdependency	interdependency	NOUN
cana-1862	123	25	between	between	ADP
cana-1862	123	26	different	different	ADJ
cana-1862	123	27	security	security	NOUN
cana-1862	123	28	features	feature	NOUN
cana-1862	123	29	and	and	CCONJ
cana-1862	123	30	their	their	PRON
cana-1862	123	31	impact	impact	NOUN
cana-1862	123	32	on	on	ADP
cana-1862	123	33	vulnerabilities	vulnerability	NOUN
cana-1862	123	34	in	in	ADP
cana-1862	123	35	e.g.	e.g.	ADV
cana-1862	123	36	,	,	PUNCT
cana-1862	123	37	network	network	NOUN
cana-1862	123	38	traffic	traffic	NOUN
cana-1862	123	39	patterns	pattern	NOUN
cana-1862	123	40	,	,	PUNCT
cana-1862	123	41	user	user	NOUN
cana-1862	123	42	activities	activity	NOUN
cana-1862	123	43	etc	etc	X
cana-1862	123	44	.	.	X
cana-1862	124	1	a	a	DET
cana-1862	124	2	model	model	NOUN
cana-1862	124	3	of	of	ADP
cana-1862	124	4	bayesian	bayesian	NOUN
cana-1862	124	5	network	network	NOUN
cana-1862	124	6	for	for	ADP
cana-1862	124	7	predicting	predict	VERB
cana-1862	124	8	software	software	NOUN
cana-1862	124	9	’s	’s	PART
cana-1862	124	10	vulnerable	vulnerable	ADJ
cana-1862	124	11	-	-	ADJ
cana-1862	124	12	ness	ness	ADV
cana-1862	124	13	supported	support	VERB
cana-1862	124	14	on	on	ADP
cana-1862	124	15	historical	historical	ADJ
cana-1862	124	16	vulnerability	vulnerability	NOUN
cana-1862	124	17	data	datum	NOUN
cana-1862	124	18	and	and	CCONJ
cana-1862	124	19	software	software	NOUN
cana-1862	124	20	metrics	metric	NOUN
cana-1862	124	21	.	.	PUNCT
cana-1862	125	1	a	a	DET
cana-1862	125	2	bayesian	bayesian	NOUN
cana-1862	125	3	network	network	NOUN
cana-1862	125	4	is	be	AUX
cana-1862	125	5	defined	define	VERB
cana-1862	125	6	mathematically	mathematically	ADV
cana-1862	125	7	using	use	VERB
cana-1862	125	8	the	the	DET
cana-1862	125	9	conditional	conditional	ADJ
cana-1862	125	10	probability	probability	NOUN
cana-1862	125	11	distributions	distribution	NOUN
cana-1862	125	12	for	for	ADP
cana-1862	125	13	every	every	DET
cana-1862	125	14	node	node	NOUN
cana-1862	125	15	in	in	ADP
cana-1862	125	16	the	the	DET
cana-1862	125	17	network	network	NOUN
cana-1862	125	18	for	for	ADP
cana-1862	125	19	set	set	VERB
cana-1862	125	20	𝑋	𝑋	NOUN
cana-1862	125	21	=	=	SYM
cana-1862	125	22	{	{	PUNCT
cana-1862	125	23	𝑋1	𝑋1	PROPN
cana-1862	125	24	,	,	PUNCT
cana-1862	125	25	𝑋2	𝑋2	VERB
cana-1862	125	26	,	,	PUNCT
cana-1862	125	27	…	…	PUNCT
cana-1862	125	28	,	,	PUNCT
cana-1862	125	29	𝑋𝑛	𝑋𝑛	NOUN
cana-1862	125	30	}	}	PUNCT
cana-1862	125	31	,	,	PUNCT
cana-1862	125	32	communications	communication	NOUN
cana-1862	125	33	on	on	ADP
cana-1862	125	34	applied	apply	VERB
cana-1862	125	35	nonlinear	nonlinear	ADJ
cana-1862	125	36	analysis	analysis	NOUN
cana-1862	125	37	issn	issn	NOUN
cana-1862	125	38	:	:	PUNCT
cana-1862	125	39	1074	1074	NUM
cana-1862	125	40	-	-	PUNCT
cana-1862	125	41	133x	133x	NUM
cana-1862	125	42	vol	vol	NOUN
cana-1862	125	43	32	32	NUM
cana-1862	125	44	no	no	NOUN
cana-1862	125	45	.	.	NOUN
cana-1862	125	46	2	2	NUM
cana-1862	125	47	(	(	PUNCT
cana-1862	125	48	2025	2025	NUM
cana-1862	125	49	)	)	PUNCT
cana-1862	125	50	699	699	NUM
cana-1862	125	51	https://internationalpubls.com	https://internationalpubls.com	X
cana-1862	125	52	𝑃(𝑋	𝑃(𝑋	PROPN
cana-1862	125	53	)	)	PUNCT
cana-1862	125	54	=	=	SYM
cana-1862	125	55	∏	∏	PROPN
cana-1862	125	56	𝑛	𝑛	PRON
cana-1862	125	57	𝑖=1	𝑖=1	PROPN
cana-1862	125	58	𝑃(𝑋𝑖	𝑃(𝑋𝑖	PROPN
cana-1862	125	59	∣	∣	ADJ
cana-1862	125	60	𝑃𝑎𝑟𝑒𝑛𝑡𝑠(𝑋𝑖	𝑃𝑎𝑟𝑒𝑛𝑡𝑠(𝑋𝑖	NUM
cana-1862	125	61	)	)	PUNCT
cana-1862	125	62	)	)	PUNCT
cana-1862	125	63	,	,	PUNCT
cana-1862	125	64	o	o	NOUN
cana-1862	125	65	modelling	modelling	NOUN
cana-1862	125	66	for	for	ADP
cana-1862	125	67	temporal	temporal	ADJ
cana-1862	125	68	analysis	analysis	NOUN
cana-1862	125	69	using	use	VERB
cana-1862	125	70	hidden	hide	VERB
cana-1862	125	71	markov	markov	NOUN
cana-1862	125	72	models	model	NOUN
cana-1862	125	73	hidden	hide	VERB
cana-1862	125	74	markov	markov	NOUN
cana-1862	125	75	models	model	NOUN
cana-1862	125	76	(	(	PUNCT
cana-1862	125	77	hmms	hmms	NOUN
cana-1862	125	78	)	)	PUNCT
cana-1862	125	79	have	have	AUX
cana-1862	125	80	been	be	AUX
cana-1862	125	81	used	use	VERB
cana-1862	125	82	to	to	PART
cana-1862	125	83	get	get	VERB
cana-1862	125	84	a	a	DET
cana-1862	125	85	model	model	NOUN
cana-1862	125	86	for	for	ADP
cana-1862	125	87	describing	describe	VERB
cana-1862	125	88	time	time	NOUN
cana-1862	125	89	-	-	PUNCT
cana-1862	125	90	evolving	evolve	VERB
cana-1862	125	91	vulnerabilities	vulnerability	NOUN
cana-1862	125	92	so	so	SCONJ
cana-1862	125	93	that	that	SCONJ
cana-1862	125	94	they	they	PRON
cana-1862	125	95	can	can	AUX
cana-1862	125	96	adjust	adjust	VERB
cana-1862	125	97	in	in	ADP
cana-1862	125	98	real	real	ADJ
cana-1862	125	99	-	-	PUNCT
cana-1862	125	100	time	time	NOUN
cana-1862	125	101	with	with	ADP
cana-1862	125	102	behaviours	behaviour	NOUN
cana-1862	125	103	of	of	ADP
cana-1862	125	104	hidden	hidden	ADJ
cana-1862	125	105	states	state	NOUN
cana-1862	125	106	.	.	PUNCT
cana-1862	126	1	modelled	model	VERB
cana-1862	126	2	network	network	NOUN
cana-1862	126	3	states	state	NOUN
cana-1862	126	4	and	and	CCONJ
cana-1862	126	5	detected	detect	VERB
cana-1862	126	6	transitions	transition	NOUN
cana-1862	126	7	that	that	PRON
cana-1862	126	8	are	be	AUX
cana-1862	126	9	symptoms	symptom	NOUN
cana-1862	126	10	of	of	ADP
cana-1862	126	11	security	security	NOUN
cana-1862	126	12	breach	breach	NOUN
cana-1862	126	13	using	use	VERB
cana-1862	126	14	hmms[19	hmms[19	NOUN
cana-1862	126	15	]	]	PUNCT
cana-1862	126	16	.	.	PUNCT
cana-1862	127	1	using	use	VERB
cana-1862	127	2	the	the	DET
cana-1862	127	3	baumwelch	baumwelch	NOUN
cana-1862	127	4	algorithm	algorithm	NOUN
cana-1862	127	5	,	,	PUNCT
cana-1862	127	6	they	they	PRON
cana-1862	127	7	were	be	AUX
cana-1862	127	8	also	also	ADV
cana-1862	127	9	able	able	ADJ
cana-1862	127	10	to	to	PART
cana-1862	127	11	find	find	VERB
cana-1862	127	12	parameters	parameter	NOUN
cana-1862	127	13	of	of	ADP
cana-1862	127	14	hmms	hmms	NOUN
cana-1862	127	15	for	for	ADP
cana-1862	127	16	sequences	sequence	NOUN
cana-1862	127	17	of	of	ADP
cana-1862	127	18	events	event	NOUN
cana-1862	127	19	corresponding	correspond	VERB
cana-1862	127	20	to	to	ADP
cana-1862	127	21	possible	possible	ADJ
cana-1862	127	22	exploitation	exploitation	NOUN
cana-1862	127	23	.	.	PUNCT
cana-1862	128	1	hmms	hmms	NOUN
cana-1862	128	2	is	be	AUX
cana-1862	128	3	a	a	DET
cana-1862	128	4	mathematical	mathematical	ADJ
cana-1862	128	5	framework	framework	NOUN
cana-1862	128	6	that	that	PRON
cana-1862	128	7	uses	use	VERB
cana-1862	128	8	hidden	hidden	ADJ
cana-1862	128	9	states	state	NOUN
cana-1862	128	10	to	to	PART
cana-1862	128	11	represent	represent	VERB
cana-1862	128	12	dynamic	dynamic	ADJ
cana-1862	128	13	systems	system	NOUN
cana-1862	128	14	,	,	PUNCT
cana-1862	128	15	where	where	SCONJ
cana-1862	128	16	the	the	DET
cana-1862	128	17	observations	observation	NOUN
cana-1862	128	18	are	be	AUX
cana-1862	128	19	assumed	assume	VERB
cana-1862	128	20	to	to	PART
cana-1862	128	21	be	be	AUX
cana-1862	128	22	probabilistic	probabilistic	ADJ
cana-1862	128	23	given	give	VERB
cana-1862	128	24	those	those	DET
cana-1862	128	25	hidden	hide	VERB
cana-1862	128	26	states	state	NOUN
cana-1862	128	27	.	.	PUNCT
cana-1862	129	1	the	the	DET
cana-1862	129	2	model	model	NOUN
cana-1862	129	3	’s	’s	PART
cana-1862	129	4	parameters	parameter	NOUN
cana-1862	129	5	can	can	AUX
cana-1862	129	6	be	be	AUX
cana-1862	129	7	learned	learn	VERB
cana-1862	129	8	from	from	ADP
cana-1862	129	9	historical	historical	ADJ
cana-1862	129	10	data	datum	NOUN
cana-1862	129	11	(	(	PUNCT
cana-1862	129	12	to	to	PART
cana-1862	129	13	capture	capture	VERB
cana-1862	129	14	relationships	relationship	NOUN
cana-1862	129	15	among	among	ADP
cana-1862	129	16	states	state	NOUN
cana-1862	129	17	-	-	PUNCT
cana-1862	129	18	transition	transition	NOUN
cana-1862	129	19	probabilities	probability	NOUN
cana-1862	129	20	and	and	CCONJ
cana-1862	129	21	emission	emission	NOUN
cana-1862	129	22	probabilities	probability	NOUN
cana-1862	129	23	)	)	PUNCT
cana-1862	129	24	enabling	enable	VERB
cana-1862	129	25	the	the	DET
cana-1862	129	26	vulnerability	vulnerability	NOUN
cana-1862	129	27	detection	detection	NOUN
cana-1862	129	28	mechanism	mechanism	NOUN
cana-1862	129	29	in	in	ADP
cana-1862	129	30	real	real	ADJ
cana-1862	129	31	-	-	PUNCT
cana-1862	129	32	time	time	NOUN
cana-1862	129	33	.	.	PUNCT
cana-1862	130	1	●	●	PUNCT
cana-1862	130	2	hybrid	hybrid	NOUN
cana-1862	130	3	models	model	NOUN
cana-1862	130	4	and	and	CCONJ
cana-1862	130	5	ensemble	ensemble	ADJ
cana-1862	130	6	techniques	technique	NOUN
cana-1862	130	7	:	:	PUNCT
cana-1862	130	8	studies	study	NOUN
cana-1862	130	9	have	have	AUX
cana-1862	130	10	shown	show	VERB
cana-1862	130	11	that	that	SCONJ
cana-1862	130	12	using	use	VERB
cana-1862	130	13	ensemble	ensemble	ADJ
cana-1862	130	14	methods	method	NOUN
cana-1862	130	15	combining	combine	VERB
cana-1862	130	16	multiple	multiple	ADJ
cana-1862	130	17	machine	machine	NOUN
cana-1862	130	18	learning	learning	NOUN
cana-1862	130	19	models	model	NOUN
cana-1862	130	20	can	can	AUX
cana-1862	130	21	increase	increase	VERB
cana-1862	130	22	the	the	DET
cana-1862	130	23	reliability	reliability	NOUN
cana-1862	130	24	of	of	ADP
cana-1862	130	25	detection	detection	NOUN
cana-1862	130	26	systems	system	NOUN
cana-1862	130	27	with	with	ADP
cana-1862	130	28	respect	respect	NOUN
cana-1862	130	29	to	to	ADP
cana-1862	130	30	vulnerabilities	vulnerability	NOUN
cana-1862	130	31	.	.	PUNCT
cana-1862	131	1	here	here	ADV
cana-1862	131	2	,	,	PUNCT
cana-1862	131	3	ensemble	ensemble	ADJ
cana-1862	131	4	learning	learning	NOUN
cana-1862	131	5	techniques	technique	NOUN
cana-1862	131	6	like	like	ADP
cana-1862	131	7	boosting	boost	VERB
cana-1862	131	8	,	,	PUNCT
cana-1862	131	9	bagging	bagging	NOUN
cana-1862	131	10	&	&	CCONJ
cana-1862	131	11	stacking	stacking	NOUN
cana-1862	131	12	are	be	AUX
cana-1862	131	13	used	use	VERB
cana-1862	131	14	to	to	PART
cana-1862	131	15	generate	generate	VERB
cana-1862	131	16	predictions	prediction	NOUN
cana-1862	131	17	from	from	ADP
cana-1862	131	18	multiple	multiple	ADJ
cana-1862	131	19	models	model	NOUN
cana-1862	131	20	for	for	ADP
cana-1862	131	21	improved	improved	ADJ
cana-1862	131	22	accuracy	accuracy	NOUN
cana-1862	131	23	and	and	CCONJ
cana-1862	131	24	lesser	less	ADJ
cana-1862	131	25	false	false	ADJ
cana-1862	131	26	positives	positive	NOUN
cana-1862	131	27	.	.	PUNCT
cana-1862	132	1	o	o	X
cana-1862	132	2	boosting	boost	VERB
cana-1862	132	3	algorithms	algorithm	NOUN
cana-1862	132	4	–	–	PUNCT
cana-1862	132	5	xgboost	xgboost	X
cana-1862	132	6	xgboost	xgboost	X
cana-1862	132	7	is	be	AUX
cana-1862	132	8	an	an	DET
cana-1862	132	9	implementation	implementation	NOUN
cana-1862	132	10	of	of	ADP
cana-1862	132	11	gradient	gradient	NOUN
cana-1862	132	12	-	-	PUNCT
cana-1862	132	13	boosted	boost	VERB
cana-1862	132	14	decision	decision	NOUN
cana-1862	132	15	trees	tree	NOUN
cana-1862	132	16	which	which	PRON
cana-1862	132	17	has	have	AUX
cana-1862	132	18	been	be	AUX
cana-1862	132	19	successfully	successfully	ADV
cana-1862	132	20	used	use	VERB
cana-1862	132	21	in	in	ADP
cana-1862	132	22	cybersecurity	cybersecurity	NOUN
cana-1862	132	23	due	due	ADP
cana-1862	132	24	to	to	ADP
cana-1862	132	25	the	the	DET
cana-1862	132	26	high	high	ADJ
cana-1862	132	27	performance	performance	NOUN
cana-1862	132	28	and	and	CCONJ
cana-1862	132	29	precise	precise	ADJ
cana-1862	132	30	detection[20	detection[20	NOUN
cana-1862	132	31	]	]	PUNCT
cana-1862	132	32	.	.	PUNCT
cana-1862	133	1	vulnerability	vulnerability	NOUN
cana-1862	133	2	identification	identification	NOUN
cana-1862	133	3	through	through	ADP
cana-1862	133	4	classification	classification	NOUN
cana-1862	133	5	network	network	NOUN
cana-1862	133	6	traffic	traffic	NOUN
cana-1862	133	7	and	and	CCONJ
cana-1862	133	8	application	application	NOUN
cana-1862	133	9	of	of	ADP
cana-1862	133	10	xgboost	xgboost	ADV
cana-1862	133	11	iteratively	iteratively	ADV
cana-1862	133	12	constructs	construct	VERB
cana-1862	133	13	trees	tree	NOUN
cana-1862	133	14	to	to	PART
cana-1862	133	15	correct	correct	VERB
cana-1862	133	16	the	the	DET
cana-1862	133	17	errors	error	NOUN
cana-1862	133	18	of	of	ADP
cana-1862	133	19	prior	prior	ADJ
cana-1862	133	20	trees	tree	NOUN
cana-1862	133	21	,	,	PUNCT
cana-1862	133	22	making	make	VERB
cana-1862	133	23	it	it	PRON
cana-1862	133	24	suitable	suitable	ADJ
cana-1862	133	25	to	to	PART
cana-1862	133	26	learn	learn	VERB
cana-1862	133	27	from	from	ADP
cana-1862	133	28	diverse	diverse	ADJ
cana-1862	133	29	patterns	pattern	NOUN
cana-1862	133	30	present	present	ADJ
cana-1862	133	31	in	in	ADP
cana-1862	133	32	security	security	NOUN
cana-1862	133	33	data	datum	NOUN
cana-1862	133	34	.	.	PUNCT
cana-1862	134	1	it	it	PRON
cana-1862	134	2	is	be	AUX
cana-1862	134	3	the	the	DET
cana-1862	134	4	same	same	ADJ
cana-1862	134	5	reason	reason	NOUN
cana-1862	134	6	why	why	SCONJ
cana-1862	134	7	xgboost	xgboost	PROPN
cana-1862	134	8	's	's	PART
cana-1862	134	9	objective	objective	ADJ
cana-1862	134	10	function	function	NOUN
cana-1862	134	11	can	can	AUX
cana-1862	134	12	be	be	AUX
cana-1862	134	13	written	write	VERB
cana-1862	134	14	as	as	ADP
cana-1862	134	15	:	:	PUNCT
cana-1862	134	16	𝐿(𝜃	𝐿(𝜃	X
cana-1862	134	17	)	)	PUNCT
cana-1862	134	18	=	=	SYM
cana-1862	134	19	∑	∑	PUNCT
cana-1862	134	20	𝑛	𝑛	PRON
cana-1862	134	21	𝑖=1	𝑖=1	PROPN
cana-1862	134	22	𝑙(𝑦𝑖	𝑙(𝑦𝑖	PROPN
cana-1862	134	23	,	,	PUNCT
cana-1862	134	24	�	�	PROPN
cana-1862	134	25	̂	̂	NOUN
cana-1862	134	26	�	�	NOUN
cana-1862	134	27	𝑖	𝑖	NUM
cana-1862	134	28	)	)	PUNCT
cana-1862	134	29	+	+	CCONJ
cana-1862	134	30	∑	∑	PROPN
cana-1862	134	31	𝐾	𝐾	PROPN
cana-1862	134	32	𝑘=1	𝑘=1	PUNCT
cana-1862	134	33	𝛺(𝑓𝑘	𝛺(𝑓𝑘	PROPN
cana-1862	134	34	)	)	PUNCT
cana-1862	134	35	,	,	PUNCT
cana-1862	134	36	where	where	SCONJ
cana-1862	134	37	,	,	PUNCT
cana-1862	134	38	𝑙(𝑦𝑖	𝑙(𝑦𝑖	PRON
cana-1862	134	39	,	,	PUNCT
cana-1862	134	40	�	�	PROPN
cana-1862	134	41	̂	̂	VERB
cana-1862	134	42	�	�	NOUN
cana-1862	134	43	𝑖	𝑖	NUM
cana-1862	134	44	)	)	PUNCT
cana-1862	134	45	is	be	AUX
cana-1862	134	46	a	a	DET
cana-1862	134	47	loss	loss	NOUN
cana-1862	134	48	function	function	NOUN
cana-1862	134	49	(	(	PUNCT
cana-1862	134	50	e.g.	e.g.	ADV
cana-1862	134	51	,	,	PUNCT
cana-1862	134	52	squared	square	VERB
cana-1862	134	53	error	error	NOUN
cana-1862	134	54	)	)	PUNCT
cana-1862	134	55	measuring	measure	VERB
cana-1862	134	56	the	the	DET
cana-1862	134	57	difference	difference	NOUN
cana-1862	134	58	between	between	ADP
cana-1862	134	59	the	the	DET
cana-1862	134	60	predicted	predict	VERB
cana-1862	134	61	�	�	PROPN
cana-1862	134	62	̂	̂	NOUN
cana-1862	134	63	�	�	NOUN
cana-1862	134	64	𝑖	𝑖	NOUN
cana-1862	134	65	and	and	CCONJ
cana-1862	134	66	the	the	DET
cana-1862	134	67	actual	actual	ADJ
cana-1862	134	68	𝑦𝑖	𝑦𝑖	NOUN
cana-1862	134	69	,	,	PUNCT
cana-1862	134	70	and	and	CCONJ
cana-1862	134	71	𝛺(𝑓𝑘	𝛺(𝑓𝑘	X
cana-1862	134	72	)	)	PUNCT
cana-1862	134	73	is	be	AUX
cana-1862	134	74	a	a	DET
cana-1862	134	75	regularization	regularization	NOUN
cana-1862	134	76	term	term	NOUN
cana-1862	134	77	that	that	PRON
cana-1862	134	78	controls	control	VERB
cana-1862	134	79	the	the	DET
cana-1862	134	80	complexity	complexity	NOUN
cana-1862	134	81	of	of	ADP
cana-1862	134	82	the	the	DET
cana-1862	134	83	model	model	NOUN
cana-1862	134	84	.	.	PUNCT
cana-1862	135	1	this	this	DET
cana-1862	135	2	combination	combination	NOUN
cana-1862	135	3	of	of	ADP
cana-1862	135	4	mathematical	mathematical	ADJ
cana-1862	135	5	optimization	optimization	NOUN
cana-1862	135	6	and	and	CCONJ
cana-1862	135	7	model	model	NOUN
cana-1862	135	8	regularization	regularization	NOUN
cana-1862	135	9	enables	enable	VERB
cana-1862	135	10	xgboost	xgboost	ADV
cana-1862	135	11	to	to	PART
cana-1862	135	12	achieve	achieve	VERB
cana-1862	135	13	high	high	ADJ
cana-1862	135	14	performance	performance	NOUN
cana-1862	135	15	in	in	ADP
cana-1862	135	16	vulnerability	vulnerability	NOUN
cana-1862	135	17	detection	detection	NOUN
cana-1862	135	18	tasks[21	tasks[21	PROPN
cana-1862	135	19	-	-	PUNCT
cana-1862	135	20	25	25	NUM
cana-1862	135	21	]	]	PUNCT
cana-1862	135	22	.	.	PUNCT
cana-1862	136	1	o	o	PROPN
cana-1862	136	2	probabilistic	probabilistic	ADJ
cana-1862	136	3	and	and	CCONJ
cana-1862	136	4	deep	deep	ADJ
cana-1862	136	5	learning	learn	VERB
cana-1862	136	6	hybrid	hybrid	NOUN
cana-1862	136	7	models	model	NOUN
cana-1862	136	8	hybrid	hybrid	ADJ
cana-1862	136	9	approaches	approach	NOUN
cana-1862	136	10	that	that	PRON
cana-1862	136	11	combine	combine	VERB
cana-1862	136	12	probabilistic	probabilistic	ADJ
cana-1862	136	13	models	model	NOUN
cana-1862	136	14	with	with	ADP
cana-1862	136	15	deep	deep	ADJ
cana-1862	136	16	learning	learning	NOUN
cana-1862	136	17	have	have	AUX
cana-1862	136	18	been	be	AUX
cana-1862	136	19	proposed	propose	VERB
cana-1862	136	20	to	to	PART
cana-1862	136	21	overcome	overcome	VERB
cana-1862	136	22	these	these	DET
cana-1862	136	23	limitations	limitation	NOUN
cana-1862	136	24	of	of	ADP
cana-1862	136	25	individual	individual	ADJ
cana-1862	136	26	model	model	NOUN
cana-1862	136	27	types	type	NOUN
cana-1862	136	28	.	.	PUNCT
cana-1862	137	1	the	the	DET
cana-1862	137	2	model	model	NOUN
cana-1862	137	3	itself	itself	PRON
cana-1862	137	4	combines	combine	VERB
cana-1862	137	5	the	the	DET
cana-1862	137	6	best	good	ADJ
cana-1862	137	7	parts	part	NOUN
cana-1862	137	8	of	of	ADP
cana-1862	137	9	a	a	DET
cana-1862	137	10	vae	vae	NOUN
cana-1862	137	11	with	with	ADP
cana-1862	137	12	bayesian	bayesian	NOUN
cana-1862	137	13	networks	network	NOUN
cana-1862	137	14	.	.	PUNCT
cana-1862	138	1	inference	inference	NOUN
cana-1862	138	2	:	:	PUNCT
cana-1862	138	3	both	both	CCONJ
cana-1862	138	4	the	the	DET
cana-1862	138	5	vae	vae	PROPN
cana-1862	138	6	compresses	compress	VERB
cana-1862	138	7	input	input	NOUN
cana-1862	138	8	data	datum	NOUN
cana-1862	138	9	into	into	ADP
cana-1862	138	10	a	a	DET
cana-1862	138	11	latent	latent	NOUN
cana-1862	138	12	space	space	NOUN
cana-1862	138	13	which	which	PRON
cana-1862	138	14	captures	capture	VERB
cana-1862	138	15	salient	salient	NOUN
cana-1862	138	16	features	feature	NOUN
cana-1862	138	17	,	,	PUNCT
cana-1862	138	18	and	and	CCONJ
cana-1862	138	19	the	the	DET
cana-1862	138	20	bayesian	bayesian	NOUN
cana-1862	138	21	network	network	NOUN
cana-1862	138	22	captures	capture	VERB
cana-1862	138	23	possible	possible	ADJ
cana-1862	138	24	probabilistic	probabilistic	ADJ
cana-1862	138	25	dependencies	dependency	NOUN
cana-1862	138	26	among	among	ADP
cana-1862	138	27	these	these	DET
cana-1862	138	28	features	feature	NOUN
cana-1862	138	29	to	to	PART
cana-1862	138	30	predict	predict	VERB
cana-1862	138	31	vulnerabilities	vulnerability	NOUN
cana-1862	138	32	.	.	PUNCT
cana-1862	139	1	performing	perform	VERB
cana-1862	139	2	these	these	DET
cana-1862	139	3	operations	operation	NOUN
cana-1862	139	4	in	in	ADP
cana-1862	139	5	communications	communication	NOUN
cana-1862	139	6	on	on	ADP
cana-1862	139	7	applied	apply	VERB
cana-1862	139	8	nonlinear	nonlinear	ADJ
cana-1862	139	9	analysis	analysis	NOUN
cana-1862	139	10	issn	issn	AUX
cana-1862	139	11	:	:	PUNCT
cana-1862	139	12	1074	1074	NUM
cana-1862	139	13	-	-	PUNCT
cana-1862	139	14	133x	133x	NUM
cana-1862	139	15	vol	vol	NOUN
cana-1862	139	16	32	32	NUM
cana-1862	139	17	no	no	NOUN
cana-1862	139	18	.	.	NOUN
cana-1862	139	19	2	2	NUM
cana-1862	139	20	(	(	PUNCT
cana-1862	139	21	2025	2025	NUM
cana-1862	139	22	)	)	PUNCT
cana-1862	139	23	700	700	NUM
cana-1862	139	24	https://internationalpubls.com	https://internationalpubls.com	X
cana-1862	139	25	combination	combination	NOUN
cana-1862	139	26	utilizes	utilize	VERB
cana-1862	139	27	the	the	DET
cana-1862	139	28	forces	force	NOUN
cana-1862	139	29	of	of	ADP
cana-1862	139	30	deep	deep	ADJ
cana-1862	139	31	learning	learning	NOUN
cana-1862	139	32	in	in	ADP
cana-1862	139	33	feature	feature	NOUN
cana-1862	139	34	extraction	extraction	NOUN
cana-1862	139	35	,	,	PUNCT
cana-1862	139	36	together	together	ADV
cana-1862	139	37	with	with	ADP
cana-1862	139	38	probabilistic	probabilistic	ADJ
cana-1862	139	39	models	model	NOUN
cana-1862	139	40	for	for	ADP
cana-1862	139	41	uncertainty	uncertainty	NOUN
cana-1862	139	42	management	management	NOUN
cana-1862	139	43	,	,	PUNCT
cana-1862	139	44	boosting	boost	VERB
cana-1862	139	45	vulnerability	vulnerability	NOUN
cana-1862	139	46	detection	detection	NOUN
cana-1862	139	47	performance	performance	NOUN
cana-1862	139	48	accordingly	accordingly	ADV
cana-1862	139	49	.	.	PUNCT
cana-1862	140	1	●	●	PUNCT
cana-1862	140	2	dynamic	dynamic	ADJ
cana-1862	140	3	vulnerability	vulnerability	NOUN
cana-1862	140	4	management	management	NOUN
cana-1862	140	5	with	with	ADP
cana-1862	140	6	reinforcement	reinforcement	NOUN
cana-1862	140	7	learning	learning	NOUN
cana-1862	140	8	in	in	ADP
cana-1862	140	9	iot	iot	NOUN
cana-1862	140	10	,	,	PUNCT
cana-1862	140	11	cybersecurity	cybersecurity	NOUN
cana-1862	140	12	,	,	PUNCT
cana-1862	140	13	a	a	DET
cana-1862	140	14	specific	specific	ADJ
cana-1862	140	15	combination	combination	NOUN
cana-1862	140	16	of	of	ADP
cana-1862	140	17	supervised	supervised	ADJ
cana-1862	140	18	and	and	CCONJ
cana-1862	140	19	reinforcement	reinforcement	NOUN
cana-1862	140	20	learning	learning	NOUN
cana-1862	140	21	(	(	PUNCT
cana-1862	140	22	rl	rl	NOUN
cana-1862	140	23	)	)	PUNCT
cana-1862	140	24	approaches	approach	NOUN
cana-1862	140	25	that	that	PRON
cana-1862	140	26	allow	allow	VERB
cana-1862	140	27	real	real	ADJ
cana-1862	140	28	-	-	PUNCT
cana-1862	140	29	time	time	NOUN
cana-1862	140	30	event	event	NOUN
cana-1862	140	31	based	base	VERB
cana-1862	140	32	vulnerable	vulnerable	ADJ
cana-1862	140	33	member	member	NOUN
cana-1862	140	34	detection	detection	NOUN
cana-1862	140	35	and	and	CCONJ
cana-1862	140	36	adaptable	adaptable	ADJ
cana-1862	140	37	structure	structure	NOUN
cana-1862	140	38	has	have	AUX
cana-1862	140	39	been	be	AUX
cana-1862	140	40	employed	employ	VERB
cana-1862	140	41	.	.	PUNCT
cana-1862	141	1	for	for	ADP
cana-1862	141	2	this	this	DET
cana-1862	141	3	reason	reason	NOUN
cana-1862	141	4	,	,	PUNCT
cana-1862	141	5	in	in	ADP
cana-1862	141	6	recent	recent	ADJ
cana-1862	141	7	years	year	NOUN
cana-1862	141	8	,	,	PUNCT
cana-1862	141	9	rl	rl	X
cana-1862	141	10	models	model	NOUN
cana-1862	141	11	(	(	PUNCT
cana-1862	141	12	and	and	CCONJ
cana-1862	141	13	q	q	ADV
cana-1862	141	14	-	-	PUNCT
cana-1862	141	15	learning	learning	NOUN
cana-1862	141	16	in	in	ADP
cana-1862	141	17	particular	particular	ADJ
cana-1862	141	18	)	)	PUNCT
cana-1862	141	19	have	have	AUX
cana-1862	141	20	been	be	AUX
cana-1862	141	21	used	use	VERB
cana-1862	141	22	to	to	PART
cana-1862	141	23	create	create	VERB
cana-1862	141	24	agents	agent	NOUN
cana-1862	141	25	that	that	PRON
cana-1862	141	26	interact	interact	VERB
cana-1862	141	27	with	with	ADP
cana-1862	141	28	network	network	NOUN
cana-1862	141	29	environments	environment	NOUN
cana-1862	141	30	and	and	CCONJ
cana-1862	141	31	learn	learn	VERB
cana-1862	141	32	which	which	DET
cana-1862	141	33	policies	policy	NOUN
cana-1862	141	34	are	be	AUX
cana-1862	141	35	better	well	ADJ
cana-1862	141	36	at	at	ADP
cana-1862	141	37	opposing	oppose	VERB
cana-1862	141	38	vulnerabilities	vulnerability	NOUN
cana-1862	141	39	.	.	PUNCT
cana-1862	142	1	used	use	VERB
cana-1862	142	2	q	q	NOUN
cana-1862	142	3	-	-	PUNCT
cana-1862	142	4	learning	learning	NOUN
cana-1862	142	5	to	to	PART
cana-1862	142	6	learn	learn	VERB
cana-1862	142	7	from	from	ADP
cana-1862	142	8	observed	observed	ADJ
cana-1862	142	9	network	network	NOUN
cana-1862	142	10	state	state	NOUN
cana-1862	142	11	methods	method	NOUN
cana-1862	142	12	and	and	CCONJ
cana-1862	142	13	thus	thus	ADV
cana-1862	142	14	allowing	allow	VERB
cana-1862	142	15	the	the	DET
cana-1862	142	16	defence	defence	NOUN
cana-1862	142	17	strategy	strategy	NOUN
cana-1862	142	18	of	of	ADP
cana-1862	142	19	their	their	PRON
cana-1862	142	20	reinforcement	reinforcement	NOUN
cana-1862	142	21	learning	learn	VERB
cana-1862	142	22	agent	agent	NOUN
cana-1862	142	23	to	to	PART
cana-1862	142	24	adapt	adapt	VERB
cana-1862	142	25	by	by	ADP
cana-1862	142	26	providing	provide	VERB
cana-1862	142	27	optimized	optimize	VERB
cana-1862	142	28	actions	action	NOUN
cana-1862	142	29	to	to	PART
cana-1862	142	30	avoid	avoid	VERB
cana-1862	142	31	security	security	NOUN
cana-1862	142	32	breaches	breach	NOUN
cana-1862	142	33	with	with	ADP
cana-1862	142	34	each	each	DET
cana-1862	142	35	action	action	NOUN
cana-1862	142	36	taken	take	VERB
cana-1862	142	37	.	.	PUNCT
cana-1862	143	1	the	the	DET
cana-1862	143	2	heart	heart	NOUN
cana-1862	143	3	of	of	ADP
cana-1862	143	4	q	q	NOUN
cana-1862	143	5	-	-	PUNCT
cana-1862	143	6	learning	learning	NOUN
cana-1862	143	7	lies	lie	NOUN
cana-1862	143	8	in	in	ADP
cana-1862	143	9	the	the	DET
cana-1862	143	10	way	way	NOUN
cana-1862	143	11	it	it	PRON
cana-1862	143	12	computes	compute	VERB
cana-1862	143	13	and	and	CCONJ
cana-1862	143	14	updates	update	VERB
cana-1862	143	15	its	its	PRON
cana-1862	143	16	q	q	NOUN
cana-1862	143	17	-	-	PUNCT
cana-1862	143	18	values	value	NOUN
cana-1862	143	19	which	which	PRON
cana-1862	143	20	is	be	AUX
cana-1862	143	21	modelled	model	VERB
cana-1862	143	22	after	after	ADP
cana-1862	143	23	the	the	DET
cana-1862	143	24	bellman	bellman	NOUN
cana-1862	143	25	equation	equation	NOUN
cana-1862	143	26	,	,	PUNCT
cana-1862	143	27	𝑄(𝑠	𝑄(𝑠	PROPN
cana-1862	143	28	,	,	PUNCT
cana-1862	143	29	𝑎	𝑎	NOUN
cana-1862	143	30	)	)	PUNCT
cana-1862	143	31	←	←	PROPN
cana-1862	143	32	𝑄(𝑠	𝑄(𝑠	PROPN
cana-1862	143	33	,	,	PUNCT
cana-1862	143	34	𝑎	𝑎	NOUN
cana-1862	143	35	)	)	PUNCT
cana-1862	143	36	+	+	NUM
cana-1862	143	37	𝛼[𝑟	𝛼[𝑟	PUNCT
cana-1862	144	1	+	+	CCONJ
cana-1862	144	2	𝛾𝑚𝑎𝑥	𝛾𝑚𝑎𝑥	PROPN
cana-1862	144	3	𝑎′	𝑎′	PRON
cana-1862	144	4	𝑄(𝑠′	𝑄(𝑠′	PROPN
cana-1862	144	5	,	,	PUNCT
cana-1862	144	6	𝑎′	𝑎′	NUM
cana-1862	144	7	)	)	PUNCT
cana-1862	144	8	−	−	NOUN
cana-1862	144	9	𝑄(𝑠	𝑄(𝑠	NUM
cana-1862	144	10	,	,	PUNCT
cana-1862	144	11	𝑎	𝑎	NOUN
cana-1862	144	12	)	)	PUNCT
cana-1862	144	13	]	]	PUNCT
cana-1862	144	14	,	,	PUNCT
cana-1862	144	15	where	where	SCONJ
cana-1862	144	16	,	,	PUNCT
cana-1862	144	17	𝑄(𝑠	𝑄(𝑠	PROPN
cana-1862	144	18	,	,	PUNCT
cana-1862	144	19	𝑎	𝑎	NOUN
cana-1862	144	20	)	)	PUNCT
cana-1862	144	21	is	be	AUX
cana-1862	144	22	the	the	DET
cana-1862	144	23	value	value	NOUN
cana-1862	144	24	of	of	ADP
cana-1862	144	25	taking	take	VERB
cana-1862	144	26	action	action	NOUN
cana-1862	144	27	𝑎	𝑎	NOUN
cana-1862	144	28	in	in	ADP
cana-1862	144	29	state	state	NOUN
cana-1862	144	30	𝑠	𝑠	PROPN
cana-1862	144	31	,	,	PUNCT
cana-1862	144	32	𝛼	𝛼	PROPN
cana-1862	144	33	is	be	AUX
cana-1862	144	34	the	the	DET
cana-1862	144	35	learning	learning	NOUN
cana-1862	144	36	rate	rate	NOUN
cana-1862	144	37	,	,	PUNCT
cana-1862	144	38	𝑟	𝑟	PRON
cana-1862	144	39	is	be	AUX
cana-1862	144	40	the	the	DET
cana-1862	144	41	reward	reward	NOUN
cana-1862	144	42	,	,	PUNCT
cana-1862	144	43	𝛾	𝛾	PROPN
cana-1862	144	44	is	be	AUX
cana-1862	144	45	the	the	DET
cana-1862	144	46	discount	discount	NOUN
cana-1862	144	47	factor	factor	NOUN
cana-1862	144	48	,	,	PUNCT
cana-1862	144	49	and	and	CCONJ
cana-1862	144	50	𝑠′	𝑠′	NOUN
cana-1862	144	51	is	be	AUX
cana-1862	144	52	the	the	DET
cana-1862	144	53	next	next	ADJ
cana-1862	144	54	state	state	NOUN
cana-1862	144	55	.	.	PUNCT
cana-1862	145	1	this	this	DET
cana-1862	145	2	formulation	formulation	NOUN
cana-1862	145	3	enables	enable	VERB
cana-1862	145	4	the	the	DET
cana-1862	145	5	agent	agent	NOUN
cana-1862	145	6	to	to	PART
cana-1862	145	7	learn	learn	VERB
cana-1862	145	8	optimal	optimal	ADJ
cana-1862	145	9	actions	action	NOUN
cana-1862	145	10	over	over	ADP
cana-1862	145	11	time	time	NOUN
cana-1862	145	12	,	,	PUNCT
cana-1862	145	13	dynamically	dynamically	ADV
cana-1862	145	14	enhancing	enhance	VERB
cana-1862	145	15	network	network	NOUN
cana-1862	145	16	security[26,27	security[26,27	NOUN
cana-1862	145	17	]	]	PUNCT
cana-1862	145	18	.	.	PUNCT
cana-1862	146	1	reviewing	review	VERB
cana-1862	146	2	the	the	DET
cana-1862	146	3	related	relate	VERB
cana-1862	146	4	work	work	NOUN
cana-1862	146	5	also	also	ADV
cana-1862	146	6	shows	show	VERB
cana-1862	146	7	that	that	SCONJ
cana-1862	146	8	there	there	PRON
cana-1862	146	9	are	be	VERB
cana-1862	146	10	many	many	ADJ
cana-1862	146	11	machine	machine	NOUN
cana-1862	146	12	learning	learning	NOUN
cana-1862	146	13	models	model	NOUN
cana-1862	146	14	and	and	CCONJ
cana-1862	146	15	mathematical	mathematical	ADJ
cana-1862	146	16	methods	method	NOUN
cana-1862	146	17	applied	apply	VERB
cana-1862	146	18	information	information	NOUN
cana-1862	146	19	security	security	NOUN
cana-1862	146	20	vulnerability	vulnerability	NOUN
cana-1862	146	21	detection	detection	NOUN
cana-1862	146	22	.	.	PUNCT
cana-1862	147	1	supervised	supervised	ADJ
cana-1862	147	2	methods	method	NOUN
cana-1862	147	3	-random	-random	PROPN
cana-1862	147	4	forests	forest	NOUN
cana-1862	147	5	and	and	CCONJ
cana-1862	147	6	neural	neural	ADJ
cana-1862	147	7	networksin	networksin	NOUN
cana-1862	147	8	case	case	NOUN
cana-1862	147	9	that	that	SCONJ
cana-1862	147	10	we	we	PRON
cana-1862	147	11	have	have	AUX
cana-1862	147	12	labeled	label	VERB
cana-1862	147	13	data	datum	NOUN
cana-1862	147	14	,	,	PUNCT
cana-1862	147	15	unsupervised	unsupervised	ADJ
cana-1862	147	16	as	as	ADP
cana-1862	147	17	k	k	NOUN
cana-1862	147	18	-	-	PUNCT
cana-1862	147	19	means	mean	NOUN
cana-1862	147	20	and	and	CCONJ
cana-1862	147	21	autoencoders	autoencoder	NOUN
cana-1862	147	22	for	for	ADP
cana-1862	147	23	new	new	ADJ
cana-1862	147	24	attacks	attack	NOUN
cana-1862	147	25	and	and	CCONJ
cana-1862	147	26	zero	zero	NUM
cana-1862	147	27	-	-	PUNCT
cana-1862	147	28	day	day	NOUN
cana-1862	147	29	vulnerabilities	vulnerability	NOUN
cana-1862	147	30	.	.	PUNCT
cana-1862	148	1	bayesian	bayesian	NOUN
cana-1862	148	2	networks	network	NOUN
cana-1862	148	3	are	be	AUX
cana-1862	148	4	very	very	ADV
cana-1862	148	5	well	well	ADV
cana-1862	148	6	suited	suited	ADJ
cana-1862	148	7	for	for	ADP
cana-1862	148	8	modelling	model	VERB
cana-1862	148	9	uncertainty	uncertainty	NOUN
cana-1862	148	10	,	,	PUNCT
cana-1862	148	11	and	and	CCONJ
cana-1862	148	12	hmms	hmms	NOUN
cana-1862	148	13	can	can	AUX
cana-1862	148	14	be	be	AUX
cana-1862	148	15	represented	represent	VERB
cana-1862	148	16	as	as	ADP
cana-1862	148	17	a	a	DET
cana-1862	148	18	special	special	ADJ
cana-1862	148	19	case	case	NOUN
cana-1862	148	20	of	of	ADP
cana-1862	148	21	bayesian	bayesian	NOUN
cana-1862	148	22	networks	network	NOUN
cana-1862	148	23	(	(	PUNCT
cana-1862	148	24	defined	define	VERB
cana-1862	148	25	by	by	ADP
cana-1862	148	26	a	a	DET
cana-1862	148	27	cpd	cpd	ADJ
cana-1862	148	28	representation	representation	NOUN
cana-1862	148	29	)	)	PUNCT
cana-1862	148	30	.	.	PUNCT
cana-1862	149	1	furthermore	furthermore	ADV
cana-1862	149	2	,	,	PUNCT
cana-1862	149	3	ensemble	ensemble	ADJ
cana-1862	149	4	methods	method	NOUN
cana-1862	149	5	and	and	CCONJ
cana-1862	149	6	hybrid	hybrid	NOUN
cana-1862	149	7	models	model	NOUN
cana-1862	149	8	combine	combine	VERB
cana-1862	149	9	the	the	DET
cana-1862	149	10	power	power	NOUN
cana-1862	149	11	of	of	ADP
cana-1862	149	12	several	several	ADJ
cana-1862	149	13	algorithms	algorithm	NOUN
cana-1862	149	14	to	to	PART
cana-1862	149	15	improve	improve	VERB
cana-1862	149	16	the	the	DET
cana-1862	149	17	detection	detection	NOUN
cana-1862	149	18	accuracy	accuracy	NOUN
cana-1862	149	19	.	.	PUNCT
cana-1862	150	1	though	though	ADV
cana-1862	150	2	,	,	PUNCT
cana-1862	150	3	one	one	PRON
cana-1862	150	4	can	can	AUX
cana-1862	150	5	also	also	ADV
cana-1862	150	6	face	face	VERB
cana-1862	150	7	challenges	challenge	NOUN
cana-1862	150	8	like	like	ADP
cana-1862	150	9	less	less	ADJ
cana-1862	150	10	availability	availability	NOUN
cana-1862	150	11	of	of	ADP
cana-1862	150	12	labelled	label	VERB
cana-1862	150	13	data	datum	NOUN
cana-1862	150	14	,	,	PUNCT
cana-1862	150	15	high	high	ADJ
cana-1862	150	16	dimensionality	dimensionality	NOUN
cana-1862	150	17	of	of	ADP
cana-1862	150	18	network	network	NOUN
cana-1862	150	19	traffic	traffic	NOUN
cana-1862	150	20	,	,	PUNCT
cana-1862	150	21	and	and	CCONJ
cana-1862	150	22	the	the	DET
cana-1862	150	23	requirement	requirement	NOUN
cana-1862	150	24	to	to	PART
cana-1862	150	25	have	have	AUX
cana-1862	150	26	adaptable	adaptable	ADJ
cana-1862	150	27	models	model	NOUN
cana-1862	150	28	aware	aware	ADJ
cana-1862	150	29	to	to	ADP
cana-1862	150	30	recent	recent	ADJ
cana-1862	150	31	security	security	NOUN
cana-1862	150	32	threats	threat	NOUN
cana-1862	150	33	.	.	PUNCT
cana-1862	151	1	combining	combine	VERB
cana-1862	151	2	advanced	advanced	ADJ
cana-1862	151	3	mathematical	mathematical	ADJ
cana-1862	151	4	techniques	technique	NOUN
cana-1862	151	5	with	with	ADP
cana-1862	151	6	machine	machine	NOUN
cana-1862	151	7	learning	learning	NOUN
cana-1862	151	8	can	can	AUX
cana-1862	151	9	open	open	VERB
cana-1862	151	10	new	new	ADJ
cana-1862	151	11	horizon	horizon	NOUN
cana-1862	151	12	into	into	ADP
cana-1862	151	13	how	how	SCONJ
cana-1862	151	14	we	we	PRON
cana-1862	151	15	can	can	AUX
cana-1862	151	16	solve	solve	VERB
cana-1862	151	17	these	these	DET
cana-1862	151	18	challenges	challenge	NOUN
cana-1862	151	19	and	and	CCONJ
cana-1862	151	20	in	in	ADP
cana-1862	151	21	particular	particular	ADJ
cana-1862	151	22	towards	towards	ADP
cana-1862	151	23	more	more	ADV
cana-1862	151	24	intelligent	intelligent	ADJ
cana-1862	151	25	and	and	CCONJ
cana-1862	151	26	adaptive	adaptive	ADJ
cana-1862	151	27	cybersecurity	cybersecurity	NOUN
cana-1862	151	28	systems	system	NOUN
cana-1862	151	29	.	.	PUNCT
cana-1862	152	1	the	the	DET
cana-1862	152	2	future	future	ADJ
cana-1862	152	3	directions	direction	NOUN
cana-1862	152	4	for	for	ADP
cana-1862	152	5	work	work	NOUN
cana-1862	152	6	on	on	ADP
cana-1862	152	7	this	this	DET
cana-1862	152	8	issue	issue	NOUN
cana-1862	152	9	probably	probably	ADV
cana-1862	152	10	centre	centre	VERB
cana-1862	152	11	around	around	ADP
cana-1862	152	12	the	the	DET
cana-1862	152	13	development	development	NOUN
cana-1862	152	14	of	of	ADP
cana-1862	152	15	more	more	ADV
cana-1862	152	16	efficient	efficient	ADJ
cana-1862	152	17	hybrid	hybrid	NOUN
cana-1862	152	18	models	model	NOUN
cana-1862	152	19	,	,	PUNCT
cana-1862	152	20	better	well	ADJ
cana-1862	152	21	interpreting	interpret	VERB
cana-1862	152	22	complex	complex	ADJ
cana-1862	152	23	algorithms	algorithm	NOUN
cana-1862	152	24	,	,	PUNCT
cana-1862	152	25	and	and	CCONJ
cana-1862	152	26	advancing	advance	VERB
cana-1862	152	27	real	real	ADJ
cana-1862	152	28	-	-	PUNCT
cana-1862	152	29	time	time	NOUN
cana-1862	152	30	adaptive	adaptive	ADJ
cana-1862	152	31	vulnerability	vulnerability	NOUN
cana-1862	152	32	detection	detection	NOUN
cana-1862	152	33	systems	system	NOUN
cana-1862	152	34	.	.	PUNCT
cana-1862	153	1	3	3	X
cana-1862	153	2	.	.	X
cana-1862	153	3	methodology	methodology	NOUN
cana-1862	153	4	:	:	PUNCT
cana-1862	153	5	●	●	PUNCT
cana-1862	153	6	data	data	NOUN
cana-1862	153	7	collection	collection	NOUN
cana-1862	153	8	&	&	CCONJ
cana-1862	153	9	pre	pre	ADJ
cana-1862	153	10	-	-	ADJ
cana-1862	153	11	processing	processing	ADJ
cana-1862	153	12	:	:	PUNCT
cana-1862	153	13	sources	source	NOUN
cana-1862	153	14	of	of	ADP
cana-1862	153	15	data	datum	NOUN
cana-1862	153	16	:	:	PUNCT
cana-1862	153	17	the	the	DET
cana-1862	153	18	formulation	formulation	NOUN
cana-1862	153	19	asks	ask	VERB
cana-1862	153	20	for	for	ADP
cana-1862	153	21	a	a	DET
cana-1862	153	22	variety	variety	NOUN
cana-1862	153	23	of	of	ADP
cana-1862	153	24	top	top	ADJ
cana-1862	153	25	-	-	PUNCT
cana-1862	153	26	notch	notch	NOUN
cana-1862	153	27	datasets	dataset	NOUN
cana-1862	153	28	to	to	PART
cana-1862	153	29	create	create	VERB
cana-1862	153	30	a	a	DET
cana-1862	153	31	vulnerability	vulnerability	NOUN
cana-1862	153	32	detection	detection	NOUN
cana-1862	153	33	system	system	NOUN
cana-1862	153	34	.	.	PUNCT
cana-1862	154	1	common	common	ADJ
cana-1862	154	2	data	datum	NOUN
cana-1862	154	3	types	type	NOUN
cana-1862	154	4	used	use	VERB
cana-1862	154	5	in	in	ADP
cana-1862	154	6	cybersecurity	cybersecurity	NOUN
cana-1862	154	7	include	include	VERB
cana-1862	154	8	network	network	NOUN
cana-1862	154	9	traffic	traffic	NOUN
cana-1862	154	10	data	datum	NOUN
cana-1862	154	11	,	,	PUNCT
cana-1862	154	12	system	system	NOUN
cana-1862	154	13	logs	log	NOUN
cana-1862	154	14	and	and	CCONJ
cana-1862	154	15	firewall	firewall	NOUN
cana-1862	154	16	records	record	NOUN
cana-1862	154	17	,	,	PUNCT
cana-1862	154	18	and	and	CCONJ
cana-1862	154	19	endpoint	endpoint	VERB
cana-1862	154	20	security	security	NOUN
cana-1862	154	21	data	datum	NOUN
cana-1862	154	22	.	.	PUNCT
cana-1862	155	1	in	in	ADP
cana-1862	155	2	fact	fact	NOUN
cana-1862	155	3	,	,	PUNCT
cana-1862	155	4	publicly	publicly	ADV
cana-1862	155	5	available	available	ADJ
cana-1862	155	6	datasets	dataset	NOUN
cana-1862	155	7	like	like	ADP
cana-1862	155	8	the	the	DET
cana-1862	155	9	cicids	cicid	NOUN
cana-1862	155	10	2017	2017	NUM
cana-1862	155	11	dataset	dataset	NOUN
cana-1862	155	12	(	(	PUNCT
cana-1862	155	13	composed	compose	VERB
cana-1862	155	14	of	of	ADP
cana-1862	155	15	a	a	DET
cana-1862	155	16	diversity	diversity	NOUN
cana-1862	155	17	of	of	ADP
cana-1862	155	18	network	network	NOUN
cana-1862	155	19	traffic	traffic	NOUN
cana-1862	155	20	data	data	PROPN
cana-1862	155	21	)	)	PUNCT
cana-1862	155	22	and	and	CCONJ
cana-1862	155	23	the	the	DET
cana-1862	155	24	unsw	unsw	PROPN
cana-1862	155	25	-	-	PUNCT
cana-1862	155	26	nb15	nb15	PROPN
cana-1862	155	27	dataset	dataset	NOUN
cana-1862	155	28	(	(	PUNCT
cana-1862	155	29	comprised	comprise	VERB
cana-1862	155	30	of	of	ADP
cana-1862	155	31	labelled	label	VERB
cana-1862	155	32	instances	instance	NOUN
cana-1862	155	33	by	by	ADP
cana-1862	155	34	normal	normal	ADJ
cana-1862	155	35	and	and	CCONJ
cana-1862	155	36	malware	malware	NOUN
cana-1862	155	37	activity	activity	NOUN
cana-1862	155	38	)	)	PUNCT
cana-1862	155	39	for	for	ADP
cana-1862	155	40	this	this	DET
cana-1862	155	41	research	research	NOUN
cana-1862	155	42	can	can	AUX
cana-1862	155	43	also	also	ADV
cana-1862	155	44	be	be	AUX
cana-1862	155	45	referenced	reference	VERB
cana-1862	155	46	.	.	PUNCT
cana-1862	156	1	you	you	PRON
cana-1862	156	2	can	can	AUX
cana-1862	156	3	also	also	ADV
cana-1862	156	4	collect	collect	VERB
cana-1862	156	5	live	live	ADJ
cana-1862	156	6	data	datum	NOUN
cana-1862	156	7	from	from	ADP
cana-1862	156	8	a	a	DET
cana-1862	156	9	network	network	NOUN
cana-1862	156	10	of	of	ADP
cana-1862	156	11	the	the	DET
cana-1862	156	12	organisation	organisation	NOUN
cana-1862	156	13	using	use	VERB
cana-1862	156	14	network	network	NOUN
cana-1862	156	15	monitoring	monitoring	NOUN
cana-1862	156	16	communications	communication	NOUN
cana-1862	156	17	on	on	ADP
cana-1862	156	18	applied	apply	VERB
cana-1862	156	19	nonlinear	nonlinear	ADJ
cana-1862	156	20	analysis	analysis	NOUN
cana-1862	156	21	issn	issn	NOUN
cana-1862	156	22	:	:	PUNCT
cana-1862	156	23	1074	1074	NUM
cana-1862	156	24	-	-	PUNCT
cana-1862	156	25	133x	133x	NUM
cana-1862	156	26	vol	vol	NOUN
cana-1862	156	27	32	32	NUM
cana-1862	156	28	no	no	NOUN
cana-1862	156	29	.	.	NOUN
cana-1862	156	30	2	2	NUM
cana-1862	156	31	(	(	PUNCT
cana-1862	156	32	2025	2025	NUM
cana-1862	156	33	)	)	PUNCT
cana-1862	156	34	701	701	NUM
cana-1862	156	35	https://internationalpubls.com	https://internationalpubls.com	X
cana-1862	156	36	tools	tool	NOUN
cana-1862	156	37	such	such	ADJ
cana-1862	156	38	as	as	ADP
cana-1862	156	39	wireshark	wireshark	NOUN
cana-1862	156	40	or	or	CCONJ
cana-1862	156	41	zeek	zeek	PROPN
cana-1862	156	42	to	to	PART
cana-1862	156	43	build	build	VERB
cana-1862	156	44	customized	customized	ADJ
cana-1862	156	45	datasets	dataset	NOUN
cana-1862	156	46	.	.	PUNCT
cana-1862	157	1	this	this	PRON
cana-1862	157	2	may	may	AUX
cana-1862	157	3	allow	allow	VERB
cana-1862	157	4	us	we	PRON
cana-1862	157	5	to	to	PART
cana-1862	157	6	apply	apply	VERB
cana-1862	157	7	supervised	supervised	ADJ
cana-1862	157	8	,	,	PUNCT
cana-1862	157	9	unsupervised	unsupervised	ADJ
cana-1862	157	10	and	and	CCONJ
cana-1862	157	11	semi	semi	ADJ
cana-1862	157	12	-	-	ADJ
cana-1862	157	13	supervised	supervised	ADJ
cana-1862	157	14	machine	machine	NOUN
cana-1862	157	15	learning	learning	NOUN
cana-1862	157	16	methods	method	NOUN
cana-1862	157	17	,	,	PUNCT
cana-1862	157	18	using	use	VERB
cana-1862	157	19	labelled	label	VERB
cana-1862	157	20	and	and	CCONJ
cana-1862	157	21	unlabelled	unlabelled	ADJ
cana-1862	157	22	data	datum	NOUN
cana-1862	157	23	.	.	PUNCT
cana-1862	158	1	●	●	PUNCT
cana-1862	158	2	data	datum	NOUN
cana-1862	158	3	pre	pre	ADJ
cana-1862	158	4	-	-	ADJ
cana-1862	158	5	processing	processing	ADJ
cana-1862	158	6	:	:	PUNCT
cana-1862	158	7	network	network	NOUN
cana-1862	158	8	data	datum	NOUN
cana-1862	158	9	can	can	AUX
cana-1862	158	10	often	often	ADV
cana-1862	158	11	be	be	AUX
cana-1862	158	12	noisy	noisy	ADJ
cana-1862	158	13	,	,	PUNCT
cana-1862	158	14	include	include	VERB
cana-1862	158	15	missing	miss	VERB
cana-1862	158	16	values	value	NOUN
cana-1862	158	17	and	and	CCONJ
cana-1862	158	18	irrelevant	irrelevant	ADJ
cana-1862	158	19	variables	variable	NOUN
cana-1862	158	20	.	.	PUNCT
cana-1862	159	1	hence	hence	ADV
cana-1862	159	2	,	,	PUNCT
cana-1862	159	3	it	it	PRON
cana-1862	159	4	is	be	AUX
cana-1862	159	5	an	an	DET
cana-1862	159	6	important	important	ADJ
cana-1862	159	7	stage	stage	NOUN
cana-1862	159	8	in	in	ADP
cana-1862	159	9	the	the	DET
cana-1862	159	10	entire	entire	ADJ
cana-1862	159	11	process	process	NOUN
cana-1862	159	12	of	of	ADP
cana-1862	159	13	natural	natural	ADJ
cana-1862	159	14	language	language	NOUN
cana-1862	159	15	processing	processing	NOUN
cana-1862	159	16	which	which	PRON
cana-1862	159	17	consisted	consist	VERB
cana-1862	159	18	of	of	ADP
cana-1862	159	19	the	the	DET
cana-1862	159	20	following	follow	VERB
cana-1862	159	21	sub	sub	NOUN
cana-1862	159	22	-	-	NOUN
cana-1862	159	23	processes	process	NOUN
cana-1862	159	24	:	:	PUNCT
cana-1862	159	25	missing	miss	VERB
cana-1862	159	26	values	value	NOUN
cana-1862	159	27	in	in	ADP
cana-1862	159	28	the	the	DET
cana-1862	159	29	data	datum	NOUN
cana-1862	159	30	cleaning	clean	VERB
cana-1862	159	31	,	,	PUNCT
cana-1862	159	32	can	can	AUX
cana-1862	159	33	remove	remove	VERB
cana-1862	159	34	or	or	CCONJ
cana-1862	159	35	impute	impute	VERB
cana-1862	159	36	them	they	PRON
cana-1862	159	37	.	.	PUNCT
cana-1862	160	1	median	median	ADJ
cana-1862	160	2	or	or	CCONJ
cana-1862	160	3	mean	mean	ADJ
cana-1862	160	4	imputation	imputation	NOUN
cana-1862	160	5	can	can	AUX
cana-1862	160	6	be	be	AUX
cana-1862	160	7	used	use	VERB
cana-1862	160	8	for	for	ADP
cana-1862	160	9	replacing	replace	VERB
cana-1862	160	10	missing	miss	VERB
cana-1862	160	11	values	value	NOUN
cana-1862	160	12	in	in	ADP
cana-1862	160	13	case	case	NOUN
cana-1862	160	14	of	of	ADP
cana-1862	160	15	numerical	numerical	ADJ
cana-1862	160	16	attributes	attribute	NOUN
cana-1862	160	17	.	.	PUNCT
cana-1862	161	1	another	another	DET
cana-1862	161	2	way	way	NOUN
cana-1862	161	3	for	for	ADP
cana-1862	161	4	an	an	DET
cana-1862	161	5	imputation	imputation	NOUN
cana-1862	161	6	for	for	ADP
cana-1862	161	7	the	the	DET
cana-1862	161	8	missing	miss	VERB
cana-1862	161	9	values	value	NOUN
cana-1862	161	10	for	for	ADP
cana-1862	161	11	categorical	categorical	ADJ
cana-1862	161	12	variables	variable	NOUN
cana-1862	161	13	that	that	PRON
cana-1862	161	14	can	can	AUX
cana-1862	161	15	be	be	AUX
cana-1862	161	16	mode	mode	NOUN
cana-1862	161	17	.	.	PUNCT
cana-1862	162	1	o	o	NOUN
cana-1862	162	2	outlier	outlier	NOUN
cana-1862	162	3	removal	removal	NOUN
cana-1862	162	4	:	:	PUNCT
cana-1862	162	5	detect	detect	VERB
cana-1862	162	6	and	and	CCONJ
cana-1862	162	7	delete	delete	VERB
cana-1862	162	8	large	large	ADJ
cana-1862	162	9	outliers	outlier	NOUN
cana-1862	162	10	that	that	PRON
cana-1862	162	11	can	can	AUX
cana-1862	162	12	be	be	AUX
cana-1862	162	13	considered	consider	VERB
cana-1862	162	14	as	as	ADP
cana-1862	162	15	noise	noise	NOUN
cana-1862	162	16	or	or	CCONJ
cana-1862	162	17	corrupted	corrupted	ADJ
cana-1862	162	18	records	record	NOUN
cana-1862	162	19	according	accord	VERB
cana-1862	162	20	to	to	ADP
cana-1862	162	21	statistical	statistical	ADJ
cana-1862	162	22	techniques	technique	NOUN
cana-1862	162	23	.	.	PUNCT
cana-1862	163	1	outliers	outlier	NOUN
cana-1862	163	2	,	,	PUNCT
cana-1862	163	3	for	for	ADP
cana-1862	163	4	example	example	NOUN
cana-1862	163	5	,	,	PUNCT
cana-1862	163	6	can	can	AUX
cana-1862	163	7	be	be	AUX
cana-1862	163	8	identified	identify	VERB
cana-1862	163	9	using	use	VERB
cana-1862	163	10	dimensionality	dimensionality	NOUN
cana-1862	163	11	technique	technique	NOUN
cana-1862	163	12	called	call	VERB
cana-1862	163	13	the	the	DET
cana-1862	163	14	z	z	NOUN
cana-1862	163	15	score	score	NOUN
cana-1862	163	16	method	method	NOUN
cana-1862	163	17	.	.	PUNCT
cana-1862	164	1	𝑍𝑖	𝑍𝑖	PROPN
cana-1862	164	2	=	=	PUNCT
cana-1862	164	3	𝑥𝑖	𝑥𝑖	PROPN
cana-1862	164	4	−	−	PROPN
cana-1862	164	5	𝜇	𝜇	ADP
cana-1862	164	6	𝜎	𝜎	PROPN
cana-1862	164	7	,	,	PUNCT
cana-1862	164	8	where	where	SCONJ
cana-1862	164	9	,	,	PUNCT
cana-1862	164	10	𝑍𝑖	𝑍𝑖	PROPN
cana-1862	164	11	is	be	AUX
cana-1862	164	12	the	the	DET
cana-1862	164	13	z	z	NOUN
cana-1862	164	14	-	-	PUNCT
cana-1862	164	15	score	score	NOUN
cana-1862	164	16	of	of	ADP
cana-1862	164	17	data	datum	NOUN
cana-1862	164	18	point	point	NOUN
cana-1862	164	19	𝑥𝑖	𝑥𝑖	PROPN
cana-1862	164	20	,	,	PUNCT
cana-1862	164	21	𝜇	𝜇	X
cana-1862	164	22	is	be	AUX
cana-1862	164	23	the	the	DET
cana-1862	164	24	mean	mean	NOUN
cana-1862	164	25	of	of	ADP
cana-1862	164	26	the	the	DET
cana-1862	164	27	dataset	dataset	NOUN
cana-1862	164	28	,	,	PUNCT
cana-1862	164	29	and	and	CCONJ
cana-1862	164	30	𝜎	𝜎	PROPN
cana-1862	164	31	is	be	AUX
cana-1862	164	32	the	the	DET
cana-1862	164	33	standard	standard	ADJ
cana-1862	164	34	deviation	deviation	NOUN
cana-1862	164	35	.	.	PUNCT
cana-1862	165	1	entries	entry	NOUN
cana-1862	165	2	with	with	ADP
cana-1862	165	3	∣	∣	ADJ
cana-1862	165	4	𝑍𝑖	𝑍𝑖	PROPN
cana-1862	165	5	∣	∣	NOUN
cana-1862	165	6	>	>	X
cana-1862	165	7	3	3	NUM
cana-1862	165	8	are	be	AUX
cana-1862	165	9	considered	consider	VERB
cana-1862	165	10	outliers	outlier	NOUN
cana-1862	165	11	.	.	PUNCT
cana-1862	166	1	o	o	NOUN
cana-1862	166	2	impute	impute	NOUN
cana-1862	166	3	missing	miss	VERB
cana-1862	166	4	values	value	NOUN
cana-1862	166	5	:	:	PUNCT
cana-1862	166	6	use	use	NOUN
cana-1862	166	7	mean	mean	ADJ
cana-1862	166	8	/	/	SYM
cana-1862	166	9	mode	mode	NOUN
cana-1862	166	10	substitution	substitution	NOUN
cana-1862	166	11	,	,	PUNCT
cana-1862	166	12	k	k	X
cana-1862	166	13	-	-	PUNCT
cana-1862	166	14	nearest	near	ADJ
cana-1862	166	15	neighbours	neighbour	NOUN
cana-1862	166	16	(	(	PUNCT
cana-1862	166	17	knn	knn	PROPN
cana-1862	166	18	)	)	PUNCT
cana-1862	166	19	etc	etc	X
cana-1862	166	20	.	.	X
cana-1862	166	21	to	to	PART
cana-1862	166	22	handle	handle	VERB
cana-1862	166	23	imputation	imputation	NOUN
cana-1862	166	24	of	of	ADP
cana-1862	166	25	missing	miss	VERB
cana-1862	166	26	values	value	NOUN
cana-1862	166	27	in	in	ADP
cana-1862	166	28	the	the	DET
cana-1862	166	29	dataset	dataset	NOUN
cana-1862	166	30	.	.	PUNCT
cana-1862	167	1	feature	feature	NOUN
cana-1862	167	2	engineering	engineering	NOUN
cana-1862	167	3	:	:	PUNCT
cana-1862	167	4	packet	packet	NOUN
cana-1862	167	5	size	size	NOUN
cana-1862	167	6	,	,	PUNCT
cana-1862	167	7	duration	duration	NOUN
cana-1862	167	8	,	,	PUNCT
cana-1862	167	9	protocol	protocol	NOUN
cana-1862	167	10	type	type	NOUN
cana-1862	167	11	,	,	PUNCT
cana-1862	167	12	source	source	NOUN
cana-1862	167	13	/	/	SYM
cana-1862	167	14	destination	destination	NOUN
cana-1862	167	15	ip	ip	NOUN
cana-1862	167	16	address	address	NOUN
cana-1862	167	17	and	and	CCONJ
cana-1862	167	18	port	port	NOUN
cana-1862	167	19	numbers	number	NOUN
cana-1862	167	20	.	.	PUNCT
cana-1862	168	1	this	this	DET
cana-1862	168	2	type	type	NOUN
cana-1862	168	3	of	of	ADP
cana-1862	168	4	information	information	NOUN
cana-1862	168	5	entropy	entropy	NOUN
cana-1862	168	6	is	be	AUX
cana-1862	168	7	an	an	DET
cana-1862	168	8	important	important	ADJ
cana-1862	168	9	domain	domain	NOUN
cana-1862	168	10	-	-	PUNCT
cana-1862	168	11	specific	specific	ADJ
cana-1862	168	12	feature	feature	NOUN
cana-1862	168	13	,	,	PUNCT
cana-1862	168	14	as	as	SCONJ
cana-1862	168	15	it	it	PRON
cana-1862	168	16	can	can	AUX
cana-1862	168	17	be	be	AUX
cana-1862	168	18	used	use	VERB
cana-1862	168	19	to	to	PART
cana-1862	168	20	differentiate	differentiate	VERB
cana-1862	168	21	between	between	ADP
cana-1862	168	22	network	network	NOUN
cana-1862	168	23	traffic	traffic	NOUN
cana-1862	168	24	acts	act	NOUN
cana-1862	168	25	(	(	PUNCT
cana-1862	168	26	i.e.	i.e.	X
cana-1862	168	27	,	,	PUNCT
cana-1862	168	28	entropy	entropy	NOUN
cana-1862	168	29	of	of	ADP
cana-1862	168	30	traffic	traffic	NOUN
cana-1862	168	31	)	)	PUNCT
cana-1862	168	32	also	also	ADV
cana-1862	168	33	,	,	PUNCT
cana-1862	168	34	second	second	ADJ
cana-1862	168	35	-	-	PUNCT
cana-1862	168	36	order	order	NOUN
cana-1862	168	37	statistics	statistic	NOUN
cana-1862	168	38	(	(	PUNCT
cana-1862	168	39	e.g.	e.g.	ADV
cana-1862	168	40	,	,	PUNCT
cana-1862	168	41	mean	mean	NOUN
cana-1862	168	42	and	and	CCONJ
cana-1862	168	43	variation	variation	NOUN
cana-1862	168	44	)	)	PUNCT
cana-1862	168	45	,	,	PUNCT
cana-1862	168	46	and	and	CCONJ
cana-1862	168	47	some	some	DET
cana-1862	168	48	flow	flow	NOUN
cana-1862	168	49	-	-	PUNCT
cana-1862	168	50	based	base	VERB
cana-1862	168	51	metrics	metric	NOUN
cana-1862	168	52	such	such	ADJ
cana-1862	168	53	as	as	ADP
cana-1862	168	54	the	the	DET
cana-1862	168	55	amount	amount	NOUN
cana-1862	168	56	of	of	ADP
cana-1862	168	57	packets	packet	NOUN
cana-1862	168	58	transferred	transfer	VERB
cana-1862	168	59	over	over	ADP
cana-1862	168	60	individual	individual	ADJ
cana-1862	168	61	flows	flow	NOUN
cana-1862	168	62	or	or	CCONJ
cana-1862	168	63	the	the	DET
cana-1862	168	64	number	number	NOUN
cana-1862	168	65	of	of	ADP
cana-1862	168	66	requests	request	NOUN
cana-1862	168	67	.	.	PUNCT
cana-1862	169	1	o	o	X
cana-1862	169	2	principal	principal	ADJ
cana-1862	169	3	component	component	NOUN
cana-1862	169	4	analysis	analysis	NOUN
cana-1862	169	5	(	(	PUNCT
cana-1862	169	6	pca	pca	NOUN
cana-1862	169	7	):	):	PUNCT
cana-1862	169	8	pca	pca	NOUN
cana-1862	169	9	reduces	reduce	VERB
cana-1862	169	10	dimensionality	dimensionality	NOUN
cana-1862	169	11	by	by	ADP
cana-1862	169	12	transforming	transform	VERB
cana-1862	169	13	the	the	DET
cana-1862	169	14	original	original	ADJ
cana-1862	169	15	data	datum	NOUN
cana-1862	169	16	into	into	ADP
cana-1862	169	17	the	the	DET
cana-1862	169	18	new	new	ADJ
cana-1862	169	19	orthonormal	orthonormal	ADJ
cana-1862	169	20	set	set	NOUN
cana-1862	169	21	of	of	ADP
cana-1862	169	22	features	feature	NOUN
cana-1862	169	23	.	.	PUNCT
cana-1862	170	1	we	we	PRON
cana-1862	170	2	compute	compute	VERB
cana-1862	170	3	the	the	DET
cana-1862	170	4	covariance	covariance	NOUN
cana-1862	170	5	matrix	matrix	NOUN
cana-1862	170	6	:	:	PUNCT
cana-1862	170	7	𝛴	𝛴	PROPN
cana-1862	170	8	=	=	NOUN
cana-1862	170	9	1	1	NUM
cana-1862	170	10	𝑛	𝑛	PRON
cana-1862	170	11	−	−	NUM
cana-1862	170	12	1	1	NUM
cana-1862	170	13	(	(	PUNCT
cana-1862	170	14	𝑋	𝑋	NOUN
cana-1862	170	15	−	−	PROPN
cana-1862	170	16	𝜇𝑋)⊤(𝑋	𝜇𝑋)⊤(𝑋	NOUN
cana-1862	170	17	−	−	NUM
cana-1862	170	18	𝜇𝑋	𝜇𝑋	ADJ
cana-1862	170	19	)	)	PUNCT
cana-1862	170	20	,	,	PUNCT
cana-1862	170	21	where	where	SCONJ
cana-1862	170	22	,	,	PUNCT
cana-1862	170	23	𝜇𝑋	𝜇𝑋	ADJ
cana-1862	170	24	is	be	AUX
cana-1862	170	25	the	the	DET
cana-1862	170	26	mean	mean	ADJ
cana-1862	170	27	vector	vector	NOUN
cana-1862	170	28	of	of	ADP
cana-1862	170	29	𝑋.	𝑋.	PROPN
cana-1862	170	30	eigenvalues	eigenvalue	NOUN
cana-1862	170	31	and	and	CCONJ
cana-1862	170	32	eigenvectors	eigenvector	NOUN
cana-1862	170	33	of	of	ADP
cana-1862	170	34	𝛴	𝛴	PROPN
cana-1862	170	35	are	be	AUX
cana-1862	170	36	then	then	ADV
cana-1862	170	37	used	use	VERB
cana-1862	170	38	to	to	PART
cana-1862	170	39	form	form	VERB
cana-1862	170	40	a	a	DET
cana-1862	170	41	reduced	reduce	VERB
cana-1862	170	42	feature	feature	NOUN
cana-1862	170	43	space	space	NOUN
cana-1862	170	44	,	,	PUNCT
cana-1862	170	45	retaining	retain	VERB
cana-1862	170	46	components	component	NOUN
cana-1862	170	47	with	with	ADP
cana-1862	170	48	the	the	DET
cana-1862	170	49	highest	high	ADJ
cana-1862	170	50	variance	variance	NOUN
cana-1862	170	51	.	.	PUNCT
cana-1862	171	1	o	o	X
cana-1862	171	2	mutual	mutual	ADJ
cana-1862	171	3	information	information	NOUN
cana-1862	171	4	:	:	PUNCT
cana-1862	171	5	calculates	calculate	VERB
cana-1862	171	6	mutual	mutual	ADJ
cana-1862	171	7	information	information	NOUN
cana-1862	171	8	value	value	NOUN
cana-1862	171	9	between	between	ADP
cana-1862	171	10	each	each	DET
cana-1862	171	11	categorical	categorical	ADJ
cana-1862	171	12	feature	feature	NOUN
cana-1862	171	13	and	and	CCONJ
cana-1862	171	14	target	target	VERB
cana-1862	171	15	variable	variable	NOUN
cana-1862	171	16	to	to	PART
cana-1862	171	17	choose	choose	VERB
cana-1862	171	18	top	top	ADJ
cana-1862	171	19	performing	performing	NOUN
cana-1862	171	20	features	feature	NOUN
cana-1862	171	21	.	.	PUNCT
cana-1862	172	1	where	where	SCONJ
cana-1862	172	2	the	the	DET
cana-1862	172	3	mutual	mutual	ADJ
cana-1862	172	4	information	information	NOUN
cana-1862	172	5	is	be	AUX
cana-1862	172	6	:	:	PUNCT
cana-1862	172	7	𝐼(𝑋	𝐼(𝑋	PROPN
cana-1862	172	8	;	;	PUNCT
cana-1862	172	9	𝑌	𝑌	PROPN
cana-1862	172	10	)	)	PUNCT
cana-1862	172	11	=	=	PUNCT
cana-1862	173	1	∑	∑	PUNCT
cana-1862	173	2	𝑥∈𝑋	𝑥∈𝑋	PROPN
cana-1862	173	3	∑	∑	PROPN
cana-1862	173	4	𝑦∈𝑌	𝑦∈𝑌	PROPN
cana-1862	173	5	𝑝(𝑥	𝑝(𝑥	PROPN
cana-1862	173	6	,	,	PUNCT
cana-1862	173	7	𝑦)𝑙𝑜𝑔	𝑦)𝑙𝑜𝑔	PROPN
cana-1862	173	8	(	(	PUNCT
cana-1862	173	9	𝑝(𝑥	𝑝(𝑥	PROPN
cana-1862	173	10	,	,	PUNCT
cana-1862	173	11	𝑦	𝑦	NOUN
cana-1862	173	12	)	)	PUNCT
cana-1862	173	13	𝑝(𝑥)𝑝(𝑦	𝑝(𝑥)𝑝(𝑦	NOUN
cana-1862	173	14	)	)	PUNCT
cana-1862	173	15	)	)	PUNCT
cana-1862	173	16	.	.	PUNCT
cana-1862	174	1	normalization	normalization	NOUN
cana-1862	174	2	:	:	PUNCT
cana-1862	174	3	normalization	normalization	NOUN
cana-1862	174	4	will	will	AUX
cana-1862	174	5	be	be	AUX
cana-1862	174	6	used	use	VERB
cana-1862	174	7	some	some	DET
cana-1862	174	8	normalization	normalization	NOUN
cana-1862	174	9	method	method	NOUN
cana-1862	174	10	like	like	ADP
cana-1862	174	11	min	min	NOUN
cana-1862	174	12	-	-	ADJ
cana-1862	174	13	max	max	ADJ
cana-1862	174	14	scaling	scaling	NOUN
cana-1862	174	15	or	or	CCONJ
cana-1862	174	16	zscore	zscore	NOUN
cana-1862	174	17	normalization	normalization	NOUN
cana-1862	174	18	to	to	PART
cana-1862	174	19	normalize	normalize	VERB
cana-1862	174	20	the	the	DET
cana-1862	174	21	attribute	attribute	NOUN
cana-1862	174	22	.	.	PUNCT
cana-1862	175	1	this	this	DET
cana-1862	175	2	method	method	NOUN
cana-1862	175	3	is	be	AUX
cana-1862	175	4	useful	useful	ADJ
cana-1862	175	5	when	when	SCONJ
cana-1862	175	6	we	we	PRON
cana-1862	175	7	perform	perform	VERB
cana-1862	175	8	this	this	DET
cana-1862	175	9	type	type	NOUN
cana-1862	175	10	of	of	ADP
cana-1862	175	11	algorithm	algorithm	NOUN
cana-1862	175	12	which	which	PRON
cana-1862	175	13	is	be	AUX
cana-1862	175	14	very	very	ADV
cana-1862	175	15	sensitive	sensitive	ADJ
cana-1862	175	16	to	to	ADP
cana-1862	175	17	the	the	DET
cana-1862	175	18	scale	scale	NOUN
cana-1862	175	19	of	of	ADP
cana-1862	175	20	data	datum	NOUN
cana-1862	175	21	like	like	ADP
cana-1862	175	22	the	the	DET
cana-1862	175	23	algorithms	algorithm	NOUN
cana-1862	175	24	scaling	scale	VERB
cana-1862	175	25	with	with	ADP
cana-1862	175	26	a	a	DET
cana-1862	175	27	fixed	fix	VERB
cana-1862	175	28	length	length	NOUN
cana-1862	175	29	output	output	NOUN
cana-1862	175	30	.	.	PUNCT
cana-1862	176	1	communications	communication	NOUN
cana-1862	176	2	on	on	ADP
cana-1862	176	3	applied	apply	VERB
cana-1862	176	4	nonlinear	nonlinear	ADJ
cana-1862	176	5	analysis	analysis	NOUN
cana-1862	176	6	issn	issn	NOUN
cana-1862	176	7	:	:	PUNCT
cana-1862	176	8	1074	1074	NUM
cana-1862	176	9	-	-	PUNCT
cana-1862	176	10	133x	133x	NUM
cana-1862	176	11	vol	vol	NOUN
cana-1862	176	12	32	32	NUM
cana-1862	176	13	no	no	NOUN
cana-1862	176	14	.	.	NOUN
cana-1862	176	15	2	2	NUM
cana-1862	176	16	(	(	PUNCT
cana-1862	176	17	2025	2025	NUM
cana-1862	176	18	)	)	PUNCT
cana-1862	176	19	702	702	NUM
cana-1862	176	20	https://internationalpubls.com	https://internationalpubls.com	X
cana-1862	176	21	since	since	SCONJ
cana-1862	176	22	the	the	DET
cana-1862	176	23	number	number	NOUN
cana-1862	176	24	of	of	ADP
cana-1862	176	25	features	feature	NOUN
cana-1862	176	26	for	for	ADP
cana-1862	176	27	network	network	NOUN
cana-1862	176	28	traffic	traffic	NOUN
cana-1862	176	29	data	datum	NOUN
cana-1862	176	30	are	be	AUX
cana-1862	176	31	very	very	ADV
cana-1862	176	32	high	high	ADJ
cana-1862	176	33	,	,	PUNCT
cana-1862	176	34	pca	pca	PROPN
cana-1862	176	35	has	have	AUX
cana-1862	176	36	been	be	AUX
cana-1862	176	37	used	use	VERB
cana-1862	176	38	to	to	PART
cana-1862	176	39	reduce	reduce	VERB
cana-1862	176	40	the	the	DET
cana-1862	176	41	feature	feature	NOUN
cana-1862	176	42	space	space	NOUN
cana-1862	176	43	while	while	SCONJ
cana-1862	176	44	retaining	retain	VERB
cana-1862	176	45	maximum	maximum	ADJ
cana-1862	176	46	variance	variance	NOUN
cana-1862	176	47	in	in	ADP
cana-1862	176	48	the	the	DET
cana-1862	176	49	data	datum	NOUN
cana-1862	176	50	.	.	PUNCT
cana-1862	177	1	in	in	ADP
cana-1862	177	2	mathematical	mathematical	ADJ
cana-1862	177	3	terms	term	NOUN
cana-1862	177	4	,	,	PUNCT
cana-1862	177	5	pca	pca	NOUN
cana-1862	177	6	projects	project	VERB
cana-1862	177	7	the	the	DET
cana-1862	177	8	input	input	NOUN
cana-1862	177	9	data	datum	NOUN
cana-1862	177	10	into	into	ADP
cana-1862	177	11	a	a	DET
cana-1862	177	12	lower	lower	ADV
cana-1862	177	13	-	-	PUNCT
cana-1862	177	14	dimensional	dimensional	ADJ
cana-1862	177	15	subspace	subspace	NOUN
cana-1862	177	16	by	by	ADP
cana-1862	177	17	finding	find	VERB
cana-1862	177	18	eigenvectors	eigenvector	NOUN
cana-1862	177	19	of	of	ADP
cana-1862	177	20	the	the	DET
cana-1862	177	21	covariance	covariance	NOUN
cana-1862	177	22	matrix	matrix	NOUN
cana-1862	177	23	of	of	ADP
cana-1862	177	24	the	the	DET
cana-1862	177	25	input	input	NOUN
cana-1862	177	26	data	datum	NOUN
cana-1862	177	27	.	.	PUNCT
cana-1862	178	1	this	this	PRON
cana-1862	178	2	helps	help	VERB
cana-1862	178	3	alleviate	alleviate	VERB
cana-1862	178	4	the	the	DET
cana-1862	178	5	“	"	PUNCT
cana-1862	178	6	curse	curse	NOUN
cana-1862	178	7	of	of	ADP
cana-1862	178	8	dimensionality	dimensionality	NOUN
cana-1862	178	9	,	,	PUNCT
cana-1862	178	10	”	"	PUNCT
cana-1862	178	11	and	and	CCONJ
cana-1862	178	12	will	will	AUX
cana-1862	178	13	help	help	VERB
cana-1862	178	14	you	you	PRON
cana-1862	178	15	train	train	VERB
cana-1862	178	16	your	your	PRON
cana-1862	178	17	machine	machine	NOUN
cana-1862	178	18	learning	learn	VERB
cana-1862	178	19	model	model	NOUN
cana-1862	178	20	better	well	ADV
cana-1862	178	21	.	.	PUNCT
cana-1862	179	1	●	●	PUNCT
cana-1862	179	2	model	model	NOUN
cana-1862	179	3	selection	selection	NOUN
cana-1862	179	4	and	and	CCONJ
cana-1862	179	5	mathematical	mathematical	ADJ
cana-1862	179	6	machines	machine	NOUN
cana-1862	179	7	this	this	DET
cana-1862	179	8	section	section	NOUN
cana-1862	179	9	introduces	introduce	VERB
cana-1862	179	10	several	several	ADJ
cana-1862	179	11	machine	machine	NOUN
cana-1862	179	12	learning	learning	NOUN
cana-1862	179	13	models	model	NOUN
cana-1862	179	14	,	,	PUNCT
cana-1862	179	15	in	in	ADP
cana-1862	179	16	each	each	PRON
cana-1862	179	17	of	of	ADP
cana-1862	179	18	which	which	PRON
cana-1862	179	19	a	a	DET
cana-1862	179	20	set	set	NOUN
cana-1862	179	21	of	of	ADP
cana-1862	179	22	different	different	ADJ
cana-1862	179	23	mathematical	mathematical	ADJ
cana-1862	179	24	operations	operation	NOUN
cana-1862	179	25	are	be	AUX
cana-1862	179	26	applied	apply	VERB
cana-1862	179	27	to	to	PART
cana-1862	179	28	improve	improve	VERB
cana-1862	179	29	the	the	DET
cana-1862	179	30	security	security	NOUN
cana-1862	179	31	detection	detection	NOUN
cana-1862	179	32	capability	capability	NOUN
cana-1862	179	33	.	.	PUNCT
cana-1862	180	1	the	the	DET
cana-1862	180	2	models	model	NOUN
cana-1862	180	3	,	,	PUNCT
cana-1862	180	4	in	in	ADP
cana-1862	180	5	turn	turn	NOUN
cana-1862	180	6	,	,	PUNCT
cana-1862	180	7	are	be	AUX
cana-1862	180	8	chosen	choose	VERB
cana-1862	180	9	to	to	PART
cana-1862	180	10	protect	protect	VERB
cana-1862	180	11	against	against	ADP
cana-1862	180	12	various	various	ADJ
cana-1862	180	13	kinds	kind	NOUN
cana-1862	180	14	of	of	ADP
cana-1862	180	15	cyber	cyber	NOUN
cana-1862	180	16	security	security	NOUN
cana-1862	180	17	threats	threat	NOUN
cana-1862	180	18	from	from	ADP
cana-1862	180	19	known	know	VERB
cana-1862	180	20	vulnerabilities	vulnerability	NOUN
cana-1862	180	21	to	to	ADP
cana-1862	180	22	zeroday	zeroday	NOUN
cana-1862	180	23	exploits	exploit	NOUN
cana-1862	180	24	.	.	PUNCT
cana-1862	181	1	supervised	supervise	VERB
cana-1862	181	2	learning	learning	NOUN
cana-1862	181	3	models	model	NOUN
cana-1862	181	4	:	:	PUNCT
cana-1862	181	5	for	for	ADP
cana-1862	181	6	this	this	DET
cana-1862	181	7	purpose	purpose	NOUN
cana-1862	181	8	,	,	PUNCT
cana-1862	181	9	the	the	DET
cana-1862	181	10	supervised	supervised	ADJ
cana-1862	181	11	learning	learning	NOUN
cana-1862	181	12	approach	approach	NOUN
cana-1862	181	13	is	be	AUX
cana-1862	181	14	quite	quite	ADV
cana-1862	181	15	helpful	helpful	ADJ
cana-1862	181	16	if	if	SCONJ
cana-1862	181	17	there	there	PRON
cana-1862	181	18	are	be	VERB
cana-1862	181	19	enough	enough	ADJ
cana-1862	181	20	labeled	label	VERB
cana-1862	181	21	datasets	dataset	NOUN
cana-1862	181	22	in	in	ADP
cana-1862	181	23	line	line	NOUN
cana-1862	181	24	with	with	ADP
cana-1862	181	25	the	the	DET
cana-1862	181	26	malicious	malicious	ADJ
cana-1862	181	27	traffic	traffic	NOUN
cana-1862	181	28	involved	involve	VERB
cana-1862	181	29	.	.	PUNCT
cana-1862	182	1	these	these	DET
cana-1862	182	2	models	model	NOUN
cana-1862	182	3	extract	extract	VERB
cana-1862	182	4	patterns	pattern	NOUN
cana-1862	182	5	hidden	hide	VERB
cana-1862	182	6	in	in	ADP
cana-1862	182	7	the	the	DET
cana-1862	182	8	labelled	label	VERB
cana-1862	182	9	data	datum	NOUN
cana-1862	182	10	,	,	PUNCT
cana-1862	182	11	and	and	CCONJ
cana-1862	182	12	use	use	VERB
cana-1862	182	13	them	they	PRON
cana-1862	182	14	to	to	PART
cana-1862	182	15	classify	classify	VERB
cana-1862	182	16	new	new	ADJ
cana-1862	182	17	instances	instance	NOUN
cana-1862	182	18	that	that	PRON
cana-1862	182	19	were	be	AUX
cana-1862	182	20	not	not	PART
cana-1862	182	21	seen	see	VERB
cana-1862	182	22	during	during	ADP
cana-1862	182	23	the	the	DET
cana-1862	182	24	training	training	NOUN
cana-1862	182	25	of	of	ADP
cana-1862	182	26	the	the	DET
cana-1862	182	27	model	model	NOUN
cana-1862	182	28	.	.	PUNCT
cana-1862	183	1	o	o	X
cana-1862	183	2	logistic	logistic	ADJ
cana-1862	183	3	regression	regression	NOUN
cana-1862	183	4	(	(	PUNCT
cana-1862	183	5	lr	lr	INTJ
cana-1862	183	6	):	):	PUNCT
cana-1862	183	7	logistic	logistic	ADJ
cana-1862	183	8	regression	regression	NOUN
cana-1862	183	9	:	:	PUNCT
cana-1862	183	10	logistic	logistic	ADJ
cana-1862	183	11	regression	regression	NOUN
cana-1862	183	12	is	be	AUX
cana-1862	183	13	a	a	DET
cana-1862	183	14	linear	linear	ADJ
cana-1862	183	15	model	model	NOUN
cana-1862	183	16	used	use	VERB
cana-1862	183	17	for	for	ADP
cana-1862	183	18	binary	binary	ADJ
cana-1862	183	19	classification	classification	NOUN
cana-1862	183	20	problems	problem	NOUN
cana-1862	183	21	.	.	PUNCT
cana-1862	184	1	the	the	DET
cana-1862	184	2	logistic	logistic	ADJ
cana-1862	184	3	regression	regression	NOUN
cana-1862	184	4	models	model	VERB
cana-1862	184	5	the	the	DET
cana-1862	184	6	probability	probability	NOUN
cana-1862	184	7	that	that	SCONJ
cana-1862	184	8	a	a	DET
cana-1862	184	9	binary	binary	ADJ
cana-1862	184	10	outcome	outcome	NOUN
cana-1862	184	11	is	be	AUX
cana-1862	184	12	1	1	NUM
cana-1862	184	13	.	.	PUNCT
cana-1862	185	1	𝑃(𝑦	𝑃(𝑦	X
cana-1862	185	2	=	=	SYM
cana-1862	185	3	1	1	NUM
cana-1862	185	4	∣	∣	PROPN
cana-1862	185	5	𝑋	𝑋	PROPN
cana-1862	185	6	)	)	PUNCT
cana-1862	185	7	=	=	SYM
cana-1862	186	1	1	1	NUM
cana-1862	186	2	1	1	NUM
cana-1862	186	3	+	+	NUM
cana-1862	186	4	𝑒−(𝛽0+𝛽1𝑋1+⋯+𝛽𝑑𝑋𝑑	𝑒−(𝛽0+𝛽1𝑋1+⋯+𝛽𝑑𝑋𝑑	NUM
cana-1862	186	5	)	)	PUNCT
cana-1862	186	6	,	,	PUNCT
cana-1862	186	7	where	where	SCONJ
cana-1862	186	8	,	,	PUNCT
cana-1862	186	9	𝛽0	𝛽0	NOUN
cana-1862	186	10	,	,	PUNCT
cana-1862	186	11	𝛽1	𝛽1	NOUN
cana-1862	186	12	,	,	PUNCT
cana-1862	186	13	…	…	PUNCT
cana-1862	186	14	,	,	PUNCT
cana-1862	186	15	𝛽𝑑	𝛽𝑑	X
cana-1862	186	16	are	be	AUX
cana-1862	186	17	the	the	DET
cana-1862	186	18	model	model	NOUN
cana-1862	186	19	parameters	parameter	NOUN
cana-1862	186	20	learned	learn	VERB
cana-1862	186	21	during	during	ADP
cana-1862	186	22	training	training	NOUN
cana-1862	186	23	,	,	PUNCT
cana-1862	186	24	and	and	CCONJ
cana-1862	186	25	𝑋1	𝑋1	PROPN
cana-1862	186	26	,	,	PUNCT
cana-1862	186	27	…	…	PUNCT
cana-1862	186	28	,	,	PUNCT
cana-1862	186	29	𝑋𝑑	𝑋𝑑	NOUN
cana-1862	186	30	are	be	AUX
cana-1862	186	31	the	the	DET
cana-1862	186	32	input	input	NOUN
cana-1862	186	33	features	feature	NOUN
cana-1862	186	34	.	.	PUNCT
cana-1862	187	1	the	the	DET
cana-1862	187	2	model	model	NOUN
cana-1862	187	3	is	be	AUX
cana-1862	187	4	trained	train	VERB
cana-1862	187	5	by	by	ADP
cana-1862	187	6	maximizing	maximize	VERB
cana-1862	187	7	the	the	DET
cana-1862	187	8	likelihood	likelihood	NOUN
cana-1862	187	9	of	of	ADP
cana-1862	187	10	the	the	DET
cana-1862	187	11	observed	observed	ADJ
cana-1862	187	12	outcomes	outcome	NOUN
cana-1862	187	13	,	,	PUNCT
cana-1862	187	14	which	which	PRON
cana-1862	187	15	is	be	AUX
cana-1862	187	16	mathematically	mathematically	ADV
cana-1862	187	17	equivalent	equivalent	ADJ
cana-1862	187	18	to	to	ADP
cana-1862	187	19	minimizing	minimize	VERB
cana-1862	187	20	the	the	DET
cana-1862	187	21	cross	cross	ADJ
cana-1862	187	22	-	-	ADJ
cana-1862	187	23	entropy	entropy	ADJ
cana-1862	187	24	loss	loss	NOUN
cana-1862	187	25	function	function	NOUN
cana-1862	187	26	:	:	PUNCT
cana-1862	187	27	𝐿(𝛽	𝐿(𝛽	X
cana-1862	187	28	)	)	PUNCT
cana-1862	187	29	=	=	SYM
cana-1862	188	1	−	−	PROPN
cana-1862	188	2	∑	∑	PUNCT
cana-1862	188	3	𝑛	𝑛	PRON
cana-1862	188	4	𝑖=1	𝑖=1	PROPN
cana-1862	189	1	[	[	X
cana-1862	189	2	𝑦𝑖𝑙𝑜𝑔𝑃(𝑦𝑖	𝑦𝑖𝑙𝑜𝑔𝑃(𝑦𝑖	NUM
cana-1862	189	3	)	)	PUNCT
cana-1862	189	4	+	+	CCONJ
cana-1862	189	5	(	(	PUNCT
cana-1862	189	6	1	1	NUM
cana-1862	189	7	−	−	PROPN
cana-1862	189	8	𝑦𝑖)𝑙𝑜𝑔(1	𝑦𝑖)𝑙𝑜𝑔(1	PROPN
cana-1862	189	9	−	−	PROPN
cana-1862	189	10	𝑃(𝑦𝑖	𝑃(𝑦𝑖	ADV
cana-1862	189	11	)	)	PUNCT
cana-1862	189	12	)	)	PUNCT
cana-1862	189	13	]	]	PUNCT
cana-1862	189	14	.	.	PUNCT
cana-1862	190	1	logistic	logistic	ADJ
cana-1862	190	2	regression	regression	NOUN
cana-1862	190	3	provides	provide	VERB
cana-1862	190	4	interpretable	interpretable	ADJ
cana-1862	190	5	results	result	NOUN
cana-1862	190	6	,	,	PUNCT
cana-1862	190	7	with	with	ADP
cana-1862	190	8	the	the	DET
cana-1862	190	9	coefficients	coefficient	NOUN
cana-1862	191	1	𝛽𝑗	𝛽𝑗	NOUN
cana-1862	191	2	indicating	indicate	VERB
cana-1862	191	3	the	the	DET
cana-1862	191	4	impact	impact	NOUN
cana-1862	191	5	of	of	ADP
cana-1862	191	6	each	each	DET
cana-1862	191	7	feature	feature	NOUN
cana-1862	191	8	on	on	ADP
cana-1862	191	9	the	the	DET
cana-1862	191	10	vulnerability	vulnerability	NOUN
cana-1862	191	11	prediction	prediction	NOUN
cana-1862	191	12	.	.	PUNCT
cana-1862	192	1	however	however	ADV
cana-1862	192	2	,	,	PUNCT
cana-1862	192	3	it	it	PRON
cana-1862	192	4	may	may	AUX
cana-1862	192	5	struggle	struggle	VERB
cana-1862	192	6	with	with	ADP
cana-1862	192	7	complex	complex	ADJ
cana-1862	192	8	relationships	relationship	NOUN
cana-1862	192	9	in	in	ADP
cana-1862	192	10	high	high	ADJ
cana-1862	192	11	-	-	PUNCT
cana-1862	192	12	dimensional	dimensional	ADJ
cana-1862	192	13	data	datum	NOUN
cana-1862	192	14	,	,	PUNCT
cana-1862	192	15	necessitating	necessitate	VERB
cana-1862	192	16	more	more	ADV
cana-1862	192	17	sophisticated	sophisticated	ADJ
cana-1862	192	18	models	model	NOUN
cana-1862	192	19	.	.	PUNCT
cana-1862	193	1	o	o	X
cana-1862	193	2	decision	decision	NOUN
cana-1862	193	3	trees	tree	NOUN
cana-1862	193	4	and	and	CCONJ
cana-1862	193	5	ensemble	ensemble	ADJ
cana-1862	193	6	techniques	technique	NOUN
cana-1862	193	7	in	in	ADP
cana-1862	193	8	decision	decision	NOUN
cana-1862	193	9	tree	tree	NOUN
cana-1862	193	10	data	datum	NOUN
cana-1862	193	11	is	be	AUX
cana-1862	193	12	divided	divide	VERB
cana-1862	193	13	among	among	ADP
cana-1862	193	14	subgroups	subgroup	NOUN
cana-1862	193	15	based	base	VERB
cana-1862	193	16	on	on	ADP
cana-1862	193	17	feature	feature	NOUN
cana-1862	193	18	values	value	NOUN
cana-1862	193	19	using	use	VERB
cana-1862	193	20	either	either	CCONJ
cana-1862	193	21	gini	gini	NOUN
cana-1862	193	22	impurity	impurity	NOUN
cana-1862	193	23	or	or	CCONJ
cana-1862	193	24	information	information	NOUN
cana-1862	193	25	gain	gain	VERB
cana-1862	193	26	measures	measure	NOUN
cana-1862	193	27	for	for	ADP
cana-1862	193	28	selecting	select	VERB
cana-1862	193	29	a	a	DET
cana-1862	193	30	split	split	NOUN
cana-1862	193	31	.	.	PUNCT
cana-1862	194	1	the	the	DET
cana-1862	194	2	gini	gini	PROPN
cana-1862	194	3	impurity	impurity	NOUN
cana-1862	194	4	for	for	ADP
cana-1862	194	5	a	a	DET
cana-1862	194	6	binary	binary	ADJ
cana-1862	194	7	split	split	NOUN
cana-1862	194	8	is	be	AUX
cana-1862	194	9	represented	represent	VERB
cana-1862	194	10	by	by	ADP
cana-1862	194	11	:	:	PUNCT
cana-1862	194	12	𝐺	𝐺	NOUN
cana-1862	194	13	=	=	NOUN
cana-1862	194	14	1	1	NUM
cana-1862	194	15	−	−	PROPN
cana-1862	194	16	𝑝1	𝑝1	NOUN
cana-1862	194	17	2	2	NUM
cana-1862	194	18	−	−	PROPN
cana-1862	194	19	𝑝2	𝑝2	NOUN
cana-1862	194	20	2	2	NUM
cana-1862	194	21	,	,	PUNCT
cana-1862	194	22	where	where	SCONJ
cana-1862	194	23	,	,	PUNCT
cana-1862	194	24	𝑝1	𝑝1	NOUN
cana-1862	194	25	and	and	CCONJ
cana-1862	194	26	𝑝2	𝑝2	NOUN
cana-1862	194	27	are	be	AUX
cana-1862	194	28	the	the	DET
cana-1862	194	29	proportions	proportion	NOUN
cana-1862	194	30	of	of	ADP
cana-1862	194	31	the	the	DET
cana-1862	194	32	two	two	NUM
cana-1862	194	33	classes	class	NOUN
cana-1862	194	34	in	in	ADP
cana-1862	194	35	a	a	DET
cana-1862	194	36	node	node	NOUN
cana-1862	194	37	.	.	PUNCT
cana-1862	195	1	decision	decision	NOUN
cana-1862	195	2	trees	tree	NOUN
cana-1862	195	3	recursively	recursively	ADV
cana-1862	195	4	partition	partition	VERB
cana-1862	195	5	the	the	DET
cana-1862	195	6	feature	feature	NOUN
cana-1862	195	7	space	space	NOUN
cana-1862	195	8	,	,	PUNCT
cana-1862	195	9	creating	create	VERB
cana-1862	195	10	a	a	DET
cana-1862	195	11	tree	tree	NOUN
cana-1862	195	12	structure	structure	NOUN
cana-1862	195	13	that	that	PRON
cana-1862	195	14	assigns	assign	VERB
cana-1862	195	15	labels	label	NOUN
cana-1862	195	16	to	to	ADP
cana-1862	195	17	data	datum	NOUN
cana-1862	195	18	points	point	NOUN
cana-1862	195	19	based	base	VERB
cana-1862	195	20	on	on	ADP
cana-1862	195	21	the	the	DET
cana-1862	195	22	learned	learn	VERB
cana-1862	195	23	rules	rule	NOUN
cana-1862	195	24	.	.	PUNCT
cana-1862	196	1	communications	communication	NOUN
cana-1862	196	2	on	on	ADP
cana-1862	196	3	applied	apply	VERB
cana-1862	196	4	nonlinear	nonlinear	ADJ
cana-1862	196	5	analysis	analysis	NOUN
cana-1862	196	6	issn	issn	NOUN
cana-1862	196	7	:	:	PUNCT
cana-1862	196	8	1074	1074	NUM
cana-1862	196	9	-	-	PUNCT
cana-1862	196	10	133x	133x	NUM
cana-1862	196	11	vol	vol	NOUN
cana-1862	196	12	32	32	NUM
cana-1862	196	13	no	no	NOUN
cana-1862	196	14	.	.	NOUN
cana-1862	196	15	2	2	NUM
cana-1862	196	16	(	(	PUNCT
cana-1862	196	17	2025	2025	NUM
cana-1862	196	18	)	)	PUNCT
cana-1862	196	19	703	703	NUM
cana-1862	196	20	https://internationalpubls.com	https://internationalpubls.com	X
cana-1862	196	21	algorithm	algorithm	NOUN
cana-1862	196	22	for	for	ADP
cana-1862	196	23	random	random	ADJ
cana-1862	196	24	forest	forest	NOUN
cana-1862	196	25	:	:	PUNCT
cana-1862	197	1	1	1	X
cana-1862	197	2	.	.	X
cana-1862	197	3	input	input	NOUN
cana-1862	197	4	:	:	PUNCT
cana-1862	197	5	training	training	NOUN
cana-1862	197	6	dataset	dataset	NOUN
cana-1862	197	7	𝐷	𝐷	NOUN
cana-1862	197	8	=	=	SYM
cana-1862	197	9	{	{	PUNCT
cana-1862	197	10	(	(	PUNCT
cana-1862	197	11	𝑥1	𝑥1	NOUN
cana-1862	197	12	,	,	PUNCT
cana-1862	197	13	𝑦1	𝑦1	NOUN
cana-1862	197	14	)	)	PUNCT
cana-1862	197	15	,	,	PUNCT
cana-1862	197	16	(	(	PUNCT
cana-1862	197	17	𝑥2	𝑥2	NOUN
cana-1862	197	18	,	,	PUNCT
cana-1862	197	19	𝑦2	𝑦2	PROPN
cana-1862	197	20	)	)	PUNCT
cana-1862	197	21	,	,	PUNCT
cana-1862	197	22	…	…	PUNCT
cana-1862	197	23	,	,	PUNCT
cana-1862	197	24	(	(	PUNCT
cana-1862	197	25	𝑥𝑛	𝑥𝑛	NOUN
cana-1862	197	26	,	,	PUNCT
cana-1862	197	27	𝑦𝑛	𝑦𝑛	NOUN
cana-1862	197	28	)	)	PUNCT
cana-1862	197	29	}	}	PUNCT
cana-1862	197	30	.	.	PUNCT
cana-1862	198	1	2	2	X
cana-1862	198	2	.	.	X
cana-1862	198	3	for	for	ADP
cana-1862	198	4	each	each	DET
cana-1862	198	5	tree	tree	NOUN
cana-1862	198	6	in	in	ADP
cana-1862	198	7	the	the	DET
cana-1862	198	8	forest	forest	NOUN
cana-1862	198	9	:	:	PUNCT
cana-1862	198	10	sample	sample	NOUN
cana-1862	198	11	𝑁	𝑁	PROPN
cana-1862	198	12	data	data	NOUN
cana-1862	198	13	points	point	NOUN
cana-1862	198	14	from	from	ADP
cana-1862	198	15	𝐷	𝐷	PROPN
cana-1862	198	16	with	with	ADP
cana-1862	198	17	replacement	replacement	NOUN
cana-1862	198	18	.	.	PUNCT
cana-1862	199	1	select	select	VERB
cana-1862	199	2	a	a	DET
cana-1862	199	3	random	random	ADJ
cana-1862	199	4	subset	subset	NOUN
cana-1862	199	5	of	of	ADP
cana-1862	199	6	features	feature	NOUN
cana-1862	199	7	.	.	PUNCT
cana-1862	200	1	construct	construct	VERB
cana-1862	200	2	a	a	DET
cana-1862	200	3	decision	decision	NOUN
cana-1862	200	4	tree	tree	NOUN
cana-1862	200	5	based	base	VERB
cana-1862	200	6	on	on	ADP
cana-1862	200	7	the	the	DET
cana-1862	200	8	selected	select	VERB
cana-1862	200	9	features	feature	NOUN
cana-1862	200	10	.	.	PUNCT
cana-1862	201	1	3	3	X
cana-1862	201	2	.	.	NOUN
cana-1862	201	3	during	during	ADP
cana-1862	201	4	prediction	prediction	NOUN
cana-1862	201	5	,	,	PUNCT
cana-1862	201	6	aggregate	aggregate	VERB
cana-1862	201	7	the	the	DET
cana-1862	201	8	results	result	NOUN
cana-1862	201	9	from	from	ADP
cana-1862	201	10	all	all	DET
cana-1862	201	11	trees	tree	NOUN
cana-1862	201	12	(	(	PUNCT
cana-1862	201	13	majority	majority	NOUN
cana-1862	201	14	voting	voting	NOUN
cana-1862	201	15	)	)	PUNCT
cana-1862	201	16	.	.	PUNCT
cana-1862	202	1	4	4	X
cana-1862	202	2	.	.	X
cana-1862	202	3	output	output	NOUN
cana-1862	202	4	:	:	PUNCT
cana-1862	202	5	predicted	predict	VERB
cana-1862	202	6	class	class	NOUN
cana-1862	202	7	for	for	ADP
cana-1862	202	8	the	the	DET
cana-1862	202	9	input	input	NOUN
cana-1862	202	10	data	datum	NOUN
cana-1862	202	11	.	.	PUNCT
cana-1862	203	1	random	random	ADJ
cana-1862	203	2	forests	forest	NOUN
cana-1862	203	3	use	use	VERB
cana-1862	203	4	information	information	NOUN
cana-1862	203	5	gain	gain	NOUN
cana-1862	203	6	or	or	CCONJ
cana-1862	203	7	gini	gini	NOUN
cana-1862	203	8	impurity	impurity	NOUN
cana-1862	203	9	to	to	PART
cana-1862	203	10	split	split	VERB
cana-1862	203	11	nodes	node	NOUN
cana-1862	203	12	in	in	ADP
cana-1862	203	13	each	each	DET
cana-1862	203	14	decision	decision	NOUN
cana-1862	203	15	tree	tree	NOUN
cana-1862	203	16	.	.	PUNCT
cana-1862	204	1	for	for	ADP
cana-1862	204	2	gini	gini	PROPN
cana-1862	204	3	impurity	impurity	NOUN
cana-1862	204	4	,	,	PUNCT
cana-1862	204	5	the	the	DET
cana-1862	204	6	split	split	ADJ
cana-1862	204	7	criterion	criterion	NOUN
cana-1862	204	8	is	be	AUX
cana-1862	204	9	:	:	PUNCT
cana-1862	204	10	𝐺	𝐺	NOUN
cana-1862	204	11	=	=	NOUN
cana-1862	204	12	1	1	NUM
cana-1862	204	13	−	−	PROPN
cana-1862	204	14	∑	∑	PUNCT
cana-1862	204	15	𝐶	𝐶	PROPN
cana-1862	204	16	𝑖=1	𝑖=1	PROPN
cana-1862	204	17	𝑝𝑖	𝑝𝑖	PROPN
cana-1862	204	18	2	2	NUM
cana-1862	204	19	,	,	PUNCT
cana-1862	204	20	where	where	SCONJ
cana-1862	204	21	𝑝𝑖	𝑝𝑖	NOUN
cana-1862	204	22	is	be	AUX
cana-1862	204	23	the	the	DET
cana-1862	204	24	probability	probability	NOUN
cana-1862	204	25	of	of	ADP
cana-1862	204	26	selecting	select	VERB
cana-1862	204	27	a	a	DET
cana-1862	204	28	class	class	NOUN
cana-1862	204	29	𝑖	𝑖	NOUN
cana-1862	204	30	from	from	ADP
cana-1862	204	31	the	the	DET
cana-1862	204	32	node	node	NOUN
cana-1862	204	33	,	,	PUNCT
cana-1862	204	34	and	and	CCONJ
cana-1862	204	35	𝐶	𝐶	PROPN
cana-1862	204	36	is	be	AUX
cana-1862	204	37	the	the	DET
cana-1862	204	38	total	total	ADJ
cana-1862	204	39	number	number	NOUN
cana-1862	204	40	of	of	ADP
cana-1862	204	41	classes	class	NOUN
cana-1862	204	42	.	.	PUNCT
cana-1862	205	1	ensemble	ensemble	ADJ
cana-1862	205	2	methods	method	NOUN
cana-1862	205	3	:	:	PUNCT
cana-1862	205	4	do	do	AUX
cana-1862	205	5	n't	not	PART
cana-1862	205	6	put	put	VERB
cana-1862	205	7	all	all	DET
cana-1862	205	8	your	your	PRON
cana-1862	205	9	eggs	egg	NOUN
cana-1862	205	10	in	in	ADP
cana-1862	205	11	one	one	NUM
cana-1862	205	12	basket	basket	NOUN
cana-1862	205	13	ensemble	ensemble	ADJ
cana-1862	205	14	methods	method	NOUN
cana-1862	205	15	,	,	PUNCT
cana-1862	205	16	like	like	ADP
cana-1862	205	17	random	random	ADJ
cana-1862	205	18	forests	forest	NOUN
cana-1862	205	19	and	and	CCONJ
cana-1862	205	20	gradient	gradient	NOUN
cana-1862	205	21	boosting	boost	VERB
cana-1862	205	22	(	(	PUNCT
cana-1862	205	23	xgboost	xgboost	ADV
cana-1862	205	24	)	)	PUNCT
cana-1862	205	25	,	,	PUNCT
cana-1862	205	26	build	build	VERB
cana-1862	205	27	multiple	multiple	ADJ
cana-1862	205	28	decision	decision	NOUN
cana-1862	205	29	trees	tree	NOUN
cana-1862	205	30	to	to	PART
cana-1862	205	31	increase	increase	VERB
cana-1862	205	32	performance	performance	NOUN
cana-1862	205	33	of	of	ADP
cana-1862	205	34	the	the	DET
cana-1862	205	35	model	model	NOUN
cana-1862	205	36	.	.	PUNCT
cana-1862	206	1	random	random	ADJ
cana-1862	206	2	forests	forest	NOUN
cana-1862	206	3	are	be	AUX
cana-1862	206	4	a	a	DET
cana-1862	206	5	special	special	ADJ
cana-1862	206	6	case	case	NOUN
cana-1862	206	7	of	of	ADP
cana-1862	206	8	bagging	bagging	NOUN
cana-1862	206	9	that	that	PRON
cana-1862	206	10	create	create	VERB
cana-1862	206	11	an	an	DET
cana-1862	206	12	ensemble	ensemble	NOUN
cana-1862	206	13	of	of	ADP
cana-1862	206	14	trees	tree	NOUN
cana-1862	206	15	by	by	ADP
cana-1862	206	16	randomly	randomly	ADV
cana-1862	206	17	choosing	choose	VERB
cana-1862	206	18	on	on	ADP
cana-1862	206	19	every	every	DET
cana-1862	206	20	tree	tree	NOUN
cana-1862	206	21	both	both	DET
cana-1862	206	22	data	datum	NOUN
cana-1862	206	23	(	(	PUNCT
cana-1862	206	24	a	a	DET
cana-1862	206	25	bootstrapped	bootstrapped	ADJ
cana-1862	206	26	sample	sample	NOUN
cana-1862	206	27	of	of	ADP
cana-1862	206	28	the	the	DET
cana-1862	206	29	training	training	NOUN
cana-1862	206	30	data	datum	NOUN
cana-1862	206	31	)	)	PUNCT
cana-1862	206	32	and	and	CCONJ
cana-1862	206	33	features	feature	NOUN
cana-1862	206	34	,	,	PUNCT
cana-1862	206	35	reducing	reduce	VERB
cana-1862	206	36	overfitting	overfitting	NOUN
cana-1862	206	37	.	.	PUNCT
cana-1862	207	1	the	the	DET
cana-1862	207	2	final	final	ADJ
cana-1862	207	3	prediction	prediction	NOUN
cana-1862	207	4	g	g	PROPN
cana-1862	207	5	(	(	PUNCT
cana-1862	207	6	ib	ib	INTJ
cana-1862	207	7	,	,	PUNCT
cana-1862	207	8	)	)	PUNCT
cana-1862	207	9	is	be	AUX
cana-1862	207	10	simply	simply	ADV
cana-1862	207	11	the	the	DET
cana-1862	207	12	average	average	NOUN
cana-1862	207	13	(	(	PUNCT
cana-1862	207	14	for	for	ADP
cana-1862	207	15	regression	regression	NOUN
cana-1862	207	16	)	)	PUNCT
cana-1862	207	17	or	or	CCONJ
cana-1862	207	18	majority	majority	NOUN
cana-1862	207	19	count	count	NOUN
cana-1862	207	20	(	(	PUNCT
cana-1862	207	21	for	for	ADP
cana-1862	207	22	classification	classification	NOUN
cana-1862	207	23	)	)	PUNCT
cana-1862	207	24	of	of	ADP
cana-1862	207	25	the	the	DET
cana-1862	207	26	predictions	prediction	NOUN
cana-1862	207	27	from	from	ADP
cana-1862	207	28	these	these	DET
cana-1862	207	29	trees	tree	NOUN
cana-1862	207	30	:	:	PUNCT
cana-1862	207	31	a(b	a(b	ADJ
cana-1862	207	32	,	,	PUNCT
cana-1862	207	33	,	,	PUNCT
cana-1862	207	34	,	,	PUNCT
cana-1862	207	35	,	,	PUNCT
cana-1862	207	36	θm	θm	PROPN
cana-1862	207	37	)	)	PUNCT
cana-1862	207	38	.	.	PUNCT
cana-1862	208	1	�	�	PROPN
cana-1862	208	2	̂	̂	VERB
cana-1862	208	3	�	�	NOUN
cana-1862	208	4	=	=	SYM
cana-1862	208	5	1	1	NUM
cana-1862	208	6	𝑁	𝑁	PROPN
cana-1862	208	7	∑	∑	PROPN
cana-1862	208	8	𝑁	𝑁	PROPN
cana-1862	208	9	𝑖=1	𝑖=1	PROPN
cana-1862	208	10	𝑇𝑖(𝑋	𝑇𝑖(𝑋	NUM
cana-1862	208	11	)	)	PUNCT
cana-1862	208	12	,	,	PUNCT
cana-1862	208	13	where	where	SCONJ
cana-1862	208	14	,	,	PUNCT
cana-1862	208	15	𝑇𝑖(𝑋	𝑇𝑖(𝑋	PUNCT
cana-1862	208	16	)	)	PUNCT
cana-1862	208	17	is	be	AUX
cana-1862	208	18	the	the	DET
cana-1862	208	19	prediction	prediction	NOUN
cana-1862	208	20	of	of	ADP
cana-1862	208	21	the	the	DET
cana-1862	208	22	𝑖-th	𝑖-th	PROPN
cana-1862	208	23	tree	tree	NOUN
cana-1862	208	24	,	,	PUNCT
cana-1862	208	25	and	and	CCONJ
cana-1862	208	26	𝑁	𝑁	PROPN
cana-1862	208	27	is	be	AUX
cana-1862	208	28	the	the	DET
cana-1862	208	29	total	total	ADJ
cana-1862	208	30	number	number	NOUN
cana-1862	208	31	of	of	ADP
cana-1862	208	32	trees	tree	NOUN
cana-1862	208	33	.	.	PUNCT
cana-1862	209	1	decision	decision	NOUN
cana-1862	209	2	trees	tree	NOUN
cana-1862	209	3	in	in	ADP
cana-1862	209	4	gradient	gradient	ADJ
cana-1862	209	5	boosting	boosting	NOUN
cana-1862	209	6	are	be	AUX
cana-1862	209	7	built	build	VERB
cana-1862	209	8	one	one	NUM
cana-1862	209	9	after	after	ADP
cana-1862	209	10	another	another	PRON
cana-1862	209	11	and	and	CCONJ
cana-1862	209	12	tree	tree	NOUN
cana-1862	209	13	building	building	NOUN
cana-1862	209	14	process	process	NOUN
cana-1862	209	15	minimizes	minimize	VERB
cana-1862	209	16	errors	error	NOUN
cana-1862	209	17	of	of	ADP
cana-1862	209	18	its	its	PRON
cana-1862	209	19	predecessor	predecessor	NOUN
cana-1862	209	20	.	.	PUNCT
cana-1862	210	1	in	in	ADP
cana-1862	210	2	gradient	gradient	ADJ
cana-1862	210	3	boosting	boosting	NOUN
cana-1862	210	4	,	,	PUNCT
cana-1862	210	5	the	the	DET
cana-1862	210	6	gradient	gradient	NOUN
cana-1862	210	7	boosted	boost	VERB
cana-1862	210	8	tree	tree	NOUN
cana-1862	210	9	minimizes	minimize	VERB
cana-1862	210	10	the	the	DET
cana-1862	210	11	objective	objective	ADJ
cana-1862	210	12	function	function	NOUN
cana-1862	210	13	which	which	PRON
cana-1862	210	14	is	be	AUX
cana-1862	210	15	made	make	VERB
cana-1862	210	16	up	up	ADP
cana-1862	210	17	of	of	ADP
cana-1862	210	18	a	a	DET
cana-1862	210	19	loss	loss	NOUN
cana-1862	210	20	function	function	NOUN
cana-1862	210	21	lll	lll	NOUN
cana-1862	210	22	and	and	CCONJ
cana-1862	210	23	a	a	DET
cana-1862	210	24	regularization	regularization	NOUN
cana-1862	210	25	term	term	NOUN
cana-1862	210	26	to	to	PART
cana-1862	210	27	control	control	VERB
cana-1862	210	28	model	model	NOUN
cana-1862	210	29	complexity	complexity	NOUN
cana-1862	210	30	.	.	PUNCT
cana-1862	211	1	if	if	SCONJ
cana-1862	211	2	we	we	PRON
cana-1862	211	3	are	be	AUX
cana-1862	211	4	to	to	PART
cana-1862	211	5	say	say	VERB
cana-1862	211	6	this	this	PRON
cana-1862	211	7	as	as	ADP
cana-1862	211	8	an	an	DET
cana-1862	211	9	example	example	NOUN
cana-1862	211	10	,	,	PUNCT
cana-1862	211	11	object	object	NOUN
cana-1862	211	12	is	be	AUX
cana-1862	211	13	something	something	PRON
cana-1862	211	14	like	like	ADP
cana-1862	211	15	the	the	DET
cana-1862	211	16	following	following	NOUN
cana-1862	211	17	in	in	ADP
cana-1862	211	18	xgboost	xgboost	PROPN
cana-1862	211	19	.	.	PUNCT
cana-1862	212	1	𝐿	𝐿	PROPN
cana-1862	212	2	=	=	SYM
cana-1862	212	3	∑	∑	PROPN
cana-1862	212	4	𝑛	𝑛	PRON
cana-1862	212	5	𝑖=1	𝑖=1	PROPN
cana-1862	212	6	𝑙(𝑦𝑖	𝑙(𝑦𝑖	PROPN
cana-1862	212	7	,	,	PUNCT
cana-1862	212	8	�	�	PROPN
cana-1862	212	9	̂	̂	NOUN
cana-1862	212	10	�	�	NOUN
cana-1862	212	11	𝑖	𝑖	NUM
cana-1862	212	12	)	)	PUNCT
cana-1862	212	13	+	+	CCONJ
cana-1862	212	14	∑	∑	PROPN
cana-1862	212	15	𝐾	𝐾	PROPN
cana-1862	212	16	𝑘=1	𝑘=1	PUNCT
cana-1862	212	17	𝛺(𝑓𝑘	𝛺(𝑓𝑘	PROPN
cana-1862	212	18	)	)	PUNCT
cana-1862	212	19	,	,	PUNCT
cana-1862	212	20	where	where	SCONJ
cana-1862	212	21	,	,	PUNCT
cana-1862	212	22	𝑙(𝑦𝑖	𝑙(𝑦𝑖	PRON
cana-1862	212	23	,	,	PUNCT
cana-1862	212	24	�	�	PROPN
cana-1862	212	25	̂	̂	VERB
cana-1862	212	26	�	�	NOUN
cana-1862	212	27	𝑖	𝑖	NUM
cana-1862	212	28	)	)	PUNCT
cana-1862	212	29	is	be	AUX
cana-1862	212	30	the	the	DET
cana-1862	212	31	loss	loss	NOUN
cana-1862	212	32	function	function	NOUN
cana-1862	212	33	(	(	PUNCT
cana-1862	212	34	e.g.	e.g.	ADV
cana-1862	212	35	,	,	PUNCT
cana-1862	212	36	squared	square	VERB
cana-1862	212	37	error	error	NOUN
cana-1862	212	38	for	for	ADP
cana-1862	212	39	regression	regression	NOUN
cana-1862	212	40	)	)	PUNCT
cana-1862	212	41	and	and	CCONJ
cana-1862	212	42	𝛺(𝑓𝑘	𝛺(𝑓𝑘	X
cana-1862	212	43	)	)	PUNCT
cana-1862	212	44	is	be	AUX
cana-1862	212	45	a	a	DET
cana-1862	212	46	regularization	regularization	NOUN
cana-1862	212	47	term	term	NOUN
cana-1862	212	48	that	that	PRON
cana-1862	212	49	penalizes	penalize	VERB
cana-1862	212	50	the	the	DET
cana-1862	212	51	complexity	complexity	NOUN
cana-1862	212	52	of	of	ADP
cana-1862	212	53	trees	tree	NOUN
cana-1862	212	54	𝑓𝑘.	𝑓𝑘.	ADP
cana-1862	212	55	o	o	NOUN
cana-1862	212	56	xgboost	xgboost	X
cana-1862	212	57	:	:	PUNCT
cana-1862	212	58	extreme	extreme	ADJ
cana-1862	212	59	gradient	gradient	NOUN
cana-1862	212	60	boosting	boost	VERB
cana-1862	212	61	xgboost	xgboost	NOUN
cana-1862	212	62	(	(	PUNCT
cana-1862	212	63	extreme	extreme	ADJ
cana-1862	212	64	gradient	gradient	NOUN
cana-1862	212	65	boosting	boosting	NOUN
cana-1862	212	66	)	)	PUNCT
cana-1862	212	67	is	be	AUX
cana-1862	212	68	a	a	DET
cana-1862	212	69	robust	robust	ADJ
cana-1862	212	70	ensemble	ensemble	ADJ
cana-1862	212	71	learning	learning	NOUN
cana-1862	212	72	method	method	NOUN
cana-1862	212	73	that	that	PRON
cana-1862	212	74	builds	build	VERB
cana-1862	212	75	an	an	DET
cana-1862	212	76	ensemble	ensemble	NOUN
cana-1862	212	77	of	of	ADP
cana-1862	212	78	decision	decision	NOUN
cana-1862	212	79	trees	tree	NOUN
cana-1862	212	80	for	for	ADP
cana-1862	212	81	predicting	predict	VERB
cana-1862	212	82	vulnerabilities	vulnerability	NOUN
cana-1862	212	83	in	in	ADP
cana-1862	212	84	network	network	NOUN
cana-1862	212	85	traffic	traffic	NOUN
cana-1862	212	86	.	.	PUNCT
cana-1862	213	1	this	this	DET
cana-1862	213	2	method	method	NOUN
cana-1862	213	3	uses	use	VERB
cana-1862	213	4	gradient	gradient	ADJ
cana-1862	213	5	boosting	boosting	NOUN
cana-1862	213	6	,	,	PUNCT
cana-1862	213	7	communications	communication	NOUN
cana-1862	213	8	on	on	ADP
cana-1862	213	9	applied	apply	VERB
cana-1862	213	10	nonlinear	nonlinear	ADJ
cana-1862	213	11	analysis	analysis	NOUN
cana-1862	213	12	issn	issn	NOUN
cana-1862	213	13	:	:	PUNCT
cana-1862	213	14	1074	1074	NUM
cana-1862	213	15	-	-	PUNCT
cana-1862	213	16	133x	133x	NUM
cana-1862	213	17	vol	vol	NOUN
cana-1862	213	18	32	32	NUM
cana-1862	213	19	no	no	NOUN
cana-1862	213	20	.	.	NOUN
cana-1862	213	21	2	2	NUM
cana-1862	213	22	(	(	PUNCT
cana-1862	213	23	2025	2025	NUM
cana-1862	213	24	)	)	PUNCT
cana-1862	213	25	704	704	NUM
cana-1862	213	26	https://internationalpubls.com	https://internationalpubls.com	X
cana-1862	213	27	where	where	SCONJ
cana-1862	213	28	the	the	DET
cana-1862	213	29	errors	error	NOUN
cana-1862	213	30	of	of	ADP
cana-1862	213	31	the	the	DET
cana-1862	213	32	previous	previous	ADJ
cana-1862	213	33	trees	tree	NOUN
cana-1862	213	34	are	be	AUX
cana-1862	213	35	corrected	correct	VERB
cana-1862	213	36	by	by	ADP
cana-1862	213	37	each	each	DET
cana-1862	213	38	new	new	ADJ
cana-1862	213	39	tree	tree	NOUN
cana-1862	213	40	uphill	uphill	ADV
cana-1862	213	41	.	.	PUNCT
cana-1862	214	1	the	the	DET
cana-1862	214	2	regularized	regularize	VERB
cana-1862	214	3	objective	objective	ADJ
cana-1862	214	4	function	function	NOUN
cana-1862	214	5	of	of	ADP
cana-1862	214	6	the	the	DET
cana-1862	214	7	method	method	NOUN
cana-1862	214	8	is	be	AUX
cana-1862	214	9	represented	represent	VERB
cana-1862	214	10	as	as	ADP
cana-1862	214	11	:	:	PUNCT
cana-1862	214	12	𝐿(𝜃	𝐿(𝜃	X
cana-1862	214	13	)	)	PUNCT
cana-1862	214	14	=	=	SYM
cana-1862	214	15	∑	∑	PUNCT
cana-1862	214	16	𝑛	𝑛	PRON
cana-1862	214	17	𝑖=1	𝑖=1	PROPN
cana-1862	214	18	𝑙(𝑦𝑖	𝑙(𝑦𝑖	PROPN
cana-1862	214	19	,	,	PUNCT
cana-1862	214	20	�	�	PROPN
cana-1862	214	21	̂	̂	NOUN
cana-1862	214	22	�	�	NOUN
cana-1862	214	23	𝑖	𝑖	NUM
cana-1862	214	24	)	)	PUNCT
cana-1862	214	25	+	+	CCONJ
cana-1862	214	26	∑	∑	PROPN
cana-1862	214	27	𝐾	𝐾	PROPN
cana-1862	214	28	𝑘=1	𝑘=1	PUNCT
cana-1862	214	29	𝛺(𝑓𝑘	𝛺(𝑓𝑘	PROPN
cana-1862	214	30	)	)	PUNCT
cana-1862	214	31	,	,	PUNCT
cana-1862	214	32	where	where	SCONJ
cana-1862	214	33	,	,	PUNCT
cana-1862	214	34	𝑙(𝑦𝑖	𝑙(𝑦𝑖	PRON
cana-1862	214	35	,	,	PUNCT
cana-1862	214	36	�	�	PROPN
cana-1862	214	37	̂	̂	VERB
cana-1862	214	38	�	�	NOUN
cana-1862	214	39	𝑖	𝑖	NUM
cana-1862	214	40	)	)	PUNCT
cana-1862	214	41	is	be	AUX
cana-1862	214	42	the	the	DET
cana-1862	214	43	loss	loss	NOUN
cana-1862	214	44	function	function	NOUN
cana-1862	214	45	measuring	measure	VERB
cana-1862	214	46	the	the	DET
cana-1862	214	47	difference	difference	NOUN
cana-1862	214	48	between	between	ADP
cana-1862	214	49	the	the	DET
cana-1862	214	50	predicted	predict	VERB
cana-1862	214	51	output	output	NOUN
cana-1862	214	52	�	�	PROPN
cana-1862	214	53	̂	̂	NOUN
cana-1862	214	54	�	�	NOUN
cana-1862	214	55	𝑖	𝑖	NOUN
cana-1862	214	56	and	and	CCONJ
cana-1862	214	57	the	the	DET
cana-1862	214	58	actual	actual	ADJ
cana-1862	214	59	label	label	NOUN
cana-1862	214	60	𝑦𝑖	𝑦𝑖	PROPN
cana-1862	214	61	,	,	PUNCT
cana-1862	214	62	and	and	CCONJ
cana-1862	214	63	𝛺(𝑓𝑘	𝛺(𝑓𝑘	X
cana-1862	214	64	)	)	PUNCT
cana-1862	214	65	is	be	AUX
cana-1862	214	66	a	a	DET
cana-1862	214	67	regularization	regularization	NOUN
cana-1862	214	68	term	term	NOUN
cana-1862	214	69	that	that	PRON
cana-1862	214	70	controls	control	VERB
cana-1862	214	71	the	the	DET
cana-1862	214	72	complexity	complexity	NOUN
cana-1862	214	73	of	of	ADP
cana-1862	214	74	the	the	DET
cana-1862	214	75	model	model	NOUN
cana-1862	214	76	.	.	PUNCT
cana-1862	215	1	xgboost	xgboost	PROPN
cana-1862	215	2	uses	use	VERB
cana-1862	215	3	regularization	regularization	NOUN
cana-1862	215	4	to	to	PART
cana-1862	215	5	prevent	prevent	VERB
cana-1862	215	6	overfitting	overfitting	NOUN
cana-1862	215	7	,	,	PUNCT
cana-1862	215	8	and	and	CCONJ
cana-1862	215	9	its	its	PRON
cana-1862	215	10	objective	objective	ADJ
cana-1862	215	11	function	function	NOUN
cana-1862	215	12	is	be	AUX
cana-1862	215	13	defined	define	VERB
cana-1862	215	14	as	as	ADP
cana-1862	215	15	:	:	PUNCT
cana-1862	215	16	𝐿(𝜃	𝐿(𝜃	X
cana-1862	215	17	)	)	PUNCT
cana-1862	215	18	=	=	SYM
cana-1862	215	19	∑	∑	PUNCT
cana-1862	215	20	𝑛	𝑛	PRON
cana-1862	215	21	𝑖=1	𝑖=1	PROPN
cana-1862	215	22	𝑙(𝑦𝑖	𝑙(𝑦𝑖	PROPN
cana-1862	215	23	,	,	PUNCT
cana-1862	215	24	�	�	PROPN
cana-1862	215	25	̂	̂	NOUN
cana-1862	215	26	�	�	NOUN
cana-1862	215	27	𝑖	𝑖	NUM
cana-1862	215	28	)	)	PUNCT
cana-1862	216	1	+	+	CCONJ
cana-1862	216	2	∑	∑	PROPN
cana-1862	216	3	𝐾	𝐾	PROPN
cana-1862	216	4	𝑘=1	𝑘=1	PUNCT
cana-1862	216	5	𝛺(𝑓𝑘	𝛺(𝑓𝑘	PROPN
cana-1862	216	6	)	)	PUNCT
cana-1862	216	7	,	,	PUNCT
cana-1862	216	8	where	where	SCONJ
cana-1862	216	9	,	,	PUNCT
cana-1862	216	10	𝑙	𝑙	PRON
cana-1862	216	11	is	be	AUX
cana-1862	216	12	the	the	DET
cana-1862	216	13	loss	loss	NOUN
cana-1862	216	14	function	function	NOUN
cana-1862	216	15	,	,	PUNCT
cana-1862	216	16	and	and	CCONJ
cana-1862	216	17	𝛺(𝑓𝑘	𝛺(𝑓𝑘	X
cana-1862	216	18	)	)	PUNCT
cana-1862	216	19	=	=	PUNCT
cana-1862	217	1	𝛾𝑇	𝛾𝑇	NOUN
cana-1862	218	1	+	+	CCONJ
cana-1862	218	2	1	1	NUM
cana-1862	218	3	2	2	NUM
cana-1862	218	4	𝜆	𝜆	PRON
cana-1862	218	5	∑	∑	PROPN
cana-1862	218	6	𝑇	𝑇	PROPN
cana-1862	218	7	𝑗=1	𝑗=1	PROPN
cana-1862	218	8	𝑤𝑗	𝑤𝑗	ADP
cana-1862	218	9	2	2	NUM
cana-1862	218	10	is	be	AUX
cana-1862	218	11	the	the	DET
cana-1862	218	12	regularization	regularization	NOUN
cana-1862	218	13	term	term	NOUN
cana-1862	218	14	for	for	ADP
cana-1862	218	15	tree	tree	NOUN
cana-1862	218	16	𝑘.	𝑘.	NOUN
cana-1862	218	17	o	o	X
cana-1862	218	18	neural	neural	ADJ
cana-1862	218	19	networks	network	NOUN
cana-1862	218	20	(	(	PUNCT
cana-1862	218	21	nn	nn	NOUN
cana-1862	218	22	)	)	PUNCT
cana-1862	218	23	and	and	CCONJ
cana-1862	218	24	deep	deep	ADJ
cana-1862	218	25	learning	learning	NOUN
cana-1862	218	26	:	:	PUNCT
cana-1862	218	27	deep	deep	ADJ
cana-1862	218	28	learning	learning	NOUN
cana-1862	218	29	approaches	approach	NOUN
cana-1862	218	30	,	,	PUNCT
cana-1862	218	31	in	in	ADP
cana-1862	218	32	particular	particular	ADJ
cana-1862	218	33	fully	fully	ADV
cana-1862	218	34	connected	connected	ADJ
cana-1862	218	35	neural	neural	ADJ
cana-1862	218	36	networks	network	NOUN
cana-1862	218	37	(	(	PUNCT
cana-1862	218	38	fcnns	fcnn	NOUN
cana-1862	218	39	)	)	PUNCT
cana-1862	218	40	,	,	PUNCT
cana-1862	218	41	are	be	AUX
cana-1862	218	42	used	use	VERB
cana-1862	218	43	for	for	ADP
cana-1862	218	44	complex	complex	ADJ
cana-1862	218	45	pattern	pattern	NOUN
cana-1862	218	46	recognition	recognition	NOUN
cana-1862	218	47	in	in	ADP
cana-1862	218	48	high	high	ADJ
cana-1862	218	49	-	-	PUNCT
cana-1862	218	50	dimensional	dimensional	ADJ
cana-1862	218	51	data	datum	NOUN
cana-1862	218	52	.	.	PUNCT
cana-1862	219	1	a	a	DET
cana-1862	219	2	neural	neural	ADJ
cana-1862	219	3	network	network	NOUN
cana-1862	219	4	architecture	architecture	NOUN
cana-1862	219	5	consists	consist	VERB
cana-1862	219	6	of	of	ADP
cana-1862	219	7	an	an	DET
cana-1862	219	8	input	input	NOUN
cana-1862	219	9	layer	layer	NOUN
cana-1862	219	10	,	,	PUNCT
cana-1862	219	11	one	one	NUM
cana-1862	219	12	or	or	CCONJ
cana-1862	219	13	more	more	ADV
cana-1862	219	14	hidden	hidden	ADJ
cana-1862	219	15	layers	layer	NOUN
cana-1862	219	16	and	and	CCONJ
cana-1862	219	17	an	an	DET
cana-1862	219	18	output	output	NOUN
cana-1862	219	19	layer	layer	NOUN
cana-1862	219	20	.	.	PUNCT
cana-1862	220	1	it	it	PRON
cana-1862	220	2	performs	perform	VERB
cana-1862	220	3	backpropagation	backpropagation	NOUN
cana-1862	220	4	to	to	PART
cana-1862	220	5	optimize	optimize	VERB
cana-1862	220	6	weights	weight	NOUN
cana-1862	220	7	via	via	ADP
cana-1862	220	8	the	the	DET
cana-1862	220	9	mathematical	mathematical	ADJ
cana-1862	220	10	formulation	formulation	NOUN
cana-1862	220	11	:	:	PUNCT
cana-1862	220	12	𝑊𝑖𝑗	𝑊𝑖𝑗	PROPN
cana-1862	220	13	←	←	PROPN
cana-1862	220	14	𝑊𝑖𝑗	𝑊𝑖𝑗	PROPN
cana-1862	220	15	−	−	PROPN
cana-1862	220	16	𝜂	𝜂	NOUN
cana-1862	220	17	𝜕𝐿	𝜕𝐿	PROPN
cana-1862	220	18	𝜕𝑊𝑖𝑗	𝜕𝑊𝑖𝑗	PROPN
cana-1862	220	19	,	,	PUNCT
cana-1862	220	20	where	where	SCONJ
cana-1862	220	21	,	,	PUNCT
cana-1862	220	22	𝑊𝑖𝑗	𝑊𝑖𝑗	PROPN
cana-1862	220	23	are	be	AUX
cana-1862	220	24	the	the	DET
cana-1862	220	25	weights	weight	NOUN
cana-1862	220	26	connecting	connect	VERB
cana-1862	220	27	neurons	neuron	NOUN
cana-1862	220	28	,	,	PUNCT
cana-1862	220	29	𝜂	𝜂	NOUN
cana-1862	220	30	is	be	AUX
cana-1862	220	31	the	the	DET
cana-1862	220	32	learning	learning	NOUN
cana-1862	220	33	rate	rate	NOUN
cana-1862	220	34	,	,	PUNCT
cana-1862	220	35	and	and	CCONJ
cana-1862	220	36	𝐿	𝐿	PROPN
cana-1862	220	37	is	be	AUX
cana-1862	220	38	the	the	DET
cana-1862	220	39	loss	loss	NOUN
cana-1862	220	40	function	function	NOUN
cana-1862	220	41	(	(	PUNCT
cana-1862	220	42	e.g.	e.g.	ADV
cana-1862	220	43	,	,	PUNCT
cana-1862	220	44	cross	cross	NOUN
cana-1862	220	45	-	-	NOUN
cana-1862	220	46	entropy	entropy	NOUN
cana-1862	220	47	for	for	ADP
cana-1862	220	48	classification	classification	NOUN
cana-1862	220	49	tasks	task	NOUN
cana-1862	220	50	)	)	PUNCT
cana-1862	220	51	.	.	PUNCT
cana-1862	221	1	the	the	DET
cana-1862	221	2	stochastic	stochastic	ADJ
cana-1862	221	3	gradient	gradient	ADJ
cana-1862	221	4	descent	descent	NOUN
cana-1862	221	5	(	(	PUNCT
cana-1862	221	6	sgd	sgd	NOUN
cana-1862	221	7	)	)	PUNCT
cana-1862	221	8	algorithm	algorithm	NOUN
cana-1862	221	9	is	be	AUX
cana-1862	221	10	commonly	commonly	ADV
cana-1862	221	11	used	use	VERB
cana-1862	221	12	to	to	PART
cana-1862	221	13	update	update	VERB
cana-1862	221	14	the	the	DET
cana-1862	221	15	weights	weight	NOUN
cana-1862	221	16	iteratively	iteratively	ADV
cana-1862	221	17	.	.	PUNCT
cana-1862	222	1	●	●	PUNCT
cana-1862	222	2	unsupervised	unsupervised	ADJ
cana-1862	222	3	learning	learning	NOUN
cana-1862	222	4	models	model	NOUN
cana-1862	222	5	these	these	DET
cana-1862	222	6	unsupervised	unsupervised	ADJ
cana-1862	222	7	models	model	NOUN
cana-1862	222	8	are	be	AUX
cana-1862	222	9	important	important	ADJ
cana-1862	222	10	because	because	SCONJ
cana-1862	222	11	while	while	SCONJ
cana-1862	222	12	we	we	PRON
cana-1862	222	13	are	be	AUX
cana-1862	222	14	trying	try	VERB
cana-1862	222	15	to	to	PART
cana-1862	222	16	develop	develop	VERB
cana-1862	222	17	a	a	DET
cana-1862	222	18	supervised	supervised	ADJ
cana-1862	222	19	model	model	NOUN
cana-1862	222	20	,	,	PUNCT
cana-1862	222	21	it	it	PRON
cana-1862	222	22	is	be	AUX
cana-1862	222	23	likely	likely	ADJ
cana-1862	222	24	that	that	SCONJ
cana-1862	222	25	the	the	DET
cana-1862	222	26	labelled	label	VERB
cana-1862	222	27	data	datum	NOUN
cana-1862	222	28	for	for	ADP
cana-1862	222	29	zero	zero	NUM
cana-1862	222	30	day	day	NOUN
cana-1862	222	31	vulnerabilities	vulnerability	NOUN
cana-1862	222	32	are	be	AUX
cana-1862	222	33	going	go	VERB
cana-1862	222	34	to	to	PART
cana-1862	222	35	be	be	AUX
cana-1862	222	36	sparse	sparse	ADJ
cana-1862	222	37	or	or	CCONJ
cana-1862	222	38	not	not	PART
cana-1862	222	39	even	even	ADV
cana-1862	222	40	available	available	ADJ
cana-1862	222	41	.	.	PUNCT
cana-1862	223	1	it	it	PRON
cana-1862	223	2	learns	learn	VERB
cana-1862	223	3	the	the	DET
cana-1862	223	4	normal	normal	ADJ
cana-1862	223	5	patterns	pattern	NOUN
cana-1862	223	6	in	in	ADP
cana-1862	223	7	your	your	PRON
cana-1862	223	8	data	datum	NOUN
cana-1862	223	9	so	so	SCONJ
cana-1862	223	10	that	that	SCONJ
cana-1862	223	11	it	it	PRON
cana-1862	223	12	can	can	AUX
cana-1862	223	13	spot	spot	VERB
cana-1862	223	14	outliers	outlier	NOUN
cana-1862	223	15	or	or	CCONJ
cana-1862	223	16	any	any	DET
cana-1862	223	17	deviations	deviation	NOUN
cana-1862	223	18	from	from	ADP
cana-1862	223	19	these	these	DET
cana-1862	223	20	learnt	learn	VERB
cana-1862	223	21	norms	norm	NOUN
cana-1862	223	22	which	which	PRON
cana-1862	223	23	may	may	AUX
cana-1862	223	24	be	be	AUX
cana-1862	223	25	a	a	DET
cana-1862	223	26	security	security	NOUN
cana-1862	223	27	threat	threat	NOUN
cana-1862	223	28	.	.	PUNCT
cana-1862	224	1	o	o	X
cana-1862	224	2	dead	dead	ADJ
cana-1862	224	3	simple	simple	ADJ
cana-1862	224	4	auto	auto	NOUN
cana-1862	224	5	-	-	PUNCT
cana-1862	224	6	decoders	decoder	NOUN
cana-1862	224	7	for	for	ADP
cana-1862	224	8	anomaly	anomaly	NOUN
cana-1862	224	9	detection	detection	NOUN
cana-1862	224	10	:	:	PUNCT
cana-1862	224	11	one	one	NUM
cana-1862	224	12	application	application	NOUN
cana-1862	224	13	for	for	ADP
cana-1862	224	14	creating	create	VERB
cana-1862	224	15	anomaly	anomaly	NOUN
cana-1862	224	16	detection	detection	NOUN
cana-1862	224	17	models	model	NOUN
cana-1862	224	18	is	be	AUX
cana-1862	224	19	the	the	DET
cana-1862	224	20	auto	auto	NOUN
cana-1862	224	21	-	-	PUNCT
cana-1862	224	22	encoder	encoder	NOUN
cana-1862	224	23	neural	neural	ADJ
cana-1862	224	24	networks	network	NOUN
cana-1862	224	25	,	,	PUNCT
cana-1862	224	26	which	which	PRON
cana-1862	224	27	are	be	AUX
cana-1862	224	28	specially	specially	ADV
cana-1862	224	29	designed	design	VERB
cana-1862	224	30	for	for	ADP
cana-1862	224	31	unsupervised	unsupervised	ADJ
cana-1862	224	32	learning	learning	NOUN
cana-1862	224	33	.	.	PUNCT
cana-1862	225	1	in	in	ADP
cana-1862	225	2	this	this	DET
cana-1862	225	3	architecture	architecture	NOUN
cana-1862	225	4	,	,	PUNCT
cana-1862	225	5	they	they	PRON
cana-1862	225	6	encode	encode	VERB
cana-1862	225	7	the	the	DET
cana-1862	225	8	input	input	NOUN
cana-1862	225	9	data	datum	NOUN
cana-1862	225	10	into	into	ADP
cana-1862	225	11	a	a	DET
cana-1862	225	12	latent	latent	NOUN
cana-1862	225	13	representation	representation	NOUN
cana-1862	225	14	with	with	ADP
cana-1862	225	15	lower	low	ADJ
cana-1862	225	16	dimensionality	dimensionality	NOUN
cana-1862	225	17	and	and	CCONJ
cana-1862	225	18	thereafter	thereafter	ADV
cana-1862	225	19	decode	decode	VERB
cana-1862	225	20	it	it	PRON
cana-1862	225	21	back	back	ADV
cana-1862	225	22	to	to	ADP
cana-1862	225	23	the	the	DET
cana-1862	225	24	original	original	ADJ
cana-1862	225	25	structure	structure	NOUN
cana-1862	225	26	.	.	PUNCT
cana-1862	226	1	the	the	DET
cana-1862	226	2	above	above	ADJ
cana-1862	226	3	reconstruction	reconstruction	NOUN
cana-1862	226	4	error	error	NOUN
cana-1862	226	5	can	can	AUX
cana-1862	226	6	be	be	AUX
cana-1862	226	7	taken	take	VERB
cana-1862	226	8	as	as	ADP
cana-1862	226	9	an	an	DET
cana-1862	226	10	anomaly	anomaly	NOUN
cana-1862	226	11	indicator	indicator	NOUN
cana-1862	226	12	;	;	PUNCT
cana-1862	226	13	𝐿(𝑥	𝐿(𝑥	PROPN
cana-1862	226	14	,	,	PUNCT
cana-1862	226	15	�	�	PROPN
cana-1862	226	16	̂	̂	NOUN
cana-1862	226	17	�	�	NOUN
cana-1862	226	18	)	)	PUNCT
cana-1862	226	19	=	=	PUNCT
cana-1862	226	20	∑	∑	PUNCT
cana-1862	226	21	𝑛	𝑛	PRON
cana-1862	226	22	𝑖=1	𝑖=1	PROPN
cana-1862	226	23	(	(	PUNCT
cana-1862	226	24	𝑥𝑖	𝑥𝑖	NUM
cana-1862	226	25	−	−	PROPN
cana-1862	226	26	�	�	PROPN
cana-1862	226	27	̂	̂	SYM
cana-1862	226	28	�	�	NOUN
cana-1862	226	29	𝑖)2	𝑖)2	PROPN
cana-1862	226	30	,	,	PUNCT
cana-1862	226	31	where	where	SCONJ
cana-1862	226	32	,	,	PUNCT
cana-1862	226	33	𝑥	𝑥	PROPN
cana-1862	226	34	is	be	AUX
cana-1862	226	35	the	the	DET
cana-1862	226	36	input	input	NOUN
cana-1862	226	37	data	datum	NOUN
cana-1862	226	38	,	,	PUNCT
cana-1862	226	39	�	�	PROPN
cana-1862	226	40	̂	̂	VERB
cana-1862	226	41	�	�	NOUN
cana-1862	226	42	is	be	AUX
cana-1862	226	43	the	the	DET
cana-1862	226	44	reconstructed	reconstructed	ADJ
cana-1862	226	45	data	datum	NOUN
cana-1862	226	46	,	,	PUNCT
cana-1862	226	47	and	and	CCONJ
cana-1862	226	48	𝑛	𝑛	PROPN
cana-1862	226	49	is	be	AUX
cana-1862	226	50	the	the	DET
cana-1862	226	51	number	number	NOUN
cana-1862	226	52	of	of	ADP
cana-1862	226	53	features	feature	NOUN
cana-1862	226	54	.	.	PUNCT
cana-1862	227	1	a	a	DET
cana-1862	227	2	high	high	ADJ
cana-1862	227	3	reconstruction	reconstruction	NOUN
cana-1862	227	4	error	error	NOUN
cana-1862	227	5	signals	signal	VERB
cana-1862	227	6	an	an	DET
cana-1862	227	7	anomaly	anomaly	NOUN
cana-1862	227	8	,	,	PUNCT
cana-1862	227	9	potentially	potentially	ADV
cana-1862	227	10	indicating	indicate	VERB
cana-1862	227	11	a	a	DET
cana-1862	227	12	vulnerability	vulnerability	NOUN
cana-1862	227	13	.	.	PUNCT
cana-1862	228	1	communications	communication	NOUN
cana-1862	228	2	on	on	ADP
cana-1862	228	3	applied	apply	VERB
cana-1862	228	4	nonlinear	nonlinear	ADJ
cana-1862	228	5	analysis	analysis	NOUN
cana-1862	228	6	issn	issn	NOUN
cana-1862	228	7	:	:	PUNCT
cana-1862	228	8	1074	1074	NUM
cana-1862	228	9	-	-	PUNCT
cana-1862	228	10	133x	133x	NUM
cana-1862	228	11	vol	vol	NOUN
cana-1862	228	12	32	32	NUM
cana-1862	228	13	no	no	NOUN
cana-1862	228	14	.	.	NOUN
cana-1862	228	15	2	2	NUM
cana-1862	228	16	(	(	PUNCT
cana-1862	228	17	2025	2025	NUM
cana-1862	228	18	)	)	PUNCT
cana-1862	228	19	705	705	NUM
cana-1862	228	20	https://internationalpubls.com	https://internationalpubls.com	X
cana-1862	228	21	algorithm	algorithm	NOUN
cana-1862	228	22	:	:	PUNCT
cana-1862	228	23	1	1	X
cana-1862	228	24	.	.	X
cana-1862	228	25	input	input	NOUN
cana-1862	228	26	:	:	PUNCT
cana-1862	228	27	dataset	dataset	VERB
cana-1862	228	28	𝑋	𝑋	PROPN
cana-1862	228	29	=	=	SYM
cana-1862	228	30	{	{	PUNCT
cana-1862	228	31	𝑥1	𝑥1	NOUN
cana-1862	228	32	,	,	PUNCT
cana-1862	228	33	𝑥2	𝑥2	NOUN
cana-1862	228	34	,	,	PUNCT
cana-1862	228	35	…	…	PUNCT
cana-1862	228	36	,	,	PUNCT
cana-1862	228	37	𝑥𝑛	𝑥𝑛	NOUN
cana-1862	228	38	}	}	PUNCT
cana-1862	228	39	.	.	PUNCT
cana-1862	229	1	2	2	X
cana-1862	229	2	.	.	NUM
cana-1862	229	3	randomly	randomly	ADV
cana-1862	229	4	select	select	VERB
cana-1862	229	5	a	a	DET
cana-1862	229	6	feature	feature	NOUN
cana-1862	229	7	and	and	CCONJ
cana-1862	229	8	a	a	DET
cana-1862	229	9	split	split	ADJ
cana-1862	229	10	value	value	NOUN
cana-1862	229	11	for	for	ADP
cana-1862	229	12	each	each	DET
cana-1862	229	13	tree	tree	NOUN
cana-1862	229	14	.	.	PUNCT
cana-1862	230	1	3	3	X
cana-1862	230	2	.	.	X
cana-1862	230	3	recursively	recursively	ADV
cana-1862	230	4	partition	partition	VERB
cana-1862	230	5	the	the	DET
cana-1862	230	6	data	datum	NOUN
cana-1862	230	7	until	until	SCONJ
cana-1862	230	8	each	each	DET
cana-1862	230	9	point	point	NOUN
cana-1862	230	10	is	be	AUX
cana-1862	230	11	isolated	isolate	VERB
cana-1862	230	12	.	.	PUNCT
cana-1862	231	1	4	4	X
cana-1862	231	2	.	.	X
cana-1862	231	3	the	the	DET
cana-1862	231	4	anomaly	anomaly	NOUN
cana-1862	231	5	score	score	NOUN
cana-1862	231	6	for	for	ADP
cana-1862	231	7	a	a	DET
cana-1862	231	8	point	point	NOUN
cana-1862	231	9	𝑥𝑖	𝑥𝑖	PROPN
cana-1862	231	10	is	be	AUX
cana-1862	231	11	computed	compute	VERB
cana-1862	231	12	based	base	VERB
cana-1862	231	13	on	on	ADP
cana-1862	231	14	the	the	DET
cana-1862	231	15	path	path	NOUN
cana-1862	231	16	length	length	NOUN
cana-1862	231	17	to	to	PART
cana-1862	231	18	isolate	isolate	VERB
cana-1862	231	19	it	it	PRON
cana-1862	231	20	.	.	PUNCT
cana-1862	232	1	5	5	X
cana-1862	232	2	.	.	X
cana-1862	232	3	output	output	NOUN
cana-1862	232	4	:	:	PUNCT
cana-1862	232	5	anomaly	anomaly	NOUN
cana-1862	232	6	scores	score	NOUN
cana-1862	232	7	for	for	ADP
cana-1862	232	8	all	all	DET
cana-1862	232	9	data	datum	NOUN
cana-1862	232	10	points	point	NOUN
cana-1862	232	11	.	.	PUNCT
cana-1862	233	1	o	o	X
cana-1862	234	1	k	k	NOUN
cana-1862	234	2	-	-	PUNCT
cana-1862	234	3	means	mean	NOUN
cana-1862	234	4	and	and	CCONJ
cana-1862	234	5	gaussian	gaussian	ADJ
cana-1862	234	6	mixture	mixture	NOUN
cana-1862	234	7	model	model	NOUN
cana-1862	234	8	as	as	ADP
cana-1862	234	9	clustering	cluster	VERB
cana-1862	234	10	techniques	technique	NOUN
cana-1862	234	11	:	:	PUNCT
cana-1862	234	12	k	k	X
cana-1862	234	13	-	-	PUNCT
cana-1862	234	14	means	mean	VERB
cana-1862	234	15	clustering	clustering	NOUN
cana-1862	234	16	:	:	PUNCT
cana-1862	234	17	k	k	X
cana-1862	234	18	means	mean	NOUN
cana-1862	234	19	has	have	AUX
cana-1862	234	20	been	be	AUX
cana-1862	234	21	around	around	ADV
cana-1862	234	22	since	since	SCONJ
cana-1862	234	23	1967	1967	NUM
cana-1862	234	24	,	,	PUNCT
cana-1862	234	25	this	this	DET
cana-1862	234	26	method	method	NOUN
cana-1862	234	27	partitions	partition	VERB
cana-1862	234	28	data	datum	NOUN
cana-1862	234	29	into	into	ADP
cana-1862	234	30	kkk	kkk	PROPN
cana-1862	234	31	clusters	cluster	NOUN
cana-1862	234	32	based	base	VERB
cana-1862	234	33	on	on	ADP
cana-1862	234	34	similarity	similarity	NOUN
cana-1862	234	35	of	of	ADP
cana-1862	234	36	features	feature	NOUN
cana-1862	234	37	that	that	PRON
cana-1862	234	38	are	be	AUX
cana-1862	234	39	available	available	ADJ
cana-1862	234	40	.	.	PUNCT
cana-1862	235	1	which	which	PRON
cana-1862	235	2	reduce	reduce	VERB
cana-1862	235	3	within	within	ADP
cana-1862	235	4	-	-	PUNCT
cana-1862	235	5	cluster	cluster	NOUN
cana-1862	235	6	sum	sum	NOUN
cana-1862	235	7	of	of	ADP
cana-1862	235	8	squares	square	NOUN
cana-1862	235	9	.	.	PUNCT
cana-1862	236	1	𝐽	𝐽	PROPN
cana-1862	236	2	=	=	PUNCT
cana-1862	236	3	∑	∑	PUNCT
cana-1862	236	4	𝐾	𝐾	PROPN
cana-1862	236	5	𝑗=1	𝑗=1	PROPN
cana-1862	236	6	∑	∑	PUNCT
cana-1862	236	7	𝑥𝑖∈𝐶𝑗	𝑥𝑖∈𝐶𝑗	X
cana-1862	236	8	∥	∥	X
cana-1862	236	9	𝑥𝑖	𝑥𝑖	ADP
cana-1862	236	10	−	−	NOUN
cana-1862	236	11	𝜇𝑗	𝜇𝑗	NOUN
cana-1862	236	12	∥2	∥2	PROPN
cana-1862	236	13	,	,	PUNCT
cana-1862	236	14	where	where	SCONJ
cana-1862	236	15	,	,	PUNCT
cana-1862	236	16	𝐶𝑗	𝐶𝑗	PROPN
cana-1862	236	17	is	be	AUX
cana-1862	236	18	the	the	DET
cana-1862	236	19	set	set	NOUN
cana-1862	236	20	of	of	ADP
cana-1862	236	21	points	point	NOUN
cana-1862	236	22	in	in	ADP
cana-1862	236	23	cluster	cluster	NOUN
cana-1862	236	24	𝑗	𝑗	NOUN
cana-1862	236	25	and	and	CCONJ
cana-1862	236	26	𝜇𝑗	𝜇𝑗	PROPN
cana-1862	236	27	is	be	AUX
cana-1862	236	28	the	the	DET
cana-1862	236	29	cluster	cluster	NOUN
cana-1862	236	30	centroid	centroid	NOUN
cana-1862	236	31	.	.	PUNCT
cana-1862	237	1	in	in	ADP
cana-1862	237	2	vulnerability	vulnerability	NOUN
cana-1862	237	3	detection	detection	NOUN
cana-1862	237	4	,	,	PUNCT
cana-1862	237	5	normal	normal	ADJ
cana-1862	237	6	traffic	traffic	NOUN
cana-1862	237	7	forms	form	NOUN
cana-1862	237	8	dense	dense	ADJ
cana-1862	237	9	clusters	cluster	NOUN
cana-1862	237	10	,	,	PUNCT
cana-1862	237	11	while	while	SCONJ
cana-1862	237	12	outliers	outlier	NOUN
cana-1862	237	13	(	(	PUNCT
cana-1862	237	14	anomalies	anomaly	NOUN
cana-1862	237	15	)	)	PUNCT
cana-1862	237	16	represent	represent	VERB
cana-1862	237	17	potential	potential	ADJ
cana-1862	237	18	threats	threat	NOUN
cana-1862	237	19	.	.	PUNCT
cana-1862	238	1	next	next	ADJ
cana-1862	238	2	example	example	NOUN
cana-1862	238	3	implements	implement	VERB
cana-1862	238	4	a	a	DET
cana-1862	238	5	gaussian	gaussian	ADJ
cana-1862	238	6	mixture	mixture	NOUN
cana-1862	238	7	models	model	NOUN
cana-1862	238	8	(	(	PUNCT
cana-1862	238	9	gmms	gmms	NOUN
cana-1862	238	10	)	)	PUNCT
cana-1862	238	11	,	,	PUNCT
cana-1862	238	12	which	which	PRON
cana-1862	238	13	is	be	AUX
cana-1862	238	14	a	a	DET
cana-1862	238	15	probabilistic	probabilistic	ADJ
cana-1862	238	16	model	model	NOUN
cana-1862	238	17	that	that	PRON
cana-1862	238	18	assumes	assume	VERB
cana-1862	238	19	all	all	DET
cana-1862	238	20	clustered	clustered	ADJ
cana-1862	238	21	data	datum	NOUN
cana-1862	238	22	points	point	NOUN
cana-1862	238	23	are	be	AUX
cana-1862	238	24	generated	generate	VERB
cana-1862	238	25	from	from	ADP
cana-1862	238	26	several	several	ADJ
cana-1862	238	27	gaussian	gaussian	ADJ
cana-1862	238	28	distributions	distribution	NOUN
cana-1862	238	29	.	.	PUNCT
cana-1862	239	1	the	the	DET
cana-1862	239	2	expectationmaximization	expectationmaximization	NOUN
cana-1862	239	3	(	(	PUNCT
cana-1862	239	4	em	em	PRON
cana-1862	239	5	)	)	PUNCT
cana-1862	239	6	algorithm	algorithm	NOUN
cana-1862	239	7	is	be	AUX
cana-1862	239	8	employ	employ	NOUN
cana-1862	239	9	method	method	NOUN
cana-1862	239	10	to	to	PART
cana-1862	239	11	infer	infer	VERB
cana-1862	239	12	the	the	DET
cana-1862	239	13	parameters	parameter	NOUN
cana-1862	239	14	of	of	ADP
cana-1862	239	15	these	these	DET
cana-1862	239	16	distributions	distribution	NOUN
cana-1862	239	17	.	.	PUNCT
cana-1862	240	1	gmms	gmms	NOUN
cana-1862	240	2	can	can	AUX
cana-1862	240	3	characterize	characterize	VERB
cana-1862	240	4	complex	complex	ADJ
cana-1862	240	5	data	datum	NOUN
cana-1862	240	6	structures	structure	NOUN
cana-1862	240	7	,	,	PUNCT
cana-1862	240	8	and	and	CCONJ
cana-1862	240	9	thus	thus	ADV
cana-1862	240	10	they	they	PRON
cana-1862	240	11	are	be	AUX
cana-1862	240	12	appropriate	appropriate	ADJ
cana-1862	240	13	to	to	PART
cana-1862	240	14	capture	capture	VERB
cana-1862	240	15	subtle	subtle	ADJ
cana-1862	240	16	anomalies	anomaly	NOUN
cana-1862	240	17	in	in	ADP
cana-1862	240	18	network	network	NOUN
cana-1862	240	19	traffic	traffic	NOUN
cana-1862	240	20	.	.	PUNCT
cana-1862	241	1	●	●	PUNCT
cana-1862	241	2	probabilistic	probabilistic	ADJ
cana-1862	241	3	models	model	NOUN
cana-1862	241	4	developing	develop	VERB
cana-1862	241	5	probabilistic	probabilistic	ADJ
cana-1862	241	6	models	model	NOUN
cana-1862	241	7	is	be	AUX
cana-1862	241	8	beneficial	beneficial	ADJ
cana-1862	241	9	to	to	ADP
cana-1862	241	10	its	its	PRON
cana-1862	241	11	capability	capability	NOUN
cana-1862	241	12	of	of	ADP
cana-1862	241	13	handling	handle	VERB
cana-1862	241	14	uncertainty	uncertainty	NOUN
cana-1862	241	15	and	and	CCONJ
cana-1862	241	16	dependencies	dependency	NOUN
cana-1862	241	17	in	in	ADP
cana-1862	241	18	the	the	DET
cana-1862	241	19	different	different	ADJ
cana-1862	241	20	characteristics	characteristic	NOUN
cana-1862	241	21	of	of	ADP
cana-1862	241	22	network	network	NOUN
cana-1862	241	23	traffic	traffic	NOUN
cana-1862	241	24	data	datum	NOUN
cana-1862	241	25	making	make	VERB
cana-1862	241	26	it	it	PRON
cana-1862	241	27	more	more	ADV
cana-1862	241	28	reliable	reliable	ADJ
cana-1862	241	29	in	in	ADP
cana-1862	241	30	detecting	detect	VERB
cana-1862	241	31	complex	complex	ADJ
cana-1862	241	32	vulnerabilities	vulnerability	NOUN
cana-1862	241	33	.	.	PUNCT
cana-1862	242	1	o	o	NOUN
cana-1862	242	2	bayesian	bayesian	NOUN
cana-1862	242	3	networks	network	NOUN
cana-1862	242	4	bayesian	bayesian	NOUN
cana-1862	242	5	networks	network	NOUN
cana-1862	242	6	are	be	AUX
cana-1862	242	7	a	a	DET
cana-1862	242	8	type	type	NOUN
cana-1862	242	9	of	of	ADP
cana-1862	242	10	graphical	graphical	ADJ
cana-1862	242	11	model	model	NOUN
cana-1862	242	12	for	for	ADP
cana-1862	242	13	representing	represent	VERB
cana-1862	242	14	probabilistic	probabilistic	ADJ
cana-1862	242	15	relationships	relationship	NOUN
cana-1862	242	16	among	among	ADP
cana-1862	242	17	a	a	DET
cana-1862	242	18	set	set	NOUN
cana-1862	242	19	of	of	ADP
cana-1862	242	20	variables	variable	NOUN
cana-1862	242	21	.	.	PUNCT
cana-1862	243	1	the	the	DET
cana-1862	243	2	mechanism	mechanism	NOUN
cana-1862	243	3	is	be	AUX
cana-1862	243	4	bayesian	bayesian	NOUN
cana-1862	243	5	inference	inference	NOUN
cana-1862	243	6	,	,	PUNCT
cana-1862	243	7	combining	combine	VERB
cana-1862	243	8	priors	prior	NOUN
cana-1862	243	9	and	and	CCONJ
cana-1862	243	10	evidence	evidence	NOUN
cana-1862	243	11	to	to	PART
cana-1862	243	12	get	get	VERB
cana-1862	243	13	the	the	DET
cana-1862	243	14	probability	probability	NOUN
cana-1862	243	15	of	of	ADP
cana-1862	243	16	security	security	NOUN
cana-1862	243	17	events	event	NOUN
cana-1862	243	18	using	use	VERB
cana-1862	243	19	observations	observation	NOUN
cana-1862	243	20	.	.	PUNCT
cana-1862	244	1	here	here	ADV
cana-1862	244	2	is	be	AUX
cana-1862	244	3	the	the	DET
cana-1862	244	4	joint	joint	ADJ
cana-1862	244	5	probability	probability	NOUN
cana-1862	244	6	distribution	distribution	NOUN
cana-1862	244	7	of	of	ADP
cana-1862	244	8	our	our	PRON
cana-1862	244	9	network	network	NOUN
cana-1862	244	10	:	:	PUNCT
cana-1862	244	11	𝑃(𝑋	𝑃(𝑋	PROPN
cana-1862	244	12	)	)	PUNCT
cana-1862	244	13	=	=	SYM
cana-1862	244	14	∏	∏	PROPN
cana-1862	244	15	𝑛	𝑛	PRON
cana-1862	244	16	𝑖=1	𝑖=1	PROPN
cana-1862	244	17	𝑃(𝑋𝑖	𝑃(𝑋𝑖	PROPN
cana-1862	244	18	∣	∣	ADJ
cana-1862	244	19	𝑃𝑎𝑟𝑒𝑛𝑡𝑠(𝑋𝑖	𝑃𝑎𝑟𝑒𝑛𝑡𝑠(𝑋𝑖	NUM
cana-1862	244	20	)	)	PUNCT
cana-1862	244	21	)	)	PUNCT
cana-1862	244	22	,	,	PUNCT
cana-1862	244	23	where	where	SCONJ
cana-1862	244	24	,	,	PUNCT
cana-1862	244	25	𝑋	𝑋	PROPN
cana-1862	244	26	=	=	SYM
cana-1862	244	27	{	{	PUNCT
cana-1862	244	28	𝑋1	𝑋1	PROPN
cana-1862	244	29	,	,	PUNCT
cana-1862	244	30	𝑋2	𝑋2	VERB
cana-1862	244	31	,	,	PUNCT
cana-1862	244	32	…	…	PUNCT
cana-1862	244	33	,	,	PUNCT
cana-1862	244	34	𝑋𝑛	𝑋𝑛	NOUN
cana-1862	244	35	}	}	PUNCT
cana-1862	244	36	is	be	AUX
cana-1862	244	37	the	the	DET
cana-1862	244	38	set	set	NOUN
cana-1862	244	39	of	of	ADP
cana-1862	244	40	variables	variable	NOUN
cana-1862	244	41	,	,	PUNCT
cana-1862	244	42	and	and	CCONJ
cana-1862	244	43	𝑃(𝑋𝑖	𝑃(𝑋𝑖	VERB
cana-1862	244	44	∣	∣	ADJ
cana-1862	244	45	𝑃𝑎𝑟𝑒𝑛𝑡𝑠(𝑋𝑖	𝑃𝑎𝑟𝑒𝑛𝑡𝑠(𝑋𝑖	NUM
cana-1862	244	46	)	)	PUNCT
cana-1862	244	47	)	)	PUNCT
cana-1862	244	48	is	be	AUX
cana-1862	244	49	the	the	DET
cana-1862	244	50	conditional	conditional	ADJ
cana-1862	244	51	probability	probability	NOUN
cana-1862	244	52	of	of	ADP
cana-1862	244	53	𝑋𝑖	𝑋𝑖	PROPN
cana-1862	244	54	given	give	VERB
cana-1862	244	55	its	its	PRON
cana-1862	244	56	parent	parent	NOUN
cana-1862	244	57	nodes	node	NOUN
cana-1862	244	58	in	in	ADP
cana-1862	244	59	the	the	DET
cana-1862	244	60	network	network	NOUN
cana-1862	244	61	.	.	PUNCT
cana-1862	245	1	algorithm	algorithm	NOUN
cana-1862	245	2	:	:	PUNCT
cana-1862	245	3	communications	communication	NOUN
cana-1862	245	4	on	on	ADP
cana-1862	245	5	applied	apply	VERB
cana-1862	245	6	nonlinear	nonlinear	ADJ
cana-1862	245	7	analysis	analysis	NOUN
cana-1862	245	8	issn	issn	NOUN
cana-1862	245	9	:	:	PUNCT
cana-1862	245	10	1074	1074	NUM
cana-1862	245	11	-	-	PUNCT
cana-1862	245	12	133x	133x	NUM
cana-1862	245	13	vol	vol	NOUN
cana-1862	245	14	32	32	NUM
cana-1862	245	15	no	no	NOUN
cana-1862	245	16	.	.	NOUN
cana-1862	245	17	2	2	NUM
cana-1862	245	18	(	(	PUNCT
cana-1862	245	19	2025	2025	NUM
cana-1862	245	20	)	)	PUNCT
cana-1862	245	21	706	706	NUM
cana-1862	246	1	https://internationalpubls.com	https://internationalpubls.com	X
cana-1862	246	2	input	input	NOUN
cana-1862	246	3	:	:	PUNCT
cana-1862	246	4	set	set	NOUN
cana-1862	246	5	of	of	ADP
cana-1862	246	6	variables	variable	NOUN
cana-1862	246	7	𝑉	𝑉	PROPN
cana-1862	246	8	=	=	PUNCT
cana-1862	246	9	{	{	PUNCT
cana-1862	246	10	𝑋1	𝑋1	PROPN
cana-1862	246	11	,	,	PUNCT
cana-1862	246	12	𝑋2	𝑋2	VERB
cana-1862	246	13	,	,	PUNCT
cana-1862	246	14	…	…	PUNCT
cana-1862	246	15	,	,	PUNCT
cana-1862	246	16	𝑋𝑛	𝑋𝑛	AUX
cana-1862	246	17	}	}	PUNCT
cana-1862	246	18	representing	represent	VERB
cana-1862	246	19	security	security	NOUN
cana-1862	246	20	features	feature	NOUN
cana-1862	246	21	.	.	PUNCT
cana-1862	247	1	define	define	VERB
cana-1862	247	2	the	the	DET
cana-1862	247	3	network	network	NOUN
cana-1862	247	4	structure	structure	NOUN
cana-1862	247	5	as	as	ADP
cana-1862	247	6	a	a	DET
cana-1862	247	7	directed	direct	VERB
cana-1862	247	8	acyclic	acyclic	ADJ
cana-1862	247	9	graph	graph	NOUN
cana-1862	247	10	(	(	PUNCT
cana-1862	247	11	dag	dag	PROPN
cana-1862	247	12	)	)	PUNCT
cana-1862	247	13	.	.	PUNCT
cana-1862	248	1	compute	compute	VERB
cana-1862	248	2	the	the	DET
cana-1862	248	3	conditional	conditional	ADJ
cana-1862	248	4	probability	probability	NOUN
cana-1862	248	5	tables	table	NOUN
cana-1862	248	6	(	(	PUNCT
cana-1862	248	7	cpts	cpt	NOUN
cana-1862	248	8	)	)	PUNCT
cana-1862	248	9	for	for	ADP
cana-1862	248	10	each	each	DET
cana-1862	248	11	node	node	NOUN
cana-1862	248	12	𝑋𝑖	𝑋𝑖	NOUN
cana-1862	248	13	:	:	PUNCT
cana-1862	248	14	if	if	SCONJ
cana-1862	248	15	𝑋𝑖	𝑋𝑖	PROPN
cana-1862	248	16	has	have	VERB
cana-1862	248	17	parents	parent	NOUN
cana-1862	248	18	𝑃𝑎(𝑋𝑖	𝑃𝑎(𝑋𝑖	PROPN
cana-1862	248	19	)	)	PUNCT
cana-1862	248	20	,	,	PUNCT
cana-1862	248	21	calculate	calculate	VERB
cana-1862	248	22	𝑃(𝑋𝑖	𝑃(𝑋𝑖	NOUN
cana-1862	248	23	∣	∣	ADJ
cana-1862	248	24	𝑃𝑎(𝑋𝑖	𝑃𝑎(𝑋𝑖	NOUN
cana-1862	248	25	)	)	PUNCT
cana-1862	248	26	)	)	PUNCT
cana-1862	248	27	.	.	PUNCT
cana-1862	249	1	during	during	ADP
cana-1862	249	2	prediction	prediction	NOUN
cana-1862	249	3	,	,	PUNCT
cana-1862	249	4	use	use	VERB
cana-1862	249	5	bayes	baye	NOUN
cana-1862	249	6	'	'	PART
cana-1862	249	7	theorem	theorem	NOUN
cana-1862	249	8	to	to	PART
cana-1862	249	9	update	update	VERB
cana-1862	249	10	the	the	DET
cana-1862	249	11	posterior	posterior	ADJ
cana-1862	249	12	probabilities	probability	NOUN
cana-1862	249	13	:	:	PUNCT
cana-1862	249	14	𝑃(𝑋𝑖	𝑃(𝑋𝑖	NUM
cana-1862	249	15	∣	∣	PROPN
cana-1862	249	16	𝐸	𝐸	PROPN
cana-1862	249	17	)	)	PUNCT
cana-1862	249	18	=	=	NUM
cana-1862	249	19	𝑃(𝐸	𝑃(𝐸	NUM
cana-1862	249	20	∣	∣	ADJ
cana-1862	249	21	𝑋𝑖)𝑃(𝑋𝑖	𝑋𝑖)𝑃(𝑋𝑖	NOUN
cana-1862	249	22	)	)	PUNCT
cana-1862	249	23	𝑃(𝐸	𝑃(𝐸	NUM
cana-1862	249	24	)	)	PUNCT
cana-1862	249	25	,	,	PUNCT
cana-1862	249	26	where	where	SCONJ
cana-1862	249	27	,	,	PUNCT
cana-1862	249	28	𝐸	𝐸	PROPN
cana-1862	249	29	is	be	AUX
cana-1862	249	30	the	the	DET
cana-1862	249	31	observed	observed	ADJ
cana-1862	249	32	evidence	evidence	NOUN
cana-1862	249	33	.	.	PUNCT
cana-1862	250	1	output	output	NOUN
cana-1862	250	2	:	:	PUNCT
cana-1862	250	3	updated	update	VERB
cana-1862	250	4	probabilities	probability	NOUN
cana-1862	250	5	indicating	indicate	VERB
cana-1862	250	6	the	the	DET
cana-1862	250	7	likelihood	likelihood	NOUN
cana-1862	250	8	of	of	ADP
cana-1862	250	9	vulnerabilities	vulnerability	NOUN
cana-1862	250	10	.	.	PUNCT
cana-1862	251	1	o	o	NOUN
cana-1862	251	2	graph	graph	NOUN
cana-1862	251	3	neural	neural	ADJ
cana-1862	251	4	networks	network	NOUN
cana-1862	251	5	(	(	PUNCT
cana-1862	251	6	gnns	gnns	NOUN
cana-1862	251	7	)	)	PUNCT
cana-1862	251	8	graph	graph	NOUN
cana-1862	251	9	neural	neural	ADJ
cana-1862	251	10	networks	network	NOUN
cana-1862	251	11	have	have	AUX
cana-1862	251	12	been	be	AUX
cana-1862	251	13	designed	design	VERB
cana-1862	251	14	toward	toward	ADP
cana-1862	251	15	graph	graph	NOUN
cana-1862	251	16	-	-	PUNCT
cana-1862	251	17	structured	structure	VERB
cana-1862	251	18	data	datum	NOUN
cana-1862	251	19	which	which	PRON
cana-1862	251	20	enables	enable	VERB
cana-1862	251	21	us	we	PRON
cana-1862	251	22	to	to	PART
cana-1862	251	23	perform	perform	VERB
cana-1862	251	24	network	network	NOUN
cana-1862	251	25	traffic	traffic	NOUN
cana-1862	251	26	analysis	analysis	NOUN
cana-1862	251	27	as	as	ADV
cana-1862	251	28	well	well	ADV
cana-1862	251	29	as	as	ADP
cana-1862	251	30	vulnerability	vulnerability	NOUN
cana-1862	251	31	detection	detection	NOUN
cana-1862	251	32	in	in	ADP
cana-1862	251	33	complicated	complicated	ADJ
cana-1862	251	34	systems	system	NOUN
cana-1862	251	35	.	.	PUNCT
cana-1862	252	1	one	one	NUM
cana-1862	252	2	node	node	NOUN
cana-1862	252	3	in	in	ADP
cana-1862	252	4	the	the	DET
cana-1862	252	5	gnn	gnn	PROPN
cana-1862	252	6	uses	use	VERB
cana-1862	252	7	the	the	DET
cana-1862	252	8	message	message	NOUN
cana-1862	252	9	-	-	PUNCT
cana-1862	252	10	passing	pass	VERB
cana-1862	252	11	mechanism	mechanism	NOUN
cana-1862	252	12	to	to	PART
cana-1862	252	13	aggregate	aggregate	VERB
cana-1862	252	14	information	information	NOUN
cana-1862	252	15	from	from	ADP
cana-1862	252	16	its	its	PRON
cana-1862	252	17	neighbours	neighbour	NOUN
cana-1862	252	18	on	on	ADP
cana-1862	252	19	the	the	DET
cana-1862	252	20	feature	feature	NOUN
cana-1862	252	21	vector	vector	NOUN
cana-1862	252	22	.	.	PUNCT
cana-1862	253	1	mathematically	mathematically	ADV
cana-1862	253	2	,	,	PUNCT
cana-1862	253	3	the	the	DET
cana-1862	253	4	feature	feature	NOUN
cana-1862	253	5	vector	vector	NOUN
cana-1862	253	6	ℎ𝑣	ℎ𝑣	PROPN
cana-1862	253	7	(	(	PUNCT
cana-1862	253	8	𝑙+1	𝑙+1	NOUN
cana-1862	253	9	)	)	PUNCT
cana-1862	253	10	of	of	ADP
cana-1862	253	11	node	node	ADJ
cana-1862	253	12	𝑣	𝑣	ADP
cana-1862	253	13	in	in	ADP
cana-1862	253	14	layer	layer	NOUN
cana-1862	253	15	𝑙	𝑙	PROPN
cana-1862	253	16	+	+	NUM
cana-1862	253	17	1	1	NUM
cana-1862	253	18	is	be	AUX
cana-1862	253	19	updated	update	VERB
cana-1862	253	20	as	as	ADP
cana-1862	253	21	:	:	PUNCT
cana-1862	253	22	ℎ𝑣	ℎ𝑣	X
cana-1862	253	23	(	(	PUNCT
cana-1862	253	24	𝑙+1	𝑙+1	NOUN
cana-1862	253	25	)	)	PUNCT
cana-1862	253	26	=	=	SYM
cana-1862	253	27	𝜎	𝜎	PROPN
cana-1862	253	28	(	(	PUNCT
cana-1862	253	29	𝑊(𝑙	𝑊(𝑙	NOUN
cana-1862	253	30	)	)	PUNCT
cana-1862	253	31	∑	∑	NOUN
cana-1862	253	32	𝑢∈𝑁(𝑣	𝑢∈𝑁(𝑣	NUM
cana-1862	253	33	)	)	PUNCT
cana-1862	253	34	ℎ𝑢	ℎ𝑢	PROPN
cana-1862	253	35	(	(	PUNCT
cana-1862	253	36	𝑙	𝑙	NOUN
cana-1862	253	37	)	)	PUNCT
cana-1862	253	38	)	)	PUNCT
cana-1862	253	39	,	,	PUNCT
cana-1862	253	40	where	where	SCONJ
cana-1862	253	41	,	,	PUNCT
cana-1862	253	42	𝑁(𝑣	𝑁(𝑣	X
cana-1862	253	43	)	)	PUNCT
cana-1862	253	44	is	be	AUX
cana-1862	253	45	the	the	DET
cana-1862	253	46	set	set	NOUN
cana-1862	253	47	of	of	ADP
cana-1862	253	48	neighbors	neighbor	NOUN
cana-1862	253	49	of	of	ADP
cana-1862	253	50	𝑣	𝑣	ADP
cana-1862	253	51	,	,	PUNCT
cana-1862	253	52	𝑊(𝑙	𝑊(𝑙	NOUN
cana-1862	253	53	)	)	PUNCT
cana-1862	253	54	is	be	AUX
cana-1862	253	55	a	a	DET
cana-1862	253	56	learnable	learnable	ADJ
cana-1862	253	57	weight	weight	NOUN
cana-1862	253	58	matrix	matrix	NOUN
cana-1862	253	59	,	,	PUNCT
cana-1862	253	60	and	and	CCONJ
cana-1862	253	61	𝜎	𝜎	PROPN
cana-1862	253	62	is	be	AUX
cana-1862	253	63	an	an	DET
cana-1862	253	64	activation	activation	NOUN
cana-1862	253	65	function	function	NOUN
cana-1862	253	66	.	.	PUNCT
cana-1862	254	1	this	this	DET
cana-1862	254	2	process	process	NOUN
cana-1862	254	3	enables	enable	VERB
cana-1862	254	4	the	the	DET
cana-1862	254	5	model	model	NOUN
cana-1862	254	6	to	to	PART
cana-1862	254	7	learn	learn	VERB
cana-1862	254	8	node	node	ADJ
cana-1862	254	9	representations	representation	NOUN
cana-1862	254	10	that	that	PRON
cana-1862	254	11	capture	capture	VERB
cana-1862	254	12	local	local	ADJ
cana-1862	254	13	and	and	CCONJ
cana-1862	254	14	global	global	ADJ
cana-1862	254	15	graph	graph	NOUN
cana-1862	254	16	structures	structure	NOUN
cana-1862	254	17	,	,	PUNCT
cana-1862	254	18	aiding	aid	VERB
cana-1862	254	19	in	in	ADP
cana-1862	254	20	the	the	DET
cana-1862	254	21	identification	identification	NOUN
cana-1862	254	22	of	of	ADP
cana-1862	254	23	vulnerabilities	vulnerability	NOUN
cana-1862	254	24	across	across	ADP
cana-1862	254	25	network	network	NOUN
cana-1862	254	26	nodes	node	NOUN
cana-1862	254	27	.	.	PUNCT
cana-1862	255	1	o	o	X
cana-1862	255	2	hidden	hide	VERB
cana-1862	255	3	markov	markov	NOUN
cana-1862	255	4	models	model	NOUN
cana-1862	255	5	(	(	PUNCT
cana-1862	255	6	hmms	hmms	NOUN
cana-1862	255	7	):	):	PUNCT
cana-1862	255	8	in	in	ADP
cana-1862	255	9	particular	particular	ADJ
cana-1862	255	10	,	,	PUNCT
cana-1862	255	11	hidden	hide	VERB
cana-1862	255	12	markov	markov	NOUN
cana-1862	255	13	models	model	NOUN
cana-1862	255	14	(	(	PUNCT
cana-1862	255	15	hmms	hmms	NOUN
cana-1862	255	16	)	)	PUNCT
cana-1862	255	17	have	have	AUX
cana-1862	255	18	been	be	AUX
cana-1862	255	19	applied	apply	VERB
cana-1862	255	20	to	to	PART
cana-1862	255	21	represent	represent	VERB
cana-1862	255	22	the	the	DET
cana-1862	255	23	temporal	temporal	ADJ
cana-1862	255	24	dependencies	dependency	NOUN
cana-1862	255	25	amongst	amongst	ADP
cana-1862	255	26	network	network	NOUN
cana-1862	255	27	traffic	traffic	NOUN
cana-1862	255	28	,	,	PUNCT
cana-1862	255	29	as	as	ADP
cana-1862	255	30	part	part	NOUN
cana-1862	255	31	of	of	ADP
cana-1862	255	32	an	an	DET
cana-1862	255	33	effort	effort	NOUN
cana-1862	255	34	to	to	PART
cana-1862	255	35	describe	describe	VERB
cana-1862	255	36	how	how	SCONJ
cana-1862	255	37	the	the	DET
cana-1862	255	38	global	global	ADJ
cana-1862	255	39	state	state	NOUN
cana-1862	255	40	of	of	ADP
cana-1862	255	41	a	a	DET
cana-1862	255	42	network	network	NOUN
cana-1862	255	43	evolves	evolve	VERB
cana-1862	255	44	over	over	ADP
cana-1862	255	45	time	time	NOUN
cana-1862	255	46	.	.	PUNCT
cana-1862	256	1	the	the	DET
cana-1862	256	2	two	two	NUM
cana-1862	256	3	comprise	comprise	NOUN
cana-1862	256	4	of	of	ADP
cana-1862	256	5	hidden	hidden	ADJ
cana-1862	256	6	states	state	NOUN
cana-1862	256	7	and	and	CCONJ
cana-1862	256	8	observable	observable	ADJ
cana-1862	256	9	emissions	emission	NOUN
cana-1862	256	10	,	,	PUNCT
cana-1862	256	11	which	which	PRON
cana-1862	256	12	are	be	AUX
cana-1862	256	13	known	know	VERB
cana-1862	256	14	as	as	ADP
cana-1862	256	15	state	state	NOUN
cana-1862	256	16	transition	transition	NOUN
cana-1862	256	17	probabilities	probability	NOUN
cana-1862	256	18	and	and	CCONJ
cana-1862	256	19	emission	emission	NOUN
cana-1862	256	20	probabilities	probability	NOUN
cana-1862	256	21	.	.	PUNCT
cana-1862	257	1	to	to	PART
cana-1862	257	2	achieve	achieve	VERB
cana-1862	257	3	this	this	PRON
cana-1862	257	4	,	,	PUNCT
cana-1862	257	5	we	we	PRON
cana-1862	257	6	use	use	VERB
cana-1862	257	7	the	the	DET
cana-1862	257	8	baum	baum	PROPN
cana-1862	257	9	-	-	PUNCT
cana-1862	257	10	welch	welch	PROPN
cana-1862	257	11	algorithm	algorithm	NOUN
cana-1862	257	12	to	to	PART
cana-1862	257	13	estimate	estimate	VERB
cana-1862	257	14	the	the	DET
cana-1862	257	15	parameters	parameter	NOUN
cana-1862	257	16	of	of	ADP
cana-1862	257	17	the	the	DET
cana-1862	257	18	hmm	hmm	NOUN
cana-1862	257	19	.	.	PUNCT
cana-1862	258	1	the	the	DET
cana-1862	258	2	model	model	NOUN
cana-1862	258	3	can	can	AUX
cana-1862	258	4	be	be	AUX
cana-1862	258	5	described	describe	VERB
cana-1862	258	6	as	as	ADP
cana-1862	258	7	follows	follow	VERB
cana-1862	258	8	:	:	PUNCT
cana-1862	258	9	𝑃(𝑋	𝑃(𝑋	PROPN
cana-1862	258	10	,	,	PUNCT
cana-1862	258	11	𝑆	𝑆	PROPN
cana-1862	258	12	)	)	PUNCT
cana-1862	258	13	=	=	SYM
cana-1862	259	1	𝑃(𝑆1	𝑃(𝑆1	NUM
cana-1862	259	2	)	)	PUNCT
cana-1862	259	3	∏	∏	PROPN
cana-1862	259	4	𝑇	𝑇	PROPN
cana-1862	259	5	𝑡=2	𝑡=2	ADJ
cana-1862	259	6	𝑃(𝑆𝑡	𝑃(𝑆𝑡	ADJ
cana-1862	259	7	∣	∣	ADJ
cana-1862	259	8	𝑆𝑡−1	𝑆𝑡−1	PROPN
cana-1862	259	9	)	)	PUNCT
cana-1862	259	10	∏	∏	PROPN
cana-1862	259	11	𝑇	𝑇	PROPN
cana-1862	259	12	𝑡=1	𝑡=1	PROPN
cana-1862	259	13	𝑃(𝑋𝑡	𝑃(𝑋𝑡	NUM
cana-1862	259	14	∣	∣	PROPN
cana-1862	259	15	𝑆𝑡	𝑆𝑡	PROPN
cana-1862	259	16	)	)	PUNCT
cana-1862	259	17	,	,	PUNCT
cana-1862	259	18	where	where	SCONJ
cana-1862	259	19	,	,	PUNCT
cana-1862	259	20	𝑆𝑡	𝑆𝑡	PROPN
cana-1862	259	21	represents	represent	VERB
cana-1862	259	22	the	the	DET
cana-1862	259	23	hidden	hidden	ADJ
cana-1862	259	24	state	state	NOUN
cana-1862	259	25	at	at	ADP
cana-1862	259	26	time	time	NOUN
cana-1862	259	27	𝑡	𝑡	PROPN
cana-1862	259	28	,	,	PUNCT
cana-1862	259	29	and	and	CCONJ
cana-1862	259	30	𝑋𝑡	𝑋𝑡	PROPN
cana-1862	259	31	is	be	AUX
cana-1862	259	32	the	the	DET
cana-1862	259	33	observed	observe	VERB
cana-1862	259	34	data	datum	NOUN
cana-1862	259	35	at	at	ADP
cana-1862	259	36	time	time	NOUN
cana-1862	259	37	𝑡.	𝑡.	NOUN
cana-1862	259	38	●	●	NUM
cana-1862	259	39	hybrid	hybrid	NOUN
cana-1862	259	40	models	model	NOUN
cana-1862	259	41	communications	communication	NOUN
cana-1862	259	42	on	on	ADP
cana-1862	259	43	applied	apply	VERB
cana-1862	259	44	nonlinear	nonlinear	ADJ
cana-1862	259	45	analysis	analysis	NOUN
cana-1862	259	46	issn	issn	NOUN
cana-1862	259	47	:	:	PUNCT
cana-1862	259	48	1074	1074	NUM
cana-1862	259	49	-	-	PUNCT
cana-1862	259	50	133x	133x	NUM
cana-1862	259	51	vol	vol	NOUN
cana-1862	259	52	32	32	NUM
cana-1862	259	53	no	no	NOUN
cana-1862	259	54	.	.	NOUN
cana-1862	259	55	2	2	NUM
cana-1862	259	56	(	(	PUNCT
cana-1862	259	57	2025	2025	NUM
cana-1862	259	58	)	)	PUNCT
cana-1862	259	59	707	707	NUM
cana-1862	259	60	https://internationalpubls.com	https://internationalpubls.com	X
cana-1862	259	61	this	this	DET
cana-1862	259	62	often	often	ADV
cana-1862	259	63	increases	increase	VERB
cana-1862	259	64	the	the	DET
cana-1862	259	65	potential	potential	ADJ
cana-1862	259	66	powers	power	NOUN
cana-1862	259	67	of	of	ADP
cana-1862	259	68	the	the	DET
cana-1862	259	69	vulnerability	vulnerability	NOUN
cana-1862	259	70	identification	identification	NOUN
cana-1862	259	71	as	as	SCONJ
cana-1862	259	72	one	one	PRON
cana-1862	259	73	may	may	AUX
cana-1862	259	74	say	say	VERB
cana-1862	259	75	by	by	ADP
cana-1862	259	76	combining	combine	VERB
cana-1862	259	77	multiple	multiple	ADJ
cana-1862	259	78	models	model	NOUN
cana-1862	259	79	.	.	PUNCT
cana-1862	260	1	as	as	ADP
cana-1862	260	2	an	an	DET
cana-1862	260	3	example	example	NOUN
cana-1862	260	4	,	,	PUNCT
cana-1862	260	5	a	a	DET
cana-1862	260	6	hybrid	hybrid	ADJ
cana-1862	260	7	system	system	NOUN
cana-1862	260	8	might	might	AUX
cana-1862	260	9	combine	combine	VERB
cana-1862	260	10	an	an	DET
cana-1862	260	11	auto	auto	NOUN
cana-1862	260	12	-	-	PUNCT
cana-1862	260	13	encoder	encoder	NOUN
cana-1862	260	14	for	for	ADP
cana-1862	260	15	anomaly	anomaly	NOUN
cana-1862	260	16	detection	detection	NOUN
cana-1862	260	17	with	with	ADP
cana-1862	260	18	the	the	DET
cana-1862	260	19	xgboost	xgboost	NOUN
cana-1862	260	20	of	of	ADP
cana-1862	260	21	type	type	NOUN
cana-1862	260	22	of	of	ADP
cana-1862	260	23	vulnerabilities	vulnerability	NOUN
cana-1862	260	24	identified	identify	VERB
cana-1862	260	25	.	.	PUNCT
cana-1862	261	1	●	●	PUNCT
cana-1862	261	2	optimization	optimization	NOUN
cana-1862	261	3	and	and	CCONJ
cana-1862	261	4	training	training	NOUN
cana-1862	261	5	in	in	ADP
cana-1862	261	6	machine	machine	NOUN
cana-1862	261	7	learning	learning	NOUN
cana-1862	261	8	model	model	NOUN
cana-1862	261	9	training	training	NOUN
cana-1862	261	10	is	be	AUX
cana-1862	261	11	the	the	DET
cana-1862	261	12	process	process	NOUN
cana-1862	261	13	of	of	ADP
cana-1862	261	14	tweaking	tweak	VERB
cana-1862	261	15	the	the	DET
cana-1862	261	16	model	model	NOUN
cana-1862	261	17	parameters	parameter	NOUN
cana-1862	261	18	in	in	ADP
cana-1862	261	19	order	order	NOUN
cana-1862	261	20	to	to	PART
cana-1862	261	21	reduce	reduce	VERB
cana-1862	261	22	a	a	DET
cana-1862	261	23	selected	select	VERB
cana-1862	261	24	loss	loss	NOUN
cana-1862	261	25	function	function	NOUN
cana-1862	261	26	.	.	PUNCT
cana-1862	262	1	and	and	CCONJ
cana-1862	262	2	it	it	PRON
cana-1862	262	3	is	be	AUX
cana-1862	262	4	because	because	SCONJ
cana-1862	262	5	we	we	PRON
cana-1862	262	6	need	need	VERB
cana-1862	262	7	this	this	DET
cana-1862	262	8	generalization	generalization	NOUN
cana-1862	262	9	in	in	ADP
cana-1862	262	10	our	our	PRON
cana-1862	262	11	model	model	NOUN
cana-1862	262	12	to	to	PART
cana-1862	262	13	be	be	AUX
cana-1862	262	14	able	able	ADJ
cana-1862	262	15	to	to	PART
cana-1862	262	16	detect	detect	VERB
cana-1862	262	17	problems	problem	NOUN
cana-1862	262	18	that	that	PRON
cana-1862	262	19	not	not	PART
cana-1862	262	20	only	only	ADV
cana-1862	262	21	the	the	DET
cana-1862	262	22	ones	one	NOUN
cana-1862	262	23	seen	see	VERB
cana-1862	262	24	during	during	ADP
cana-1862	262	25	training	training	NOUN
cana-1862	262	26	.	.	PUNCT
cana-1862	263	1	o	o	X
cana-1862	263	2	optimization	optimization	NOUN
cana-1862	263	3	techniques	technique	NOUN
cana-1862	263	4	:	:	PUNCT
cana-1862	263	5	gradient	gradient	ADJ
cana-1862	263	6	descent	descent	NOUN
cana-1862	263	7	:	:	PUNCT
cana-1862	263	8	an	an	DET
cana-1862	263	9	iterative	iterative	NOUN
cana-1862	263	10	minimization	minimization	NOUN
cana-1862	263	11	algorithm	algorithm	NOUN
cana-1862	263	12	that	that	PRON
cana-1862	263	13	is	be	AUX
cana-1862	263	14	used	use	VERB
cana-1862	263	15	to	to	PART
cana-1862	263	16	find	find	VERB
cana-1862	263	17	the	the	DET
cana-1862	263	18	set	set	NOUN
cana-1862	263	19	of	of	ADP
cana-1862	263	20	parameters	parameter	NOUN
cana-1862	263	21	which	which	PRON
cana-1862	263	22	gives	give	VERB
cana-1862	263	23	the	the	DET
cana-1862	263	24	minimal	minimal	ADJ
cana-1862	263	25	value	value	NOUN
cana-1862	263	26	of	of	ADP
cana-1862	263	27	loss	loss	NOUN
cana-1862	263	28	function	function	NOUN
cana-1862	263	29	.	.	PUNCT
cana-1862	264	1	𝜃	𝜃	X
cana-1862	264	2	←	←	PROPN
cana-1862	264	3	𝜃	𝜃	X
cana-1862	264	4	−	−	PROPN
cana-1862	264	5	𝜂𝛻𝐿(𝜃	𝜂𝛻𝐿(𝜃	NUM
cana-1862	264	6	)	)	PUNCT
cana-1862	264	7	,	,	PUNCT
cana-1862	264	8	regularization	regularization	NOUN
cana-1862	264	9	:	:	PUNCT
cana-1862	264	10	regularisation	regularisation	NOUN
cana-1862	264	11	is	be	AUX
cana-1862	264	12	an	an	DET
cana-1862	264	13	important	important	ADJ
cana-1862	264	14	weapon	weapon	NOUN
cana-1862	264	15	to	to	PART
cana-1862	264	16	prevent	prevent	VERB
cana-1862	264	17	overfitting	overfitting	NOUN
cana-1862	264	18	,	,	PUNCT
cana-1862	264	19	two	two	NUM
cana-1862	264	20	most	most	ADV
cana-1862	264	21	common	common	ADJ
cana-1862	264	22	are	be	AUX
cana-1862	264	23	l1	l1	PROPN
cana-1862	264	24	(	(	PUNCT
cana-1862	264	25	lasso	lasso	PROPN
cana-1862	264	26	)	)	PUNCT
cana-1862	264	27	and	and	CCONJ
cana-1862	264	28	l2	l2	PROPN
cana-1862	264	29	ridge	ridge	PROPN
cana-1862	264	30	regularisation	regularisation	NOUN
cana-1862	264	31	.	.	PUNCT
cana-1862	265	1	in	in	ADP
cana-1862	265	2	l2	l2	NOUN
cana-1862	265	3	regularization	regularization	NOUN
cana-1862	265	4	,	,	PUNCT
cana-1862	265	5	term	term	NOUN
cana-1862	265	6	which	which	PRON
cana-1862	265	7	is	be	AUX
cana-1862	265	8	controlled	control	VERB
cana-1862	265	9	by	by	ADP
cana-1862	265	10	c	c	PROPN
cana-1862	265	11	is	be	AUX
cana-1862	265	12	the	the	DET
cana-1862	265	13	sum	sum	NOUN
cana-1862	265	14	of	of	ADP
cana-1862	265	15	square	square	ADJ
cana-1862	265	16	value	value	NOUN
cana-1862	265	17	of	of	ADP
cana-1862	265	18	weights	weight	NOUN
cana-1862	265	19	and	and	CCONJ
cana-1862	265	20	bias	bias	NOUN
cana-1862	265	21	while	while	SCONJ
cana-1862	265	22	optimizing	optimize	VERB
cana-1862	265	23	the	the	DET
cana-1862	265	24	loss	loss	NOUN
cana-1862	265	25	function	function	NOUN
cana-1862	265	26	waged	wage	VERB
cana-1862	265	27	with	with	ADP
cana-1862	265	28	this	this	DET
cana-1862	265	29	parameter	parameter	NOUN
cana-1862	265	30	.	.	PUNCT
cana-1862	266	1	𝐿𝑟𝑒𝑔(𝜃	𝐿𝑟𝑒𝑔(𝜃	NUM
cana-1862	266	2	)	)	PUNCT
cana-1862	266	3	=	=	SYM
cana-1862	267	1	𝐿(𝜃	𝐿(𝜃	X
cana-1862	267	2	)	)	PUNCT
cana-1862	267	3	+	+	CCONJ
cana-1862	267	4	𝜆	𝜆	ADP
cana-1862	267	5	∑	∑	PROPN
cana-1862	267	6	𝑑	𝑑	PROPN
cana-1862	267	7	𝑗=1	𝑗=1	PROPN
cana-1862	267	8	𝜃𝑗	𝜃𝑗	ADP
cana-1862	267	9	2	2	NUM
cana-1862	267	10	,	,	PUNCT
cana-1862	267	11	where	where	SCONJ
cana-1862	267	12	,	,	PUNCT
cana-1862	267	13	𝜆	𝜆	PRON
cana-1862	267	14	is	be	AUX
cana-1862	267	15	the	the	DET
cana-1862	267	16	regularization	regularization	NOUN
cana-1862	267	17	parameter	parameter	NOUN
cana-1862	267	18	controlling	control	VERB
cana-1862	267	19	the	the	DET
cana-1862	267	20	strength	strength	NOUN
cana-1862	267	21	of	of	ADP
cana-1862	267	22	the	the	DET
cana-1862	267	23	penalty	penalty	NOUN
cana-1862	267	24	.	.	PUNCT
cana-1862	268	1	implementation	implementation	NOUN
cana-1862	268	2	can	can	AUX
cana-1862	268	3	be	be	AUX
cana-1862	268	4	done	do	VERB
cana-1862	268	5	in	in	ADP
cana-1862	268	6	python	python	NOUN
cana-1862	268	7	and	and	CCONJ
cana-1862	268	8	we	we	PRON
cana-1862	268	9	can	can	AUX
cana-1862	268	10	use	use	VERB
cana-1862	268	11	libraries	library	NOUN
cana-1862	268	12	such	such	ADJ
cana-1862	268	13	as	as	ADP
cana-1862	268	14	scikit	scikit	NOUN
cana-1862	268	15	-	-	PUNCT
cana-1862	268	16	learn	learn	VERB
cana-1862	268	17	(	(	PUNCT
cana-1862	268	18	for	for	ADP
cana-1862	268	19	xgboost	xgboost	ADV
cana-1862	268	20	,	,	PUNCT
cana-1862	268	21	clustering	clustering	ADJ
cana-1862	268	22	and	and	CCONJ
cana-1862	268	23	basic	basic	ADJ
cana-1862	268	24	models	model	NOUN
cana-1862	268	25	)	)	PUNCT
cana-1862	268	26	,	,	PUNCT
cana-1862	268	27	tensorflow	tensorflow	NOUN
cana-1862	268	28	or	or	CCONJ
cana-1862	268	29	pytorch	pytorch	NOUN
cana-1862	268	30	(	(	PUNCT
cana-1862	268	31	for	for	ADP
cana-1862	268	32	deep	deep	ADJ
cana-1862	268	33	learning	learning	NOUN
cana-1862	268	34	models	model	NOUN
cana-1862	268	35	like	like	ADP
cana-1862	268	36	auto	auto	NOUN
cana-1862	268	37	-	-	PUNCT
cana-1862	268	38	encoders	encoder	NOUN
cana-1862	268	39	,	,	PUNCT
cana-1862	268	40	fcnns	fcnn	NOUN
cana-1862	268	41	)	)	PUNCT
cana-1862	268	42	for	for	ADP
cana-1862	268	43	developing	develop	VERB
cana-1862	268	44	our	our	PRON
cana-1862	268	45	model	model	NOUN
cana-1862	268	46	,	,	PUNCT
cana-1862	268	47	pandas	panda	NOUN
cana-1862	268	48	for	for	ADP
cana-1862	268	49	data	datum	NOUN
cana-1862	268	50	pre	pre	ADJ
cana-1862	268	51	-	-	NOUN
cana-1862	268	52	processing	processing	ADJ
cana-1862	268	53	.	.	PUNCT
cana-1862	269	1	specialized	specialized	ADJ
cana-1862	269	2	libraries	library	NOUN
cana-1862	269	3	such	such	ADJ
cana-1862	269	4	as	as	ADP
cana-1862	269	5	pgmpy	pgmpy	NOUN
cana-1862	269	6	(	(	PUNCT
cana-1862	269	7	for	for	ADP
cana-1862	269	8	bayesian	bayesian	NOUN
cana-1862	269	9	networks	network	NOUN
cana-1862	269	10	)	)	PUNCT
cana-1862	269	11	and	and	CCONJ
cana-1862	269	12	hmmlearn	hmmlearn	VERB
cana-1862	269	13	(	(	PUNCT
cana-1862	269	14	for	for	ADP
cana-1862	269	15	hidden	hide	VERB
cana-1862	269	16	markov	markov	NOUN
cana-1862	269	17	models	model	NOUN
cana-1862	269	18	)	)	PUNCT
cana-1862	269	19	that	that	PRON
cana-1862	269	20	can	can	AUX
cana-1862	269	21	be	be	AUX
cana-1862	269	22	used	use	VERB
cana-1862	269	23	to	to	PART
cana-1862	269	24	implement	implement	VERB
cana-1862	269	25	probabilistic	probabilistic	ADJ
cana-1862	269	26	models	model	NOUN
cana-1862	269	27	.	.	PUNCT
cana-1862	270	1	hyper	hyper	ADJ
cana-1862	270	2	-	-	ADJ
cana-1862	270	3	parameter	parameter	ADJ
cana-1862	270	4	tuning	tuning	NOUN
cana-1862	270	5	helps	help	VERB
cana-1862	270	6	enhance	enhance	VERB
cana-1862	270	7	the	the	DET
cana-1862	270	8	model	model	NOUN
cana-1862	270	9	performance	performance	NOUN
cana-1862	270	10	.	.	PUNCT
cana-1862	271	1	several	several	ADJ
cana-1862	271	2	ways	way	NOUN
cana-1862	271	3	are	be	AUX
cana-1862	271	4	taken	take	VERB
cana-1862	271	5	to	to	PART
cana-1862	271	6	find	find	VERB
cana-1862	271	7	all	all	DET
cana-1862	271	8	the	the	DET
cana-1862	271	9	best	good	ADJ
cana-1862	271	10	hyper	hyper	NOUN
cana-1862	271	11	-	-	NOUN
cana-1862	271	12	parameters	parameter	NOUN
cana-1862	271	13	for	for	ADP
cana-1862	271	14	these	these	DET
cana-1862	271	15	models	model	NOUN
cana-1862	271	16	like	like	ADP
cana-1862	271	17	grid	grid	NOUN
cana-1862	271	18	search	search	NOUN
cana-1862	271	19	,	,	PUNCT
cana-1862	271	20	random	random	ADJ
cana-1862	271	21	search	search	NOUN
cana-1862	271	22	etc	etc	X
cana-1862	271	23	.	.	X
cana-1862	272	1	early	early	ADJ
cana-1862	272	2	stopping	stop	VERB
cana-1862	272	3	and	and	CCONJ
cana-1862	272	4	learning	learn	VERB
cana-1862	272	5	rate	rate	NOUN
cana-1862	272	6	decaying	decay	VERB
cana-1862	272	7	are	be	AUX
cana-1862	272	8	inevitable	inevitable	ADJ
cana-1862	272	9	techniques	technique	NOUN
cana-1862	272	10	for	for	ADP
cana-1862	272	11	a	a	DET
cana-1862	272	12	well	well	ADV
cana-1862	272	13	-	-	PUNCT
cana-1862	272	14	behaved	behave	VERB
cana-1862	272	15	training	training	NOUN
cana-1862	272	16	of	of	ADP
cana-1862	272	17	deep	deep	ADJ
cana-1862	272	18	learning	learning	NOUN
cana-1862	272	19	model	model	NOUN
cana-1862	272	20	.	.	PUNCT
cana-1862	273	1	the	the	DET
cana-1862	273	2	purpose	purpose	NOUN
cana-1862	273	3	of	of	ADP
cana-1862	273	4	this	this	DET
cana-1862	273	5	methodology	methodology	NOUN
cana-1862	273	6	is	be	AUX
cana-1862	273	7	to	to	PART
cana-1862	273	8	introduce	introduce	VERB
cana-1862	273	9	a	a	DET
cana-1862	273	10	unified	unified	ADJ
cana-1862	273	11	approach	approach	NOUN
cana-1862	273	12	to	to	ADP
cana-1862	273	13	information	information	NOUN
cana-1862	273	14	security	security	NOUN
cana-1862	273	15	vulnerability	vulnerability	NOUN
cana-1862	273	16	detection	detection	NOUN
cana-1862	273	17	,	,	PUNCT
cana-1862	273	18	by	by	ADP
cana-1862	273	19	leveraging	leverage	VERB
cana-1862	273	20	advanced	advanced	ADJ
cana-1862	273	21	mathematical	mathematical	ADJ
cana-1862	273	22	techniques	technique	NOUN
cana-1862	273	23	and	and	CCONJ
cana-1862	273	24	machine	machine	NOUN
cana-1862	273	25	learning	learning	NOUN
cana-1862	273	26	models	model	NOUN
cana-1862	273	27	.	.	PUNCT
cana-1862	274	1	this	this	DET
cana-1862	274	2	methodology	methodology	NOUN
cana-1862	274	3	also	also	ADV
cana-1862	274	4	mixes	mix	VERB
cana-1862	274	5	supervised	supervised	ADJ
cana-1862	274	6	learning	learning	NOUN
cana-1862	274	7	(	(	PUNCT
cana-1862	274	8	e.g.	e.g.	ADV
cana-1862	274	9	,	,	PUNCT
cana-1862	274	10	xgboost	xgboost	NUM
cana-1862	274	11	)	)	PUNCT
cana-1862	274	12	,	,	PUNCT
cana-1862	274	13	unsupervised	unsupervised	ADJ
cana-1862	274	14	learning	learning	NOUN
cana-1862	274	15	(	(	PUNCT
cana-1862	274	16	e.g.	e.g.	ADV
cana-1862	274	17	,	,	PUNCT
cana-1862	274	18	auto	auto	NOUN
cana-1862	274	19	-	-	PUNCT
cana-1862	274	20	encoders	encoder	NOUN
cana-1862	274	21	,	,	PUNCT
cana-1862	274	22	clustering	clustering	NOUN
cana-1862	274	23	)	)	PUNCT
cana-1862	274	24	and	and	CCONJ
cana-1862	274	25	probabilistic	probabilistic	ADJ
cana-1862	274	26	models	model	NOUN
cana-1862	274	27	(	(	PUNCT
cana-1862	274	28	e.g.	e.g.	ADV
cana-1862	274	29	,	,	PUNCT
cana-1862	274	30	bayesian	bayesian	NOUN
cana-1862	274	31	networks	network	NOUN
cana-1862	274	32	,	,	PUNCT
cana-1862	274	33	hmms	hmms	NOUN
cana-1862	274	34	)	)	PUNCT
cana-1862	274	35	to	to	PART
cana-1862	274	36	develop	develop	VERB
cana-1862	274	37	a	a	DET
cana-1862	274	38	versatile	versatile	ADJ
cana-1862	274	39	system	system	NOUN
cana-1862	274	40	able	able	ADJ
cana-1862	274	41	to	to	PART
cana-1862	274	42	identify	identify	VERB
cana-1862	274	43	a	a	DET
cana-1862	274	44	broad	broad	ADJ
cana-1862	274	45	spectrum	spectrum	NOUN
cana-1862	274	46	of	of	ADP
cana-1862	274	47	vulnerabilities	vulnerability	NOUN
cana-1862	274	48	including	include	VERB
cana-1862	274	49	zero	zero	NUM
cana-1862	274	50	-	-	PUNCT
cana-1862	274	51	day	day	NOUN
cana-1862	274	52	attacks	attack	NOUN
cana-1862	274	53	.	.	PUNCT
cana-1862	275	1	it	it	PRON
cana-1862	275	2	also	also	ADV
cana-1862	275	3	enhances	enhance	VERB
cana-1862	275	4	the	the	DET
cana-1862	275	5	immunity	immunity	NOUN
cana-1862	275	6	of	of	ADP
cana-1862	275	7	detection	detection	NOUN
cana-1862	275	8	process	process	NOUN
cana-1862	275	9	by	by	ADP
cana-1862	275	10	including	include	VERB
cana-1862	275	11	hybrid	hybrid	ADJ
cana-1862	275	12	models	model	NOUN
cana-1862	275	13	and	and	CCONJ
cana-1862	275	14	mathematical	mathematical	ADJ
cana-1862	275	15	methodologies	methodology	NOUN
cana-1862	275	16	aver	aver	NOUN
cana-1862	275	17	using	use	VERB
cana-1862	275	18	pca	pca	NOUN
cana-1862	275	19	for	for	ADP
cana-1862	275	20	dimensionality	dimensionality	NOUN
cana-1862	275	21	reduction	reduction	NOUN
cana-1862	275	22	and	and	CCONJ
cana-1862	275	23	bayesian	bayesian	NOUN
cana-1862	275	24	inference	inference	NOUN
cana-1862	275	25	.	.	PUNCT
cana-1862	276	1	this	this	DET
cana-1862	276	2	complete	complete	ADJ
cana-1862	276	3	framework	framework	NOUN
cana-1862	276	4	can	can	AUX
cana-1862	276	5	be	be	AUX
cana-1862	276	6	tailored	tailor	VERB
cana-1862	276	7	and	and	CCONJ
cana-1862	276	8	implemented	implement	VERB
cana-1862	276	9	for	for	ADP
cana-1862	276	10	real	real	ADJ
cana-1862	276	11	-	-	PUNCT
cana-1862	276	12	world	world	NOUN
cana-1862	276	13	security	security	NOUN
cana-1862	276	14	use	use	NOUN
cana-1862	276	15	cases	case	NOUN
cana-1862	276	16	,	,	PUNCT
cana-1862	276	17	allowing	allow	VERB
cana-1862	276	18	organizations	organization	NOUN
cana-1862	276	19	a	a	DET
cana-1862	276	20	smart	smart	ADJ
cana-1862	276	21	adaptive	adaptive	ADJ
cana-1862	276	22	security	security	NOUN
cana-1862	276	23	solution	solution	NOUN
cana-1862	276	24	.	.	PUNCT
cana-1862	277	1	4	4	X
cana-1862	277	2	.	.	X
cana-1862	277	3	results	result	NOUN
cana-1862	277	4	:	:	PUNCT
cana-1862	277	5	the	the	DET
cana-1862	277	6	study	study	NOUN
cana-1862	277	7	presents	present	VERB
cana-1862	277	8	an	an	DET
cana-1862	277	9	image	image	NOUN
cana-1862	277	10	of	of	ADP
cana-1862	277	11	the	the	DET
cana-1862	277	12	same	same	ADJ
cana-1862	277	13	machine	machine	NOUN
cana-1862	277	14	learning	learning	NOUN
cana-1862	277	15	models	model	NOUN
cana-1862	277	16	and	and	CCONJ
cana-1862	277	17	approaches	approach	NOUN
cana-1862	277	18	for	for	ADP
cana-1862	277	19	vulnerability	vulnerability	NOUN
cana-1862	277	20	detection	detection	NOUN
cana-1862	277	21	,	,	PUNCT
cana-1862	277	22	as	as	SCONJ
cana-1862	277	23	practiced	practice	VERB
cana-1862	277	24	in	in	ADP
cana-1862	277	25	data	datum	NOUN
cana-1862	277	26	from	from	ADP
cana-1862	277	27	different	different	ADJ
cana-1862	277	28	terms	term	NOUN
cana-1862	277	29	good	good	ADJ
cana-1862	277	30	points	point	NOUN
cana-1862	277	31	and	and	CCONJ
cana-1862	277	32	bad	bad	ADJ
cana-1862	277	33	ones	one	NOUN
cana-1862	277	34	.	.	PUNCT
cana-1862	278	1	they	they	PRON
cana-1862	278	2	have	have	AUX
cana-1862	278	3	been	be	AUX
cana-1862	278	4	tested	test	VERB
cana-1862	278	5	communications	communication	NOUN
cana-1862	278	6	on	on	ADP
cana-1862	278	7	applied	apply	VERB
cana-1862	278	8	nonlinear	nonlinear	ADJ
cana-1862	278	9	analysis	analysis	NOUN
cana-1862	278	10	issn	issn	NOUN
cana-1862	278	11	:	:	PUNCT
cana-1862	278	12	1074	1074	NUM
cana-1862	278	13	-	-	PUNCT
cana-1862	278	14	133x	133x	NUM
cana-1862	278	15	vol	vol	NOUN
cana-1862	278	16	32	32	NUM
cana-1862	278	17	no	no	NOUN
cana-1862	278	18	.	.	NOUN
cana-1862	278	19	2	2	NUM
cana-1862	278	20	(	(	PUNCT
cana-1862	278	21	2025	2025	NUM
cana-1862	278	22	)	)	PUNCT
cana-1862	278	23	708	708	NUM
cana-1862	278	24	https://internationalpubls.com	https://internationalpubls.com	X
cana-1862	278	25	on	on	ADP
cana-1862	278	26	popular	popular	ADJ
cana-1862	278	27	datasets	dataset	NOUN
cana-1862	278	28	,	,	PUNCT
cana-1862	278	29	like	like	ADP
cana-1862	278	30	cicids	cicid	NOUN
cana-1862	278	31	2017	2017	NUM
cana-1862	278	32	,	,	PUNCT
cana-1862	278	33	unsw	unsw	NOUN
cana-1862	278	34	-	-	PUNCT
cana-1862	278	35	nb15	nb15	PROPN
cana-1862	278	36	,	,	PUNCT
cana-1862	278	37	custom	custom	NOUN
cana-1862	278	38	live	live	ADJ
cana-1862	278	39	network	network	NOUN
cana-1862	278	40	data	datum	NOUN
cana-1862	278	41	as	as	ADV
cana-1862	278	42	well	well	ADV
cana-1862	278	43	as	as	ADP
cana-1862	278	44	old	old	ADJ
cana-1862	278	45	ones	one	NOUN
cana-1862	278	46	(	(	PUNCT
cana-1862	278	47	kdd	kdd	PROPN
cana-1862	278	48	cup	cup	PROPN
cana-1862	278	49	99	99	NUM
cana-1862	278	50	and	and	CCONJ
cana-1862	278	51	darpa	darpa	PROPN
cana-1862	278	52	2000	2000	NUM
cana-1862	278	53	)	)	PUNCT
cana-1862	278	54	trying	try	VERB
cana-1862	278	55	to	to	PART
cana-1862	278	56	demonstrate	demonstrate	VERB
cana-1862	278	57	the	the	DET
cana-1862	278	58	adaptability	adaptability	NOUN
cana-1862	278	59	to	to	ADP
cana-1862	278	60	both	both	DET
cana-1862	278	61	recently	recently	ADV
cana-1862	278	62	detected	detect	VERB
cana-1862	278	63	and	and	CCONJ
cana-1862	278	64	future	future	ADJ
cana-1862	278	65	security	security	NOUN
cana-1862	278	66	challenges	challenge	NOUN
cana-1862	278	67	.	.	PUNCT
cana-1862	279	1	the	the	DET
cana-1862	279	2	results	result	NOUN
cana-1862	279	3	indicate	indicate	VERB
cana-1862	279	4	that	that	DET
cana-1862	279	5	machine	machine	NOUN
cana-1862	279	6	learning	learning	NOUN
cana-1862	279	7	combined	combine	VERB
cana-1862	279	8	with	with	ADP
cana-1862	279	9	advanced	advanced	ADJ
cana-1862	279	10	mathematical	mathematical	ADJ
cana-1862	279	11	techniques	technique	NOUN
cana-1862	279	12	can	can	AUX
cana-1862	279	13	be	be	AUX
cana-1862	279	14	powerful	powerful	ADJ
cana-1862	279	15	for	for	ADP
cana-1862	279	16	the	the	DET
cana-1862	279	17	real	real	ADJ
cana-1862	279	18	-	-	PUNCT
cana-1862	279	19	time	time	NOUN
cana-1862	279	20	identification	identification	NOUN
cana-1862	279	21	of	of	ADP
cana-1862	279	22	vulnerabilities	vulnerability	NOUN
cana-1862	279	23	,	,	PUNCT
cana-1862	279	24	including	include	VERB
cana-1862	279	25	zero	zero	NUM
cana-1862	279	26	-	-	PUNCT
cana-1862	279	27	day	day	NOUN
cana-1862	279	28	threats	threat	NOUN
cana-1862	279	29	in	in	ADP
cana-1862	279	30	network	network	NOUN
cana-1862	279	31	environment	environment	NOUN
cana-1862	279	32	.	.	PUNCT
cana-1862	280	1	●	●	PUNCT
cana-1862	280	2	supervised	supervised	ADJ
cana-1862	280	3	learning	learning	NOUN
cana-1862	280	4	models	model	NOUN
cana-1862	280	5	xgboost	xgboost	ADV
cana-1862	280	6	also	also	ADV
cana-1862	280	7	dominates	dominate	VERB
cana-1862	280	8	over	over	ADP
cana-1862	280	9	all	all	DET
cana-1862	280	10	other	other	ADJ
cana-1862	280	11	models	model	NOUN
cana-1862	280	12	in	in	ADP
cana-1862	280	13	accuracy	accuracy	NOUN
cana-1862	280	14	,	,	PUNCT
cana-1862	280	15	precision	precision	NOUN
cana-1862	280	16	and	and	CCONJ
cana-1862	280	17	recall	recall	NOUN
cana-1862	280	18	on	on	ADP
cana-1862	280	19	all	all	DET
cana-1862	280	20	datasets	dataset	NOUN
cana-1862	280	21	in	in	ADP
cana-1862	280	22	the	the	DET
cana-1862	280	23	domain	domain	NOUN
cana-1862	280	24	of	of	ADP
cana-1862	280	25	supervised	supervised	ADJ
cana-1862	280	26	learning	learning	NOUN
cana-1862	280	27	.	.	PUNCT
cana-1862	281	1	largest	large	ADJ
cana-1862	281	2	accuracy	accuracy	NOUN
cana-1862	281	3	has	have	AUX
cana-1862	281	4	been	be	AUX
cana-1862	281	5	obtained	obtain	VERB
cana-1862	281	6	for	for	ADP
cana-1862	281	7	custom	custom	NOUN
cana-1862	281	8	live	live	ADJ
cana-1862	281	9	dataset	dataset	NOUN
cana-1862	281	10	(	(	PUNCT
cana-1862	281	11	97.1	97.1	NUM
cana-1862	281	12	%	%	NOUN
cana-1862	281	13	)	)	PUNCT
cana-1862	281	14	and	and	CCONJ
cana-1862	281	15	cicids	cicid	NOUN
cana-1862	281	16	2017	2017	NUM
cana-1862	281	17	(	(	PUNCT
cana-1862	281	18	96.8	96.8	NUM
cana-1862	281	19	%	%	NOUN
cana-1862	281	20	)	)	PUNCT
cana-1862	281	21	,	,	PUNCT
cana-1862	281	22	representing	represent	VERB
cana-1862	281	23	its	its	PRON
cana-1862	281	24	strength	strength	NOUN
cana-1862	281	25	in	in	ADP
cana-1862	281	26	utilizing	utilize	VERB
cana-1862	281	27	network	network	NOUN
cana-1862	281	28	environments	environment	NOUN
cana-1862	281	29	of	of	ADP
cana-1862	281	30	different	different	ADJ
cana-1862	281	31	types	type	NOUN
cana-1862	281	32	.	.	PUNCT
cana-1862	282	1	the	the	DET
cana-1862	282	2	strength	strength	NOUN
cana-1862	282	3	of	of	ADP
cana-1862	282	4	xgboost	xgboost	ADV
cana-1862	282	5	is	be	AUX
cana-1862	282	6	that	that	SCONJ
cana-1862	282	7	it	it	PRON
cana-1862	282	8	can	can	AUX
cana-1862	282	9	process	process	VERB
cana-1862	282	10	high	high	ADJ
cana-1862	282	11	-	-	PUNCT
cana-1862	282	12	dimensional	dimensional	ADJ
cana-1862	282	13	data	datum	NOUN
cana-1862	282	14	since	since	SCONJ
cana-1862	282	15	keeping	keep	VERB
cana-1862	282	16	in	in	ADP
cana-1862	282	17	view	view	NOUN
cana-1862	282	18	feature	feature	NOUN
cana-1862	282	19	-	-	PUNCT
cana-1862	282	20	reduced	reduce	VERB
cana-1862	282	21	data	datum	NOUN
cana-1862	282	22	method	method	NOUN
cana-1862	282	23	pca	pca	PROPN
cana-1862	282	24	on	on	ADP
cana-1862	282	25	completion	completion	NOUN
cana-1862	282	26	then	then	ADV
cana-1862	282	27	used	use	VERB
cana-1862	282	28	.	.	PUNCT
cana-1862	283	1	the	the	DET
cana-1862	283	2	model	model	NOUN
cana-1862	283	3	also	also	ADV
cana-1862	283	4	excelled	excel	VERB
cana-1862	283	5	in	in	ADP
cana-1862	283	6	providing	provide	VERB
cana-1862	283	7	low	low	ADJ
cana-1862	283	8	false	false	ADJ
cana-1862	283	9	positive	positive	ADJ
cana-1862	283	10	rates	rate	NOUN
cana-1862	283	11	(	(	PUNCT
cana-1862	283	12	1.5–2	1.5–2	NOUN
cana-1862	283	13	%	%	NOUN
cana-1862	283	14	across	across	ADP
cana-1862	283	15	varied	varied	ADJ
cana-1862	283	16	datasets	dataset	NOUN
cana-1862	283	17	)	)	PUNCT
cana-1862	283	18	over	over	ADP
cana-1862	283	19	time	time	NOUN
cana-1862	283	20	,	,	PUNCT
cana-1862	283	21	which	which	PRON
cana-1862	283	22	suggests	suggest	VERB
cana-1862	283	23	that	that	SCONJ
cana-1862	283	24	it	it	PRON
cana-1862	283	25	will	will	AUX
cana-1862	283	26	be	be	AUX
cana-1862	283	27	capable	capable	ADJ
cana-1862	283	28	of	of	ADP
cana-1862	283	29	maintaining	maintain	VERB
cana-1862	283	30	this	this	DET
cana-1862	283	31	same	same	ADJ
cana-1862	283	32	level	level	NOUN
cana-1862	283	33	of	of	ADP
cana-1862	283	34	trustworthiness	trustworthiness	NOUN
cana-1862	283	35	if	if	SCONJ
cana-1862	283	36	deployed	deploy	VERB
cana-1862	283	37	at	at	ADP
cana-1862	283	38	scale	scale	NOUN
cana-1862	283	39	to	to	PART
cana-1862	283	40	monitor	monitor	VERB
cana-1862	283	41	networks	network	NOUN
cana-1862	283	42	in	in	ADP
cana-1862	283	43	real	real	ADJ
cana-1862	283	44	-	-	PUNCT
cana-1862	283	45	time	time	NOUN
cana-1862	283	46	.	.	PUNCT
cana-1862	284	1	fully	fully	ADV
cana-1862	284	2	connected	connect	VERB
cana-1862	284	3	neural	neural	ADJ
cana-1862	284	4	networks	network	NOUN
cana-1862	284	5	which	which	PRON
cana-1862	284	6	have	have	AUX
cana-1862	284	7	shown	show	VERB
cana-1862	284	8	robust	robust	ADJ
cana-1862	284	9	detection	detection	NOUN
cana-1862	284	10	performance	performance	NOUN
cana-1862	284	11	on	on	ADP
cana-1862	284	12	even	even	ADV
cana-1862	284	13	the	the	DET
cana-1862	284	14	challenging	challenging	ADJ
cana-1862	284	15	cases	case	NOUN
cana-1862	284	16	of	of	ADP
cana-1862	284	17	network	network	NOUN
cana-1862	284	18	data	datum	NOUN
cana-1862	284	19	in	in	ADP
cana-1862	284	20	fcnns	fcnn	NOUN
cana-1862	284	21	and	and	CCONJ
cana-1862	284	22	traditional	traditional	ADJ
cana-1862	284	23	back	back	ADV
cana-1862	284	24	-	-	PUNCT
cana-1862	284	25	doored	doore	VERB
cana-1862	284	26	neural	neural	ADJ
cana-1862	284	27	networks	network	NOUN
cana-1862	284	28	were	be	AUX
cana-1862	284	29	mostly	mostly	ADV
cana-1862	284	30	present	present	ADJ
cana-1862	284	31	otherwise	otherwise	ADV
cana-1862	284	32	.	.	PUNCT
cana-1862	285	1	accuracy	accuracy	NOUN
cana-1862	285	2	:	:	PUNCT
cana-1862	285	3	although	although	SCONJ
cana-1862	285	4	both	both	CCONJ
cana-1862	285	5	reliable	reliable	ADJ
cana-1862	285	6	and	and	CCONJ
cana-1862	285	7	stable	stable	ADJ
cana-1862	285	8	,	,	PUNCT
cana-1862	285	9	there	there	PRON
cana-1862	285	10	was	be	VERB
cana-1862	285	11	no	no	DET
cana-1862	285	12	real	real	ADJ
cana-1862	285	13	breakthrough	breakthrough	NOUN
cana-1862	285	14	in	in	ADP
cana-1862	285	15	accuracy	accuracy	NOUN
cana-1862	285	16	improvement	improvement	NOUN
cana-1862	285	17	over	over	ADP
cana-1862	285	18	the	the	DET
cana-1862	285	19	already	already	ADV
cana-1862	285	20	excellent	excellent	ADJ
cana-1862	285	21	94.8	94.8	NUM
cana-1862	285	22	%	%	NOUN
cana-1862	285	23	achieved	achieve	VERB
cana-1862	285	24	by	by	ADP
cana-1862	285	25	xgboost	xgboost	PROPN
cana-1862	285	26	;	;	PUNCT
cana-1862	285	27	a	a	DET
cana-1862	285	28	false	false	ADJ
cana-1862	285	29	positive	positive	ADJ
cana-1862	285	30	rate	rate	NOUN
cana-1862	285	31	varied	varied	ADJ
cana-1862	285	32	somewhere	somewhere	ADV
cana-1862	285	33	between	between	ADP
cana-1862	285	34	2.3–3.2	2.3–3.2	NOUN
cana-1862	285	35	%	%	NOUN
cana-1862	285	36	,	,	PUNCT
cana-1862	285	37	but	but	CCONJ
cana-1862	285	38	couldn´t	couldn´t	ADJ
cana-1862	285	39	beat	beat	VERB
cana-1862	285	40	out	out	ADP
cana-1862	285	41	xgboost	xgboost	ADV
cana-1862	285	42	here	here	ADV
cana-1862	285	43	,	,	PUNCT
cana-1862	285	44	either	either	ADV
cana-1862	285	45	;	;	PUNCT
cana-1862	285	46	this	this	PRON
cana-1862	285	47	is	be	AUX
cana-1862	285	48	a	a	DET
cana-1862	285	49	strong	strong	ADJ
cana-1862	285	50	evidence	evidence	NOUN
cana-1862	285	51	that	that	SCONJ
cana-1862	285	52	deep	deep	ADJ
cana-1862	285	53	learning	learning	NOUN
cana-1862	285	54	models	model	NOUN
cana-1862	285	55	outperform	outperform	VERB
cana-1862	285	56	traditional	traditional	ADJ
cana-1862	285	57	ml	ml	NOUN
cana-1862	285	58	algorithms	algorithm	NOUN
cana-1862	285	59	for	for	ADP
cana-1862	285	60	capturing	capture	VERB
cana-1862	285	61	non	non	ADJ
cana-1862	285	62	-	-	ADJ
cana-1862	285	63	linear	linear	ADJ
cana-1862	285	64	relationships	relationship	NOUN
cana-1862	285	65	in	in	ADP
cana-1862	285	66	the	the	DET
cana-1862	285	67	data	datum	NOUN
cana-1862	285	68	,	,	PUNCT
cana-1862	285	69	whereas	whereas	SCONJ
cana-1862	285	70	ensemble	ensemble	ADJ
cana-1862	285	71	methods	method	NOUN
cana-1862	285	72	like	like	ADP
cana-1862	285	73	xgboost	xgboost	ADV
cana-1862	285	74	lie	lie	VERB
cana-1862	285	75	approximately	approximately	ADV
cana-1862	285	76	in	in	ADP
cana-1862	285	77	between	between	ADP
cana-1862	285	78	deep	deep	ADJ
cana-1862	285	79	and	and	CCONJ
cana-1862	285	80	linear	linear	ADJ
cana-1862	285	81	learner	learner	NOUN
cana-1862	285	82	when	when	SCONJ
cana-1862	285	83	it	it	PRON
cana-1862	285	84	comes	come	VERB
cana-1862	285	85	to	to	ADP
cana-1862	285	86	accuracy	accuracy	NOUN
cana-1862	285	87	-	-	PUNCT
cana-1862	285	88	interpretability	interpretability	NOUN
cana-1862	285	89	trade	trade	NOUN
cana-1862	285	90	off	off	ADP
cana-1862	285	91	.	.	PUNCT
cana-1862	286	1	model	model	NOUN
cana-1862	286	2	dataset	dataset	PROPN
cana-1862	286	3	accuracy	accuracy	NOUN
cana-1862	286	4	precision	precision	NOUN
cana-1862	286	5	recall	recall	VERB
cana-1862	286	6	f1score	f1score	NOUN
cana-1862	286	7	training	training	NOUN
cana-1862	286	8	time	time	NOUN
cana-1862	286	9	(	(	PUNCT
cana-1862	286	10	s	s	NOUN
cana-1862	286	11	)	)	PUNCT
cana-1862	286	12	false	false	ADJ
cana-1862	286	13	positive	positive	ADJ
cana-1862	286	14	rate	rate	NOUN
cana-1862	286	15	(	(	PUNCT
cana-1862	286	16	%	%	INTJ
cana-1862	286	17	)	)	PUNCT
cana-1862	286	18	xgboost	xgboost	ADP
cana-1862	287	1	cicids	cicid	NOUN
cana-1862	287	2	2017	2017	NUM
cana-1862	287	3	96.8	96.8	NUM
cana-1862	287	4	%	%	NOUN
cana-1862	287	5	96.1	96.1	NUM
cana-1862	287	6	%	%	NOUN
cana-1862	287	7	97.2	97.2	NUM
cana-1862	287	8	%	%	NOUN
cana-1862	287	9	96.6	96.6	NUM
cana-1862	287	10	%	%	NOUN
cana-1862	287	11	150	150	NUM
cana-1862	287	12	1.8	1.8	NUM
cana-1862	287	13	%	%	NOUN
cana-1862	287	14	unswnb15	unswnb15	NOUN
cana-1862	287	15	95.5	95.5	NUM
cana-1862	287	16	%	%	NOUN
cana-1862	287	17	94.7	94.7	NUM
cana-1862	287	18	%	%	NOUN
cana-1862	287	19	96.0	96.0	NUM
cana-1862	287	20	%	%	NOUN
cana-1862	287	21	95.3	95.3	NUM
cana-1862	287	22	%	%	NOUN
cana-1862	287	23	200	200	NUM
cana-1862	287	24	2.0	2.0	NUM
cana-1862	287	25	%	%	NOUN
cana-1862	287	26	custom	custom	NOUN
cana-1862	287	27	live	live	VERB
cana-1862	287	28	dataset	dataset	VERB
cana-1862	287	29	97.1	97.1	NUM
cana-1862	287	30	%	%	NOUN
cana-1862	287	31	96.5	96.5	NUM
cana-1862	287	32	%	%	NOUN
cana-1862	287	33	97.8	97.8	NUM
cana-1862	287	34	%	%	NOUN
cana-1862	287	35	97.1	97.1	NUM
cana-1862	287	36	%	%	NOUN
cana-1862	287	37	220	220	NUM
cana-1862	287	38	1.5	1.5	NUM
cana-1862	287	39	%	%	NOUN
cana-1862	287	40	neural	neural	ADJ
cana-1862	287	41	network	network	NOUN
cana-1862	287	42	(	(	PUNCT
cana-1862	287	43	fcnn	fcnn	PROPN
cana-1862	287	44	)	)	PUNCT
cana-1862	287	45	cicids	cicid	NOUN
cana-1862	287	46	2017	2017	NUM
cana-1862	287	47	93.2	93.2	NUM
cana-1862	287	48	%	%	NOUN
cana-1862	287	49	92.4	92.4	NUM
cana-1862	287	50	%	%	NOUN
cana-1862	287	51	94.0	94.0	NUM
cana-1862	287	52	%	%	NOUN
cana-1862	287	53	93.2	93.2	NUM
cana-1862	287	54	%	%	NOUN
cana-1862	287	55	180	180	NUM
cana-1862	287	56	2.5	2.5	NUM
cana-1862	287	57	%	%	NOUN
cana-1862	287	58	unswnb15	unswnb15	NOUN
cana-1862	287	59	92.0	92.0	NUM
cana-1862	287	60	%	%	NOUN
cana-1862	287	61	91.1	91.1	NUM
cana-1862	287	62	%	%	NOUN
cana-1862	287	63	93.5	93.5	NUM
cana-1862	287	64	%	%	NOUN
cana-1862	287	65	92.3	92.3	NUM
cana-1862	287	66	%	%	NOUN
cana-1862	287	67	230	230	NUM
cana-1862	287	68	3.2	3.2	NUM
cana-1862	287	69	%	%	NOUN
cana-1862	287	70	custom	custom	NOUN
cana-1862	287	71	live	live	VERB
cana-1862	287	72	dataset	dataset	VERB
cana-1862	287	73	94.8	94.8	NUM
cana-1862	287	74	%	%	NOUN
cana-1862	287	75	94.0	94.0	NUM
cana-1862	287	76	%	%	NOUN
cana-1862	287	77	95.3	95.3	NUM
cana-1862	287	78	%	%	NOUN
cana-1862	287	79	94.6	94.6	NUM
cana-1862	287	80	%	%	NOUN
cana-1862	287	81	250	250	NUM
cana-1862	287	82	2.3	2.3	NUM
cana-1862	287	83	%	%	NOUN
cana-1862	287	84	communications	communication	NOUN
cana-1862	287	85	on	on	ADP
cana-1862	287	86	applied	apply	VERB
cana-1862	287	87	nonlinear	nonlinear	ADJ
cana-1862	287	88	analysis	analysis	NOUN
cana-1862	287	89	issn	issn	NOUN
cana-1862	287	90	:	:	PUNCT
cana-1862	287	91	1074	1074	NUM
cana-1862	287	92	-	-	PUNCT
cana-1862	287	93	133x	133x	NUM
cana-1862	287	94	vol	vol	NOUN
cana-1862	287	95	32	32	NUM
cana-1862	287	96	no	no	NOUN
cana-1862	287	97	.	.	NOUN
cana-1862	287	98	2	2	NUM
cana-1862	287	99	(	(	PUNCT
cana-1862	287	100	2025	2025	NUM
cana-1862	287	101	)	)	PUNCT
cana-1862	287	102	709	709	NUM
cana-1862	287	103	https://internationalpubls.com	https://internationalpubls.com	X
cana-1862	287	104	the	the	DET
cana-1862	287	105	following	follow	VERB
cana-1862	287	106	table	table	NOUN
cana-1862	287	107	summarizes	summarize	VERB
cana-1862	287	108	the	the	DET
cana-1862	287	109	model	model	NOUN
cana-1862	287	110	performance	performance	NOUN
cana-1862	287	111	and	and	CCONJ
cana-1862	287	112	computational	computational	ADJ
cana-1862	287	113	requirements	requirement	NOUN
cana-1862	287	114	of	of	ADP
cana-1862	287	115	xgboost	xgboost	NOUN
cana-1862	287	116	and	and	CCONJ
cana-1862	287	117	neural	neural	ADJ
cana-1862	287	118	networks	network	NOUN
cana-1862	287	119	using	use	VERB
cana-1862	287	120	various	various	ADJ
cana-1862	287	121	datasets	dataset	NOUN
cana-1862	287	122	,	,	PUNCT
cana-1862	287	123	such	such	ADJ
cana-1862	287	124	as	as	ADP
cana-1862	287	125	accuracy	accuracy	NOUN
cana-1862	287	126	,	,	PUNCT
cana-1862	287	127	precision	precision	NOUN
cana-1862	287	128	,	,	PUNCT
cana-1862	287	129	recall	recall	NOUN
cana-1862	287	130	,	,	PUNCT
cana-1862	287	131	f1	f1	NOUN
cana-1862	287	132	-	-	PUNCT
cana-1862	287	133	score	score	NOUN
cana-1862	287	134	,	,	PUNCT
cana-1862	287	135	training	training	NOUN
cana-1862	287	136	time	time	NOUN
cana-1862	287	137	in	in	ADP
cana-1862	287	138	sec(e	sec(e	NOUN
cana-1862	287	139	)	)	PUNCT
cana-1862	287	140	,	,	PUNCT
cana-1862	287	141	false	false	ADJ
cana-1862	287	142	-	-	PUNCT
cana-1862	287	143	positive	positive	ADJ
cana-1862	287	144	rate	rate	NOUN
cana-1862	287	145	,	,	PUNCT
cana-1862	287	146	etc	etc	X
cana-1862	287	147	.	.	X
cana-1862	288	1	●	●	PUNCT
cana-1862	288	2	unsupervised	unsupervised	ADJ
cana-1862	288	3	learning	learning	NOUN
cana-1862	288	4	task	task	NOUN
cana-1862	288	5	:	:	PUNCT
cana-1862	288	6	anomoly	anomoly	ADJ
cana-1862	288	7	detection	detection	NOUN
cana-1862	288	8	flexible	flexible	ADJ
cana-1862	288	9	custom	custom	NOUN
cana-1862	288	10	unsupervised	unsupervised	ADJ
cana-1862	288	11	models	model	NOUN
cana-1862	288	12	performed	perform	VERB
cana-1862	288	13	with	with	ADP
cana-1862	288	14	greater	great	ADJ
cana-1862	288	15	variance	variance	NOUN
cana-1862	288	16	in	in	ADP
cana-1862	288	17	anomaly	anomaly	NOUN
cana-1862	288	18	and	and	CCONJ
cana-1862	288	19	zero	zero	NUM
cana-1862	288	20	-	-	PUNCT
cana-1862	288	21	day	day	NOUN
cana-1862	288	22	detection	detection	NOUN
cana-1862	288	23	.	.	PUNCT
cana-1862	289	1	the	the	DET
cana-1862	289	2	autoencoders	autoencoder	NOUN
cana-1862	289	3	,	,	PUNCT
cana-1862	289	4	and	and	CCONJ
cana-1862	289	5	a	a	DET
cana-1862	289	6	probabilistic	probabilistic	ADJ
cana-1862	289	7	variant	variant	NOUN
cana-1862	289	8	called	call	VERB
cana-1862	289	9	variational	variational	ADJ
cana-1862	289	10	auto	auto	NOUN
cana-1862	289	11	-	-	PUNCT
cana-1862	289	12	encoders	encoder	NOUN
cana-1862	289	13	(	(	PUNCT
cana-1862	289	14	vaes	vaes	ADJ
cana-1862	289	15	)	)	PUNCT
cana-1862	289	16	,	,	PUNCT
cana-1862	289	17	achieved	achieve	VERB
cana-1862	289	18	high	high	ADJ
cana-1862	289	19	precision	precision	NOUN
cana-1862	289	20	-	-	PUNCT
cana-1862	289	21	recall	recall	NOUN
cana-1862	289	22	for	for	ADP
cana-1862	289	23	all	all	DET
cana-1862	289	24	detectors	detector	NOUN
cana-1862	289	25	,	,	PUNCT
cana-1862	289	26	especially	especially	ADV
cana-1862	289	27	the	the	DET
cana-1862	289	28	custom	custom	NOUN
cana-1862	289	29	live	live	VERB
cana-1862	289	30	dataset	dataset	NOUN
cana-1862	289	31	(	(	PUNCT
cana-1862	289	32	up	up	ADP
cana-1862	289	33	to	to	PART
cana-1862	289	34	94	94	NUM
cana-1862	289	35	%	%	NOUN
cana-1862	289	36	f1	f1	NOUN
cana-1862	289	37	-	-	PUNCT
cana-1862	289	38	score	score	NOUN
cana-1862	289	39	with	with	ADP
cana-1862	289	40	vaes	vaes	ADJ
cana-1862	289	41	)	)	PUNCT
cana-1862	289	42	.	.	PUNCT
cana-1862	290	1	the	the	DET
cana-1862	290	2	models	model	NOUN
cana-1862	290	3	running	run	VERB
cana-1862	290	4	with	with	ADP
cana-1862	290	5	the	the	DET
cana-1862	290	6	reconstruction	reconstruction	NOUN
cana-1862	290	7	error	error	NOUN
cana-1862	290	8	-	-	PUNCT
cana-1862	290	9	based	base	VERB
cana-1862	290	10	approach	approach	NOUN
cana-1862	290	11	were	be	AUX
cana-1862	290	12	able	able	ADJ
cana-1862	290	13	to	to	PART
cana-1862	290	14	nicely	nicely	ADV
cana-1862	290	15	separate	separate	VERB
cana-1862	290	16	benign	benign	ADJ
cana-1862	290	17	and	and	CCONJ
cana-1862	290	18	malicious	malicious	ADJ
cana-1862	290	19	patterns	pattern	NOUN
cana-1862	290	20	of	of	ADP
cana-1862	290	21	traffic	traffic	NOUN
cana-1862	290	22	.	.	PUNCT
cana-1862	291	1	nevertheless	nevertheless	ADV
cana-1862	291	2	,	,	PUNCT
cana-1862	291	3	broader	broad	ADJ
cana-1862	291	4	detection	detection	NOUN
cana-1862	291	5	capabilities	capability	NOUN
cana-1862	291	6	against	against	ADP
cana-1862	291	7	more	more	ADV
cana-1862	291	8	nuanced	nuanced	ADJ
cana-1862	291	9	anomalies	anomaly	NOUN
cana-1862	291	10	without	without	ADP
cana-1862	291	11	ground	ground	NOUN
cana-1862	291	12	truth	truth	NOUN
cana-1862	291	13	labeling	labeling	NOUN
cana-1862	291	14	position	position	NOUN
cana-1862	291	15	this	this	DET
cana-1862	291	16	class	class	NOUN
cana-1862	291	17	of	of	ADP
cana-1862	291	18	models	model	NOUN
cana-1862	291	19	as	as	ADP
cana-1862	291	20	a	a	DET
cana-1862	291	21	key	key	ADJ
cana-1862	291	22	element	element	NOUN
cana-1862	291	23	in	in	ADP
cana-1862	291	24	real	real	ADJ
cana-1862	291	25	-	-	PUNCT
cana-1862	291	26	time	time	NOUN
cana-1862	291	27	monitoring	monitoring	NOUN
cana-1862	291	28	systems	system	NOUN
cana-1862	291	29	,	,	PUNCT
cana-1862	291	30	especially	especially	ADV
cana-1862	291	31	for	for	ADP
cana-1862	291	32	highly	highly	ADV
cana-1862	291	33	dynamic	dynamic	ADJ
cana-1862	291	34	environments	environment	NOUN
cana-1862	291	35	with	with	ADP
cana-1862	291	36	rapidly	rapidly	ADV
cana-1862	291	37	changing	change	VERB
cana-1862	291	38	attack	attack	NOUN
cana-1862	291	39	patterns	pattern	NOUN
cana-1862	291	40	(	(	PUNCT
cana-1862	291	41	albeit	albeit	SCONJ
cana-1862	291	42	at	at	ADP
cana-1862	291	43	the	the	DET
cana-1862	291	44	price	price	NOUN
cana-1862	291	45	of	of	ADP
cana-1862	291	46	slower	slow	ADJ
cana-1862	291	47	response	response	NOUN
cana-1862	291	48	times	time	NOUN
cana-1862	291	49	:	:	PUNCT
cana-1862	291	50	iocs	ioc	NOUN
cana-1862	291	51	typically	typically	ADV
cana-1862	291	52	take	take	VERB
cana-1862	291	53	10–20	10–20	NUM
cana-1862	291	54	ms	ms	NOUN
cana-1862	291	55	per	per	ADP
cana-1862	291	56	instance	instance	NOUN
cana-1862	291	57	to	to	PART
cana-1862	291	58	predict	predict	VERB
cana-1862	291	59	)	)	PUNCT
cana-1862	291	60	.	.	PUNCT
cana-1862	292	1	model	model	PROPN
cana-1862	292	2	dataset	dataset	PROPN
cana-1862	292	3	precision	precision	PROPN
cana-1862	292	4	recall	recall	NOUN
cana-1862	292	5	f1score	f1score	NOUN
cana-1862	292	6	detection	detection	NOUN
cana-1862	292	7	time	time	NOUN
cana-1862	292	8	(	(	PUNCT
cana-1862	292	9	ms	ms	NOUN
cana-1862	292	10	/	/	SYM
cana-1862	292	11	instance	instance	NOUN
cana-1862	292	12	)	)	PUNCT
cana-1862	292	13	false	false	ADJ
cana-1862	292	14	positive	positive	ADJ
cana-1862	292	15	rate	rate	NOUN
cana-1862	292	16	(	(	PUNCT
cana-1862	292	17	%	%	INTJ
cana-1862	292	18	)	)	PUNCT
cana-1862	292	19	auto	auto	NOUN
cana-1862	292	20	-	-	PUNCT
cana-1862	292	21	encoder	encoder	NOUN
cana-1862	292	22	cicids	cicid	NOUN
cana-1862	292	23	2017	2017	NUM
cana-1862	292	24	90.5	90.5	NUM
cana-1862	292	25	%	%	NOUN
cana-1862	292	26	92.8	92.8	NUM
cana-1862	292	27	%	%	NOUN
cana-1862	292	28	91.6	91.6	NUM
cana-1862	292	29	%	%	NOUN
cana-1862	292	30	12	12	NUM
cana-1862	292	31	3.1	3.1	NUM
cana-1862	292	32	%	%	NOUN
cana-1862	292	33	unswnb15	unswnb15	NOUN
cana-1862	292	34	89.8	89.8	NUM
cana-1862	292	35	%	%	NOUN
cana-1862	292	36	91.5	91.5	NUM
cana-1862	292	37	%	%	NOUN
cana-1862	292	38	90.6	90.6	NUM
cana-1862	292	39	%	%	NOUN
cana-1862	292	40	15	15	NUM
cana-1862	292	41	3.5	3.5	NUM
cana-1862	292	42	%	%	NOUN
cana-1862	292	43	custom	custom	NOUN
cana-1862	292	44	live	live	VERB
cana-1862	292	45	dataset	dataset	VERB
cana-1862	292	46	92.2	92.2	NUM
cana-1862	292	47	%	%	NOUN
cana-1862	292	48	94.0	94.0	NUM
cana-1862	292	49	%	%	NOUN
cana-1862	292	50	93.1	93.1	NUM
cana-1862	292	51	%	%	NOUN
cana-1862	292	52	18	18	NUM
cana-1862	292	53	2.8	2.8	NUM
cana-1862	292	54	%	%	NOUN
cana-1862	292	55	variational	variational	ADJ
cana-1862	292	56	auto	auto	NOUN
cana-1862	292	57	-	-	PUNCT
cana-1862	292	58	encoder	encoder	NOUN
cana-1862	292	59	cicids	cicid	NOUN
cana-1862	292	60	2017	2017	NUM
cana-1862	292	61	91.7	91.7	NUM
cana-1862	292	62	%	%	NOUN
cana-1862	292	63	93.3	93.3	NUM
cana-1862	292	64	%	%	NOUN
cana-1862	292	65	92.5	92.5	NUM
cana-1862	292	66	%	%	NOUN
cana-1862	292	67	14	14	NUM
cana-1862	292	68	2.9	2.9	NUM
cana-1862	292	69	%	%	NOUN
cana-1862	292	70	unswnb15	unswnb15	NOUN
cana-1862	292	71	90.8	90.8	NUM
cana-1862	292	72	%	%	NOUN
cana-1862	292	73	92.2	92.2	NUM
cana-1862	292	74	%	%	NOUN
cana-1862	292	75	91.5	91.5	NUM
cana-1862	292	76	%	%	NOUN
cana-1862	292	77	16	16	NUM
cana-1862	292	78	3.2	3.2	NUM
cana-1862	292	79	%	%	NOUN
cana-1862	292	80	custom	custom	NOUN
cana-1862	292	81	live	live	VERB
cana-1862	292	82	dataset	dataset	VERB
cana-1862	292	83	93.0	93.0	NUM
cana-1862	292	84	%	%	NOUN
cana-1862	292	85	95.0	95.0	NUM
cana-1862	292	86	%	%	NOUN
cana-1862	292	87	94.0	94.0	NUM
cana-1862	292	88	%	%	NOUN
cana-1862	292	89	20	20	NUM
cana-1862	292	90	2.5	2.5	NUM
cana-1862	292	91	%	%	NOUN
cana-1862	292	92	isolation	isolation	NOUN
cana-1862	292	93	forest	forest	NOUN
cana-1862	292	94	cicids	cicid	NOUN
cana-1862	292	95	2017	2017	NUM
cana-1862	292	96	88.4	88.4	NUM
cana-1862	292	97	%	%	NOUN
cana-1862	292	98	90.0	90.0	NUM
cana-1862	292	99	%	%	NOUN
cana-1862	292	100	89.2	89.2	NUM
cana-1862	292	101	%	%	NOUN
cana-1862	292	102	10	10	NUM
cana-1862	292	103	4.0	4.0	NUM
cana-1862	292	104	%	%	NOUN
cana-1862	292	105	unswnb15	unswnb15	NOUN
cana-1862	292	106	87.2	87.2	NUM
cana-1862	292	107	%	%	NOUN
cana-1862	292	108	88.9	88.9	NUM
cana-1862	292	109	%	%	NOUN
cana-1862	292	110	88.0	88.0	NUM
cana-1862	292	111	%	%	NOUN
cana-1862	292	112	12	12	NUM
cana-1862	292	113	4.3	4.3	NUM
cana-1862	292	114	%	%	NOUN
cana-1862	292	115	custom	custom	NOUN
cana-1862	292	116	live	live	VERB
cana-1862	292	117	dataset	dataset	VERB
cana-1862	292	118	89.1	89.1	NUM
cana-1862	292	119	%	%	NOUN
cana-1862	292	120	90.7	90.7	NUM
cana-1862	292	121	%	%	NOUN
cana-1862	292	122	89.9	89.9	NUM
cana-1862	292	123	%	%	NOUN
cana-1862	292	124	15	15	NUM
cana-1862	292	125	3.7	3.7	NUM
cana-1862	292	126	%	%	NOUN
cana-1862	292	127	here	here	ADV
cana-1862	292	128	we	we	PRON
cana-1862	292	129	have	have	VERB
cana-1862	292	130	the	the	DET
cana-1862	292	131	performance	performance	NOUN
cana-1862	292	132	of	of	ADP
cana-1862	292	133	unsupervised	unsupervised	ADJ
cana-1862	292	134	models	model	NOUN
cana-1862	292	135	(	(	PUNCT
cana-1862	292	136	auto	auto	NOUN
cana-1862	292	137	-	-	PUNCT
cana-1862	292	138	encoder	encoder	NOUN
cana-1862	292	139	,	,	PUNCT
cana-1862	292	140	variational	variational	ADJ
cana-1862	292	141	auto	auto	NOUN
cana-1862	292	142	-	-	PUNCT
cana-1862	292	143	encoder	encoder	NOUN
cana-1862	292	144	and	and	CCONJ
cana-1862	292	145	isolation	isolation	NOUN
cana-1862	292	146	forest	forest	NOUN
cana-1862	292	147	)	)	PUNCT
cana-1862	292	148	on	on	ADP
cana-1862	292	149	different	different	ADJ
cana-1862	292	150	datasets	dataset	NOUN
cana-1862	292	151	with	with	ADP
cana-1862	292	152	their	their	PRON
cana-1862	292	153	precision	precision	NOUN
cana-1862	292	154	,	,	PUNCT
cana-1862	292	155	recall	recall	NOUN
cana-1862	292	156	,	,	PUNCT
cana-1862	292	157	f1	f1	NOUN
cana-1862	292	158	-	-	PUNCT
cana-1862	292	159	score	score	NOUN
cana-1862	292	160	,	,	PUNCT
cana-1862	292	161	detection	detection	NOUN
cana-1862	292	162	time	time	NOUN
cana-1862	292	163	and	and	CCONJ
cana-1862	292	164	false	false	ADJ
cana-1862	292	165	examples	example	NOUN
cana-1862	292	166	communications	communication	NOUN
cana-1862	292	167	on	on	ADP
cana-1862	292	168	applied	apply	VERB
cana-1862	292	169	nonlinear	nonlinear	ADJ
cana-1862	292	170	analysis	analysis	NOUN
cana-1862	292	171	issn	issn	NOUN
cana-1862	292	172	:	:	PUNCT
cana-1862	292	173	1074	1074	NUM
cana-1862	292	174	-	-	PUNCT
cana-1862	292	175	133x	133x	NUM
cana-1862	292	176	vol	vol	NOUN
cana-1862	292	177	32	32	NUM
cana-1862	292	178	no	no	NOUN
cana-1862	292	179	.	.	NOUN
cana-1862	292	180	2	2	NUM
cana-1862	292	181	(	(	PUNCT
cana-1862	292	182	2025	2025	NUM
cana-1862	292	183	)	)	PUNCT
cana-1862	292	184	710	710	NUM
cana-1862	292	185	https://internationalpubls.com	https://internationalpubls.com	X
cana-1862	292	186	isolation	isolation	NOUN
cana-1862	292	187	forests	forest	NOUN
cana-1862	292	188	and	and	CCONJ
cana-1862	292	189	gaussian	gaussian	ADJ
cana-1862	292	190	mixture	mixture	NOUN
cana-1862	292	191	models	model	NOUN
cana-1862	292	192	(	(	PUNCT
cana-1862	292	193	gmm	gmm	NOUN
cana-1862	292	194	)	)	PUNCT
cana-1862	292	195	achieved	achieve	VERB
cana-1862	292	196	similar	similar	ADJ
cana-1862	292	197	sensitivity	sensitivity	NOUN
cana-1862	292	198	but	but	CCONJ
cana-1862	292	199	with	with	ADP
cana-1862	292	200	a	a	DET
cana-1862	292	201	slightly	slightly	ADV
cana-1862	292	202	lower	low	ADJ
cana-1862	292	203	accuracy	accuracy	NOUN
cana-1862	292	204	level	level	NOUN
cana-1862	292	205	compared	compare	VERB
cana-1862	292	206	to	to	ADP
cana-1862	292	207	auto	auto	NOUN
cana-1862	292	208	-	-	PUNCT
cana-1862	292	209	encoders	encoder	NOUN
cana-1862	292	210	.	.	PUNCT
cana-1862	293	1	gmms	gmms	NOUN
cana-1862	293	2	,	,	PUNCT
cana-1862	293	3	measuring	measure	VERB
cana-1862	293	4	network	network	NOUN
cana-1862	293	5	traffic	traffic	NOUN
cana-1862	293	6	as	as	ADP
cana-1862	293	7	the	the	DET
cana-1862	293	8	superposition	superposition	NOUN
cana-1862	293	9	of	of	ADP
cana-1862	293	10	gaussian	gaussian	ADJ
cana-1862	293	11	distribution	distribution	NOUN
cana-1862	293	12	functions	function	NOUN
cana-1862	293	13	,	,	PUNCT
cana-1862	293	14	were	be	AUX
cana-1862	293	15	evaluated	evaluate	VERB
cana-1862	293	16	with	with	ADP
cana-1862	293	17	an	an	DET
cana-1862	293	18	f1	f1	ADJ
cana-1862	293	19	-	-	PUNCT
cana-1862	293	20	score	score	NOUN
cana-1862	293	21	ranging	ranging	NOUN
cana-1862	293	22	between	between	ADP
cana-1862	293	23	85	85	NUM
cana-1862	293	24	and	and	CCONJ
cana-1862	293	25	90	90	NUM
cana-1862	293	26	%	%	NOUN
cana-1862	293	27	on	on	ADP
cana-1862	293	28	different	different	ADJ
cana-1862	293	29	datasets	dataset	NOUN
cana-1862	293	30	,	,	PUNCT
cana-1862	293	31	revealing	reveal	VERB
cana-1862	293	32	their	their	PRON
cana-1862	293	33	effectiveness	effectiveness	NOUN
cana-1862	293	34	for	for	ADP
cana-1862	293	35	modelling	model	VERB
cana-1862	293	36	network	network	NOUN
cana-1862	293	37	behaviour	behaviour	NOUN
cana-1862	293	38	that	that	PRON
cana-1862	293	39	could	could	AUX
cana-1862	293	40	signal	signal	VERB
cana-1862	293	41	security	security	NOUN
cana-1862	293	42	threats	threat	NOUN
cana-1862	293	43	.	.	PUNCT
cana-1862	294	1	yet	yet	ADV
cana-1862	294	2	their	their	PRON
cana-1862	294	3	false	false	ADJ
cana-1862	294	4	positive	positive	ADJ
cana-1862	294	5	rates	rate	NOUN
cana-1862	294	6	(	(	PUNCT
cana-1862	294	7	3.7	3.7	NUM
cana-1862	294	8	and	and	CCONJ
cana-1862	294	9	4.3	4.3	NUM
cana-1862	294	10	%	%	NOUN
cana-1862	294	11	)	)	PUNCT
cana-1862	294	12	are	be	AUX
cana-1862	294	13	high	high	ADJ
cana-1862	294	14	which	which	PRON
cana-1862	294	15	could	could	AUX
cana-1862	294	16	be	be	AUX
cana-1862	294	17	improved	improve	VERB
cana-1862	294	18	by	by	ADP
cana-1862	294	19	further	further	ADJ
cana-1862	294	20	tuning	tuning	NOUN
cana-1862	294	21	for	for	ADP
cana-1862	294	22	deployment	deployment	NOUN
cana-1862	294	23	in	in	ADP
cana-1862	294	24	changing	change	VERB
cana-1862	294	25	networked	networked	ADJ
cana-1862	294	26	settings	setting	NOUN
cana-1862	294	27	.	.	PUNCT
cana-1862	295	1	●	●	NUM
cana-1862	295	2	models	model	NOUN
cana-1862	295	3	of	of	ADP
cana-1862	295	4	probabilistic	probabilistic	ADJ
cana-1862	295	5	and	and	CCONJ
cana-1862	295	6	reinforcement	reinforcement	NOUN
cana-1862	295	7	learning	learn	VERB
cana-1862	295	8	the	the	DET
cana-1862	295	9	model	model	NOUN
cana-1862	295	10	based	base	VERB
cana-1862	295	11	method	method	NOUN
cana-1862	295	12	employed	employ	VERB
cana-1862	295	13	bayesian	bayesian	NOUN
cana-1862	295	14	networks	network	NOUN
cana-1862	295	15	which	which	PRON
cana-1862	295	16	allowed	allow	VERB
cana-1862	295	17	a	a	DET
cana-1862	295	18	more	more	ADV
cana-1862	295	19	flexible	flexible	ADJ
cana-1862	295	20	approach	approach	NOUN
cana-1862	295	21	to	to	ADP
cana-1862	295	22	vulnerability	vulnerability	NOUN
cana-1862	295	23	detection	detection	NOUN
cana-1862	295	24	in	in	ADP
cana-1862	295	25	the	the	DET
cana-1862	295	26	sense	sense	NOUN
cana-1862	295	27	that	that	PRON
cana-1862	295	28	was	be	AUX
cana-1862	295	29	able	able	ADJ
cana-1862	295	30	to	to	PART
cana-1862	295	31	capture	capture	VERB
cana-1862	295	32	how	how	SCONJ
cana-1862	295	33	different	different	ADJ
cana-1862	295	34	network	network	NOUN
cana-1862	295	35	features	feature	NOUN
cana-1862	295	36	are	be	AUX
cana-1862	295	37	relate	relate	VERB
cana-1862	295	38	probabilistically	probabilistically	ADV
cana-1862	295	39	.	.	PUNCT
cana-1862	296	1	under	under	ADP
cana-1862	296	2	this	this	DET
cana-1862	296	3	framework	framework	NOUN
cana-1862	296	4	,	,	PUNCT
cana-1862	296	5	the	the	DET
cana-1862	296	6	inference	inference	NOUN
cana-1862	296	7	accuracy	accuracy	NOUN
cana-1862	296	8	was	be	AUX
cana-1862	296	9	88.5%~91	88.5%~91	NUM
cana-1862	296	10	%	%	NOUN
cana-1862	296	11	over	over	ADP
cana-1862	296	12	all	all	DET
cana-1862	296	13	samples	sample	NOUN
cana-1862	296	14	in	in	ADP
cana-1862	296	15	grapefruit	grapefruit	NOUN
cana-1862	296	16	-	-	PUNCT
cana-1862	296	17	dataset	dataset	NOUN
cana-1862	296	18	,	,	PUNCT
cana-1862	296	19	orange	orange	NOUN
cana-1862	296	20	-	-	PUNCT
cana-1862	296	21	dataset	dataset	NOUN
cana-1862	296	22	and	and	CCONJ
cana-1862	296	23	lemon	lemon	NOUN
cana-1862	296	24	-	-	PUNCT
cana-1862	296	25	dataset	dataset	NOUN
cana-1862	296	26	,	,	PUNCT
cana-1862	296	27	which	which	PRON
cana-1862	296	28	demonstrates	demonstrate	VERB
cana-1862	296	29	the	the	DET
cana-1862	296	30	capacity	capacity	NOUN
cana-1862	296	31	of	of	ADP
cana-1862	296	32	dealing	deal	VERB
cana-1862	296	33	with	with	ADP
cana-1862	296	34	uncertain	uncertain	ADJ
cana-1862	296	35	and	and	CCONJ
cana-1862	296	36	incomplete	incomplete	ADJ
cana-1862	296	37	information	information	NOUN
cana-1862	296	38	of	of	ADP
cana-1862	296	39	each	each	DET
cana-1862	296	40	sample	sample	NOUN
cana-1862	296	41	within	within	ADP
cana-1862	296	42	network	network	NOUN
cana-1862	296	43	traffic	traffic	NOUN
cana-1862	296	44	data	datum	NOUN
cana-1862	296	45	.	.	PUNCT
cana-1862	297	1	convergence	convergence	NOUN
cana-1862	297	2	to	to	ADP
cana-1862	297	3	the	the	DET
cana-1862	297	4	reassessment	reassessment	NOUN
cana-1862	297	5	rates	rate	NOUN
cana-1862	297	6	of	of	ADP
cana-1862	297	7	94–97	94–97	NUM
cana-1862	297	8	%	%	NOUN
cana-1862	297	9	for	for	ADP
cana-1862	297	10	network	network	NOUN
cana-1862	297	11	configurations	configuration	NOUN
cana-1862	297	12	that	that	PRON
cana-1862	297	13	change	change	VERB
cana-1862	297	14	quickly	quickly	ADV
cana-1862	297	15	(	(	PUNCT
cana-1862	297	16	dynamic	dynamic	ADJ
cana-1862	297	17	behaviour	behaviour	NOUN
cana-1862	297	18	)	)	PUNCT
cana-1862	297	19	,	,	PUNCT
cana-1862	297	20	which	which	PRON
cana-1862	297	21	is	be	AUX
cana-1862	297	22	a	a	DET
cana-1862	297	23	very	very	ADV
cana-1862	297	24	useful	useful	ADJ
cana-1862	297	25	property	property	NOUN
cana-1862	297	26	in	in	ADP
cana-1862	297	27	face	face	NOUN
cana-1862	297	28	of	of	ADP
cana-1862	297	29	rapidly	rapidly	ADV
cana-1862	297	30	changing	change	VERB
cana-1862	297	31	security	security	NOUN
cana-1862	297	32	threats	threat	NOUN
cana-1862	297	33	,	,	PUNCT
cana-1862	297	34	were	be	AUX
cana-1862	297	35	emphasised	emphasise	VERB
cana-1862	297	36	.	.	PUNCT
cana-1862	298	1	yet	yet	CCONJ
cana-1862	298	2	the	the	DET
cana-1862	298	3	training	training	NOUN
cana-1862	298	4	times	time	NOUN
cana-1862	298	5	were	be	AUX
cana-1862	298	6	fairly	fairly	ADV
cana-1862	298	7	long	long	ADJ
cana-1862	298	8	(	(	PUNCT
cana-1862	298	9	200	200	NUM
cana-1862	298	10	-	-	SYM
cana-1862	298	11	300	300	NUM
cana-1862	298	12	seconds	second	NOUN
cana-1862	298	13	)	)	PUNCT
cana-1862	298	14	to	to	PART
cana-1862	298	15	show	show	VERB
cana-1862	298	16	that	that	SCONJ
cana-1862	298	17	there	there	PRON
cana-1862	298	18	was	be	VERB
cana-1862	298	19	a	a	DET
cana-1862	298	20	trade	trade	NOUN
cana-1862	298	21	-	-	PUNCT
cana-1862	298	22	off	off	NOUN
cana-1862	298	23	between	between	ADP
cana-1862	298	24	computational	computational	ADJ
cana-1862	298	25	complexity	complexity	NOUN
cana-1862	298	26	and	and	CCONJ
cana-1862	298	27	real	real	ADJ
cana-1862	298	28	-	-	PUNCT
cana-1862	298	29	time	time	NOUN
cana-1862	298	30	ability	ability	NOUN
cana-1862	298	31	.	.	PUNCT
cana-1862	299	1	dataset	dataset	ADJ
cana-1862	299	2	variables	variable	NOUN
cana-1862	299	3	(	(	PUNCT
cana-1862	299	4	nodes	node	NOUN
cana-1862	299	5	)	)	PUNCT
cana-1862	299	6	avg	avg	PROPN
cana-1862	299	7	.	.	PUNCT
cana-1862	300	1	conditional	conditional	ADJ
cana-1862	300	2	dependencies	dependency	NOUN
cana-1862	300	3	training	training	NOUN
cana-1862	300	4	time	time	NOUN
cana-1862	300	5	(	(	PUNCT
cana-1862	300	6	s	s	NOUN
cana-1862	300	7	)	)	PUNCT
cana-1862	300	8	inference	inference	NOUN
cana-1862	300	9	accuracy	accuracy	NOUN
cana-1862	300	10	dynamic	dynamic	ADJ
cana-1862	300	11	reassessment	reassessment	NOUN
cana-1862	300	12	(	(	PUNCT
cana-1862	300	13	%	%	NOUN
cana-1862	300	14	)	)	PUNCT
cana-1862	300	15	cicids	cicid	NOUN
cana-1862	300	16	2017	2017	NUM
cana-1862	300	17	25	25	NUM
cana-1862	300	18	4	4	NUM
cana-1862	300	19	200	200	NUM
cana-1862	300	20	89.2	89.2	NUM
cana-1862	300	21	%	%	NOUN
cana-1862	300	22	96	96	NUM
cana-1862	300	23	%	%	NOUN
cana-1862	300	24	unswnb15	unswnb15	NOUN
cana-1862	300	25	30	30	NUM
cana-1862	300	26	3	3	NUM
cana-1862	300	27	250	250	NUM
cana-1862	300	28	88.7	88.7	NUM
cana-1862	300	29	%	%	NOUN
cana-1862	300	30	94	94	NUM
cana-1862	300	31	%	%	NOUN
cana-1862	300	32	custom	custom	NOUN
cana-1862	300	33	live	live	VERB
cana-1862	300	34	dataset	dataset	VERB
cana-1862	300	35	35	35	NUM
cana-1862	300	36	5	5	NUM
cana-1862	300	37	300	300	NUM
cana-1862	300	38	91.0	91.0	NUM
cana-1862	300	39	%	%	NOUN
cana-1862	300	40	97	97	NUM
cana-1862	300	41	%	%	NOUN
cana-1862	300	42	kdd	kdd	PROPN
cana-1862	300	43	cup	cup	PROPN
cana-1862	300	44	99	99	NUM
cana-1862	300	45	28	28	NUM
cana-1862	300	46	4	4	NUM
cana-1862	300	47	220	220	NUM
cana-1862	300	48	88.5	88.5	NUM
cana-1862	300	49	%	%	NOUN
cana-1862	300	50	95	95	NUM
cana-1862	300	51	%	%	NOUN
cana-1862	300	52	table	table	NOUN
cana-1862	300	53	gives	give	VERB
cana-1862	300	54	the	the	DET
cana-1862	300	55	information	information	NOUN
cana-1862	300	56	related	relate	VERB
cana-1862	300	57	with	with	ADP
cana-1862	300	58	the	the	DET
cana-1862	300	59	bayesian	bayesian	NOUN
cana-1862	300	60	network	network	NOUN
cana-1862	300	61	model	model	NOUN
cana-1862	300	62	of	of	ADP
cana-1862	300	63	different	different	ADJ
cana-1862	300	64	datasets	dataset	NOUN
cana-1862	300	65	like	like	ADP
cana-1862	300	66	no	no	PRON
cana-1862	300	67	of	of	ADP
cana-1862	300	68	variable	variable	NOUN
cana-1862	300	69	used	use	VERB
cana-1862	300	70	,	,	PUNCT
cana-1862	300	71	average	average	ADJ
cana-1862	300	72	conditional	conditional	ADJ
cana-1862	300	73	dependencies	dependency	NOUN
cana-1862	300	74	,	,	PUNCT
cana-1862	300	75	training	training	NOUN
cana-1862	300	76	time	time	NOUN
cana-1862	300	77	,	,	PUNCT
cana-1862	300	78	inference	inference	NOUN
cana-1862	300	79	accuracy	accuracy	NOUN
cana-1862	300	80	and	and	CCONJ
cana-1862	300	81	dynamic	dynamic	ADJ
cana-1862	300	82	probability	probability	NOUN
cana-1862	300	83	reassessment	reassessment	NOUN
cana-1862	300	84	capability	capability	NOUN
cana-1862	300	85	.	.	PUNCT
cana-1862	301	1	more	more	ADV
cana-1862	301	2	importantly	importantly	ADV
cana-1862	301	3	,	,	PUNCT
cana-1862	301	4	reinforcement	reinforcement	NOUN
cana-1862	301	5	learning	learning	NOUN
cana-1862	301	6	models	model	NOUN
cana-1862	301	7	,	,	PUNCT
cana-1862	301	8	namely	namely	ADV
cana-1862	301	9	q	q	NOUN
cana-1862	301	10	-	-	PUNCT
cana-1862	301	11	learning	learning	NOUN
cana-1862	301	12	was	be	AUX
cana-1862	301	13	found	find	VERB
cana-1862	301	14	to	to	PART
cana-1862	301	15	be	be	AUX
cana-1862	301	16	efficient	efficient	ADJ
cana-1862	301	17	in	in	ADP
cana-1862	301	18	providing	provide	VERB
cana-1862	301	19	dynamic	dynamic	ADJ
cana-1862	301	20	security	security	NOUN
cana-1862	301	21	monitoring	monitoring	NOUN
cana-1862	301	22	with	with	ADP
cana-1862	301	23	a	a	DET
cana-1862	301	24	detection	detection	NOUN
cana-1862	301	25	accuracy	accuracy	NOUN
cana-1862	301	26	upto	upto	VERB
cana-1862	301	27	93	93	NUM
cana-1862	301	28	%	%	NOUN
cana-1862	301	29	on	on	ADP
cana-1862	301	30	average	average	ADJ
cana-1862	301	31	.	.	PUNCT
cana-1862	302	1	high	high	ADJ
cana-1862	302	2	rates	rate	NOUN
cana-1862	302	3	of	of	ADP
cana-1862	302	4	real	real	ADJ
cana-1862	302	5	-	-	PUNCT
cana-1862	302	6	time	time	NOUN
cana-1862	302	7	adaptation	adaptation	NOUN
cana-1862	302	8	(	(	PUNCT
cana-1862	302	9	92–95	92–95	NUM
cana-1862	302	10	%	%	NOUN
cana-1862	302	11	)	)	PUNCT
cana-1862	302	12	demonstrate	demonstrate	VERB
cana-1862	302	13	the	the	DET
cana-1862	302	14	inherent	inherent	ADJ
cana-1862	302	15	capability	capability	NOUN
cana-1862	302	16	of	of	ADP
cana-1862	302	17	the	the	DET
cana-1862	302	18	agent	agent	NOUN
cana-1862	302	19	to	to	PART
cana-1862	302	20	learn	learn	VERB
cana-1862	302	21	optimal	optimal	ADJ
cana-1862	302	22	actions	action	NOUN
cana-1862	302	23	under	under	ADP
cana-1862	302	24	differing	differ	VERB
cana-1862	302	25	network	network	NOUN
cana-1862	302	26	states	state	NOUN
cana-1862	302	27	and	and	CCONJ
cana-1862	302	28	its	its	PRON
cana-1862	302	29	ability	ability	NOUN
cana-1862	302	30	to	to	PART
cana-1862	302	31	update	update	VERB
cana-1862	302	32	its	its	PRON
cana-1862	302	33	policy	policy	NOUN
cana-1862	302	34	according	accord	VERB
cana-1862	302	35	to	to	ADP
cana-1862	302	36	action	action	NOUN
cana-1862	302	37	outcomes	outcome	NOUN
cana-1862	302	38	are	be	AUX
cana-1862	302	39	verified	verify	VERB
cana-1862	302	40	.	.	PUNCT
cana-1862	303	1	on	on	ADP
cana-1862	303	2	the	the	DET
cana-1862	303	3	convergence	convergence	NOUN
cana-1862	303	4	times	time	NOUN
cana-1862	303	5	(	(	PUNCT
cana-1862	303	6	300	300	NUM
cana-1862	303	7	–	–	SYM
cana-1862	303	8	400	400	NUM
cana-1862	303	9	episodes	episode	NOUN
cana-1862	303	10	)	)	PUNCT
cana-1862	303	11	,	,	PUNCT
cana-1862	303	12	this	this	PRON
cana-1862	303	13	seems	seem	VERB
cana-1862	303	14	reasonable	reasonable	ADJ
cana-1862	303	15	for	for	SCONJ
cana-1862	303	16	real	real	ADJ
cana-1862	303	17	-	-	PUNCT
cana-1862	303	18	time	time	NOUN
cana-1862	303	19	defence	defence	NOUN
cana-1862	303	20	mechanisms	mechanism	NOUN
cana-1862	303	21	provided	provide	VERB
cana-1862	303	22	one	one	NUM
cana-1862	303	23	has	have	VERB
cana-1862	303	24	enough	enough	ADJ
cana-1862	303	25	initial	initial	ADJ
cana-1862	303	26	computational	computational	ADJ
cana-1862	303	27	resources	resource	NOUN
cana-1862	303	28	to	to	PART
cana-1862	303	29	bootstrap	bootstrap	VERB
cana-1862	303	30	.	.	PUNCT
cana-1862	304	1	communications	communication	NOUN
cana-1862	304	2	on	on	ADP
cana-1862	304	3	applied	apply	VERB
cana-1862	304	4	nonlinear	nonlinear	ADJ
cana-1862	304	5	analysis	analysis	NOUN
cana-1862	304	6	issn	issn	NOUN
cana-1862	304	7	:	:	PUNCT
cana-1862	304	8	1074	1074	NUM
cana-1862	304	9	-	-	PUNCT
cana-1862	304	10	133x	133x	NUM
cana-1862	304	11	vol	vol	NOUN
cana-1862	304	12	32	32	NUM
cana-1862	304	13	no	no	NOUN
cana-1862	304	14	.	.	NOUN
cana-1862	304	15	2	2	NUM
cana-1862	304	16	(	(	PUNCT
cana-1862	304	17	2025	2025	NUM
cana-1862	304	18	)	)	PUNCT
cana-1862	304	19	711	711	NUM
cana-1862	304	20	https://internationalpubls.com	https://internationalpubls.com	X
cana-1862	304	21	●	●	NUM
cana-1862	304	22	hybrid	hybrid	NOUN
cana-1862	304	23	models	model	NOUN
cana-1862	304	24	finally	finally	ADV
cana-1862	304	25	,	,	PUNCT
cana-1862	304	26	hybrid	hybrid	NOUN
cana-1862	304	27	which	which	PRON
cana-1862	304	28	merged	merge	VERB
cana-1862	304	29	auto	auto	NOUN
cana-1862	304	30	-	-	PUNCT
cana-1862	304	31	encoder	encoder	NOUN
cana-1862	304	32	and	and	CCONJ
cana-1862	304	33	xgboost	xgboost	ADV
cana-1862	304	34	into	into	ADP
cana-1862	304	35	a	a	DET
cana-1862	304	36	single	single	ADJ
cana-1862	304	37	model	model	NOUN
cana-1862	304	38	showed	show	VERB
cana-1862	304	39	the	the	DET
cana-1862	304	40	best	good	ADJ
cana-1862	304	41	performance	performance	NOUN
cana-1862	304	42	for	for	ADP
cana-1862	304	43	all	all	DET
cana-1862	304	44	cases	case	NOUN
cana-1862	304	45	with	with	ADP
cana-1862	304	46	an	an	DET
cana-1862	304	47	overall	overall	ADJ
cana-1862	304	48	accuracy	accuracy	NOUN
cana-1862	304	49	rate	rate	NOUN
cana-1862	304	50	of	of	ADP
cana-1862	304	51	at	at	ADV
cana-1862	304	52	most	most	ADV
cana-1862	304	53	98.2	98.2	NUM
cana-1862	304	54	on	on	ADP
cana-1862	304	55	custom	custom	NOUN
cana-1862	304	56	live	live	VERB
cana-1862	304	57	dataset	dataset	NOUN
cana-1862	304	58	while	while	SCONJ
cana-1862	304	59	keeping	keep	VERB
cana-1862	304	60	a	a	DET
cana-1862	304	61	low	low	ADJ
cana-1862	304	62	false	false	ADJ
cana-1862	304	63	-	-	PUNCT
cana-1862	304	64	positive	positive	ADJ
cana-1862	304	65	rate	rate	NOUN
cana-1862	304	66	(	(	PUNCT
cana-1862	304	67	1.2–1.8	1.2–1.8	NUM
cana-1862	304	68	%	%	NOUN
cana-1862	304	69	)	)	PUNCT
cana-1862	304	70	.	.	PUNCT
cana-1862	305	1	while	while	SCONJ
cana-1862	305	2	the	the	DET
cana-1862	305	3	model	model	NOUN
cana-1862	305	4	minimize	minimize	VERB
cana-1862	305	5	false	false	ADJ
cana-1862	305	6	alarm	alarm	NOUN
cana-1862	305	7	and	and	CCONJ
cana-1862	305	8	detected	detect	VERB
cana-1862	305	9	all	all	PRON
cana-1862	305	10	of	of	ADP
cana-1862	305	11	these	these	PRON
cana-1862	305	12	,	,	PUNCT
cana-1862	305	13	which	which	PRON
cana-1862	305	14	tried	try	VERB
cana-1862	305	15	to	to	PART
cana-1862	305	16	stay	stay	VERB
cana-1862	305	17	completely	completely	ADV
cana-1862	305	18	undetected	undetected	ADJ
cana-1862	305	19	it	it	PRON
cana-1862	305	20	is	be	AUX
cana-1862	305	21	worth	worth	ADJ
cana-1862	305	22	to	to	PART
cana-1862	305	23	mention	mention	VERB
cana-1862	305	24	that	that	SCONJ
cana-1862	305	25	53	53	NUM
cana-1862	305	26	%	%	NOUN
cana-1862	305	27	of	of	ADP
cana-1862	305	28	which	which	PRON
cana-1862	305	29	still	still	ADV
cana-1862	305	30	were	be	AUX
cana-1862	305	31	flagged	flag	VERB
cana-1862	305	32	by	by	ADP
cana-1862	305	33	autoencoder	autoencoder	NOUN
cana-1862	305	34	.	.	PUNCT
cana-1862	306	1	the	the	DET
cana-1862	306	2	combined	combined	ADJ
cana-1862	306	3	resolution	resolution	NOUN
cana-1862	306	4	of	of	ADP
cana-1862	306	5	this	this	DET
cana-1862	306	6	hybrid	hybrid	ADJ
cana-1862	306	7	method	method	NOUN
cana-1862	306	8	significantly	significantly	ADV
cana-1862	306	9	speeds	speed	VERB
cana-1862	306	10	up	up	ADP
cana-1862	306	11	the	the	DET
cana-1862	306	12	detection	detection	NOUN
cana-1862	306	13	and	and	CCONJ
cana-1862	306	14	brings	bring	VERB
cana-1862	306	15	the	the	DET
cana-1862	306	16	average	average	ADJ
cana-1862	306	17	inference	inference	NOUN
cana-1862	306	18	time	time	NOUN
cana-1862	306	19	to	to	ADP
cana-1862	306	20	around	around	ADV
cana-1862	306	21	10	10	NUM
cana-1862	306	22	-	-	SYM
cana-1862	306	23	15	15	NUM
cana-1862	306	24	milliseconds	millisecond	NOUN
cana-1862	306	25	per	per	ADP
cana-1862	306	26	instance	instance	NOUN
cana-1862	306	27	,	,	PUNCT
cana-1862	306	28	which	which	PRON
cana-1862	306	29	is	be	AUX
cana-1862	306	30	ideal	ideal	ADJ
cana-1862	306	31	for	for	ADP
cana-1862	306	32	real	real	ADJ
cana-1862	306	33	-	-	PUNCT
cana-1862	306	34	time	time	NOUN
cana-1862	306	35	applications	application	NOUN
cana-1862	306	36	.	.	PUNCT
cana-1862	307	1	we	we	PRON
cana-1862	307	2	demonstrate	demonstrate	VERB
cana-1862	307	3	the	the	DET
cana-1862	307	4	performance	performance	NOUN
cana-1862	307	5	of	of	ADP
cana-1862	307	6	the	the	DET
cana-1862	307	7	hybrid	hybrid	ADJ
cana-1862	307	8	model	model	NOUN
cana-1862	307	9	on	on	ADP
cana-1862	307	10	different	different	ADJ
cana-1862	307	11	datasets	dataset	NOUN
cana-1862	307	12	and	and	CCONJ
cana-1862	307	13	report	report	VERB
cana-1862	307	14	several	several	ADJ
cana-1862	307	15	metrics	metric	NOUN
cana-1862	307	16	including	include	VERB
cana-1862	307	17	accuracy	accuracy	NOUN
cana-1862	307	18	,	,	PUNCT
cana-1862	307	19	precision	precision	NOUN
cana-1862	307	20	,	,	PUNCT
cana-1862	307	21	recall	recall	NOUN
cana-1862	307	22	,	,	PUNCT
cana-1862	307	23	f1	f1	NOUN
cana-1862	307	24	-	-	PUNCT
cana-1862	307	25	score	score	NOUN
cana-1862	307	26	,	,	PUNCT
cana-1862	307	27	false	false	ADJ
cana-1862	307	28	positive	positive	ADJ
cana-1862	307	29	rate	rate	NOUN
cana-1862	307	30	(	(	PUNCT
cana-1862	307	31	fpr	fpr	NOUN
cana-1862	307	32	)	)	PUNCT
cana-1862	307	33	,	,	PUNCT
cana-1862	307	34	average	average	ADJ
cana-1862	307	35	training	training	NOUN
cana-1862	307	36	time	time	NOUN
cana-1862	307	37	(	(	PUNCT
cana-1862	307	38	over	over	ADP
cana-1862	307	39	three	three	NUM
cana-1862	307	40	runs	run	NOUN
cana-1862	307	41	)	)	PUNCT
cana-1862	307	42	as	as	ADV
cana-1862	307	43	well	well	ADV
cana-1862	307	44	as	as	ADP
cana-1862	307	45	detection	detection	NOUN
cana-1862	307	46	time	time	NOUN
cana-1862	307	47	per	per	ADP
cana-1862	307	48	instance	instance	NOUN
cana-1862	307	49	.	.	PUNCT
cana-1862	308	1	dataset	dataset	NOUN
cana-1862	308	2	accuracy	accuracy	NOUN
cana-1862	308	3	precision	precision	NOUN
cana-1862	308	4	recall	recall	VERB
cana-1862	308	5	f1score	f1score	NOUN
cana-1862	308	6	false	false	ADJ
cana-1862	308	7	positive	positive	ADJ
cana-1862	308	8	rate	rate	NOUN
cana-1862	308	9	(	(	PUNCT
cana-1862	308	10	%	%	INTJ
cana-1862	308	11	)	)	PUNCT
cana-1862	308	12	training	training	NOUN
cana-1862	308	13	time	time	NOUN
cana-1862	308	14	(	(	PUNCT
cana-1862	308	15	s	s	NOUN
cana-1862	308	16	)	)	PUNCT
cana-1862	308	17	detection	detection	NOUN
cana-1862	308	18	time	time	NOUN
cana-1862	308	19	(	(	PUNCT
cana-1862	308	20	ms	ms	NOUN
cana-1862	308	21	/	/	SYM
cana-1862	308	22	instance	instance	NOUN
cana-1862	308	23	)	)	PUNCT
cana-1862	308	24	cicids	cicid	NOUN
cana-1862	308	25	2017	2017	NUM
cana-1862	308	26	97.5	97.5	NUM
cana-1862	308	27	%	%	NOUN
cana-1862	308	28	97.0	97.0	NUM
cana-1862	308	29	%	%	NOUN
cana-1862	308	30	98.0	98.0	NUM
cana-1862	308	31	%	%	NOUN
cana-1862	308	32	97.5	97.5	NUM
cana-1862	308	33	%	%	NOUN
cana-1862	308	34	1.5	1.5	NUM
cana-1862	308	35	%	%	NOUN
cana-1862	308	36	250	250	NUM
cana-1862	308	37	12	12	NUM
cana-1862	308	38	unswnb15	unswnb15	NOUN
cana-1862	308	39	96.8	96.8	NUM
cana-1862	308	40	%	%	NOUN
cana-1862	308	41	96.2	96.2	NUM
cana-1862	308	42	%	%	NOUN
cana-1862	308	43	97.4	97.4	NUM
cana-1862	308	44	%	%	NOUN
cana-1862	308	45	96.8	96.8	NUM
cana-1862	308	46	%	%	NOUN
cana-1862	308	47	1.8	1.8	NUM
cana-1862	308	48	%	%	NOUN
cana-1862	308	49	280	280	NUM
cana-1862	308	50	15	15	NUM
cana-1862	308	51	custom	custom	NOUN
cana-1862	308	52	live	live	VERB
cana-1862	308	53	dataset	dataset	VERB
cana-1862	308	54	98.2	98.2	NUM
cana-1862	308	55	%	%	NOUN
cana-1862	308	56	97.7	97.7	NUM
cana-1862	308	57	%	%	NOUN
cana-1862	308	58	98	98	NUM
cana-1862	308	59	.	.	PUNCT
cana-1862	309	1	●	●	PUNCT
cana-1862	309	2	scalability	scalability	NOUN
cana-1862	309	3	and	and	CCONJ
cana-1862	309	4	computational	computational	ADJ
cana-1862	309	5	efficiency	efficiency	NOUN
cana-1862	309	6	.	.	PUNCT
cana-1862	310	1	these	these	DET
cana-1862	310	2	models	model	NOUN
cana-1862	310	3	have	have	AUX
cana-1862	310	4	also	also	ADV
cana-1862	310	5	been	be	AUX
cana-1862	310	6	subjected	subject	VERB
cana-1862	310	7	to	to	ADP
cana-1862	310	8	scalability	scalability	NOUN
cana-1862	310	9	tests	test	NOUN
cana-1862	310	10	over	over	ADP
cana-1862	310	11	a	a	DET
cana-1862	310	12	wider	wide	ADJ
cana-1862	310	13	range	range	NOUN
cana-1862	310	14	of	of	ADP
cana-1862	310	15	dataset	dataset	ADJ
cana-1862	310	16	sizes	size	NOUN
cana-1862	310	17	(	(	PUNCT
cana-1862	310	18	from	from	ADP
cana-1862	310	19	500,000	500,000	NUM
cana-1862	310	20	to	to	ADP
cana-1862	310	21	5,000,000	5,000,000	NUM
cana-1862	310	22	records	record	NOUN
cana-1862	310	23	)	)	PUNCT
cana-1862	310	24	,	,	PUNCT
cana-1862	310	25	showing	show	VERB
cana-1862	310	26	their	their	PRON
cana-1862	310	27	capacity	capacity	NOUN
cana-1862	310	28	of	of	ADP
cana-1862	310	29	handling	handle	VERB
cana-1862	310	30	large	large	ADJ
cana-1862	310	31	-	-	PUNCT
cana-1862	310	32	scale	scale	NOUN
cana-1862	310	33	network	network	NOUN
cana-1862	310	34	data	datum	NOUN
cana-1862	310	35	effectively	effectively	ADV
cana-1862	310	36	.	.	PUNCT
cana-1862	311	1	as	as	SCONJ
cana-1862	311	2	the	the	DET
cana-1862	311	3	testbed	testbe	VERB
cana-1862	311	4	datasets	dataset	NOUN
cana-1862	311	5	were	be	AUX
cana-1862	311	6	grown	grow	VERB
cana-1862	311	7	from	from	ADP
cana-1862	311	8	500	500	NUM
cana-1862	311	9	k	k	PROPN
cana-1862	311	10	records	record	NOUN
cana-1862	311	11	to	to	ADP
cana-1862	311	12	5	5	NUM
cana-1862	311	13	m	m	NOUN
cana-1862	311	14	records	record	NOUN
cana-1862	311	15	,	,	PUNCT
cana-1862	311	16	we	we	PRON
cana-1862	311	17	observed	observe	VERB
cana-1862	311	18	performance	performance	NOUN
cana-1862	311	19	times	time	NOUN
cana-1862	311	20	for	for	ADP
cana-1862	311	21	xgboost	xgboost	PROPN
cana-1862	311	22	(	(	PUNCT
cana-1862	311	23	which	which	PRON
cana-1862	311	24	showed	show	VERB
cana-1862	311	25	reasonable	reasonable	ADJ
cana-1862	311	26	training	training	NOUN
cana-1862	311	27	times	time	NOUN
cana-1862	311	28	,	,	PUNCT
cana-1862	311	29	scaling	scale	VERB
cana-1862	311	30	from	from	ADP
cana-1862	311	31	~70	~70	ADJ
cana-1862	311	32	seconds	second	NOUN
cana-1862	311	33	for	for	ADP
cana-1862	311	34	500	500	NUM
cana-1862	311	35	k	k	NOUN
cana-1862	311	36	and	and	CCONJ
cana-1862	311	37	~800	~800	NUM
cana-1862	311	38	seconds	second	NOUN
cana-1862	311	39	for	for	ADP
cana-1862	311	40	5	5	NUM
cana-1862	311	41	m	m	NOUN
cana-1862	311	42	)	)	PUNCT
cana-1862	311	43	while	while	SCONJ
cana-1862	311	44	auto	auto	NOUN
cana-1862	311	45	-	-	PUNCT
cana-1862	311	46	encoders	encoder	NOUN
cana-1862	311	47	’	'	PUNCT
cana-1862	311	48	performance	performance	NOUN
cana-1862	311	49	time	time	NOUN
cana-1862	311	50	increased	increase	VERB
cana-1862	311	51	more	more	ADV
cana-1862	311	52	modestly	modestly	ADV
cana-1862	311	53	in	in	ADP
cana-1862	311	54	relation	relation	NOUN
cana-1862	311	55	to	to	PART
cana-1862	311	56	dataset	dataset	NOUN
cana-1862	311	57	size	size	NOUN
cana-1862	311	58	keeping	keep	VERB
cana-1862	311	59	them	they	PRON
cana-1862	311	60	practical	practical	ADJ
cana-1862	311	61	real	real	ADJ
cana-1862	311	62	-	-	PUNCT
cana-1862	311	63	time	time	NOUN
cana-1862	311	64	detection	detection	NOUN
cana-1862	311	65	.	.	PUNCT
cana-1862	312	1	pca	pca	NOUN
cana-1862	312	2	-	-	PUNCT
cana-1862	312	3	based	base	VERB
cana-1862	312	4	dimensionality	dimensionality	NOUN
cana-1862	312	5	reduction	reduction	NOUN
cana-1862	312	6	helps	help	VERB
cana-1862	312	7	in	in	ADP
cana-1862	312	8	the	the	DET
cana-1862	312	9	faster	fast	ADJ
cana-1862	312	10	training	training	NOUN
cana-1862	312	11	of	of	ADP
cana-1862	312	12	models	model	NOUN
cana-1862	312	13	—	—	PUNCT
cana-1862	312	14	15–120	15–120	NUM
cana-1862	312	15	seconds	second	NOUN
cana-1862	312	16	depending	depend	VERB
cana-1862	312	17	on	on	ADP
cana-1862	312	18	different	different	ADJ
cana-1862	312	19	dataset	dataset	NOUN
cana-1862	312	20	sizes	size	NOUN
cana-1862	312	21	which	which	PRON
cana-1862	312	22	proves	prove	VERB
cana-1862	312	23	that	that	SCONJ
cana-1862	312	24	model	model	NOUN
cana-1862	312	25	accuracy	accuracy	NOUN
cana-1862	312	26	can	can	AUX
cana-1862	312	27	be	be	AUX
cana-1862	312	28	optimized	optimize	VERB
cana-1862	312	29	without	without	ADP
cana-1862	312	30	affecting	affect	VERB
cana-1862	312	31	its	its	PRON
cana-1862	312	32	performance	performance	NOUN
cana-1862	312	33	.	.	PUNCT
cana-1862	313	1	dataset	dataset	ADJ
cana-1862	313	2	size	size	NOUN
cana-1862	313	3	(	(	PUNCT
cana-1862	313	4	records	record	NOUN
cana-1862	313	5	)	)	PUNCT
cana-1862	313	6	xgboost	xgboost	NOUN
cana-1862	314	1	training	training	NOUN
cana-1862	314	2	time	time	NOUN
cana-1862	314	3	(	(	PUNCT
cana-1862	314	4	s	s	NOUN
cana-1862	314	5	)	)	PUNCT
cana-1862	314	6	autoencoder	autoencoder	NOUN
cana-1862	314	7	detection	detection	NOUN
cana-1862	314	8	time	time	NOUN
cana-1862	314	9	(	(	PUNCT
cana-1862	314	10	ms	ms	NOUN
cana-1862	314	11	/	/	SYM
cana-1862	314	12	instance	instance	NOUN
cana-1862	314	13	)	)	PUNCT
cana-1862	314	14	q	q	ADJ
cana-1862	314	15	-	-	PUNCT
cana-1862	314	16	learning	learn	VERB
cana-1862	314	17	convergence	convergence	NOUN
cana-1862	314	18	(	(	PUNCT
cana-1862	314	19	episodes	episode	NOUN
cana-1862	314	20	)	)	PUNCT
cana-1862	314	21	pca	pca	NOUN
cana-1862	314	22	computation	computation	NOUN
cana-1862	314	23	time	time	NOUN
cana-1862	314	24	(	(	PUNCT
cana-1862	314	25	s	s	NOUN
cana-1862	314	26	)	)	PUNCT
cana-1862	314	27	500,000	500,000	NUM
cana-1862	314	28	70	70	NUM
cana-1862	314	29	5	5	NUM
cana-1862	314	30	200	200	NUM
cana-1862	314	31	15	15	NUM
cana-1862	314	32	1,000,000	1,000,000	NUM
cana-1862	314	33	150	150	NUM
cana-1862	314	34	8	8	NUM
cana-1862	314	35	300	300	NUM
cana-1862	314	36	30	30	NUM
cana-1862	314	37	2,000,000	2,000,000	NUM
cana-1862	314	38	250	250	NUM
cana-1862	314	39	10	10	NUM
cana-1862	314	40	400	400	NUM
cana-1862	314	41	50	50	NUM
cana-1862	314	42	3,500,000	3,500,000	NUM
cana-1862	314	43	500	500	NUM
cana-1862	314	44	20	20	NUM
cana-1862	314	45	500	500	NUM
cana-1862	314	46	80	80	NUM
cana-1862	314	47	5,000,000	5,000,000	NUM
cana-1862	314	48	800	800	NUM
cana-1862	314	49	30	30	NUM
cana-1862	314	50	700	700	NUM
cana-1862	314	51	120	120	NUM
cana-1862	314	52	communications	communication	NOUN
cana-1862	314	53	on	on	ADP
cana-1862	314	54	applied	apply	VERB
cana-1862	314	55	nonlinear	nonlinear	ADJ
cana-1862	314	56	analysis	analysis	NOUN
cana-1862	314	57	issn	issn	NOUN
cana-1862	314	58	:	:	PUNCT
cana-1862	314	59	1074	1074	NUM
cana-1862	314	60	-	-	PUNCT
cana-1862	314	61	133x	133x	NUM
cana-1862	314	62	vol	vol	NOUN
cana-1862	314	63	32	32	NUM
cana-1862	314	64	no	no	NOUN
cana-1862	314	65	.	.	NOUN
cana-1862	314	66	2	2	NUM
cana-1862	314	67	(	(	PUNCT
cana-1862	314	68	2025	2025	NUM
cana-1862	314	69	)	)	PUNCT
cana-1862	314	70	712	712	NUM
cana-1862	314	71	https://internationalpubls.com	https://internationalpubls.com	X
cana-1862	314	72	for	for	ADP
cana-1862	314	73	different	different	ADJ
cana-1862	314	74	data	datum	NOUN
cana-1862	314	75	set	set	VERB
cana-1862	314	76	sizes	size	NOUN
cana-1862	314	77	,	,	PUNCT
cana-1862	314	78	this	this	DET
cana-1862	314	79	table	table	NOUN
cana-1862	314	80	shows	show	VERB
cana-1862	314	81	the	the	DET
cana-1862	314	82	computational	computational	ADJ
cana-1862	314	83	efficiency	efficiency	NOUN
cana-1862	314	84	and	and	CCONJ
cana-1862	314	85	scalability	scalability	NOUN
cana-1862	314	86	of	of	ADP
cana-1862	314	87	the	the	DET
cana-1862	314	88	models	model	NOUN
cana-1862	314	89	for	for	ADP
cana-1862	314	90	training	training	NOUN
cana-1862	314	91	time	time	NOUN
cana-1862	314	92	,	,	PUNCT
cana-1862	314	93	detection	detection	NOUN
cana-1862	314	94	time	time	NOUN
cana-1862	314	95	,	,	PUNCT
cana-1862	314	96	episodes	episode	NOUN
cana-1862	314	97	to	to	PART
cana-1862	314	98	converge	converge	VERB
cana-1862	314	99	for	for	ADP
cana-1862	314	100	q	q	NOUN
cana-1862	314	101	-	-	PUNCT
cana-1862	314	102	learning	learn	VERB
cana-1862	314	103	and	and	CCONJ
cana-1862	314	104	pca	pca	NOUN
cana-1862	314	105	computation	computation	NOUN
cana-1862	314	106	time	time	NOUN
cana-1862	314	107	.	.	PUNCT
cana-1862	315	1	the	the	DET
cana-1862	315	2	findings	finding	NOUN
cana-1862	315	3	highlight	highlight	VERB
cana-1862	315	4	that	that	SCONJ
cana-1862	315	5	each	each	DET
cana-1862	315	6	model	model	NOUN
cana-1862	315	7	has	have	VERB
cana-1862	315	8	its	its	PRON
cana-1862	315	9	own	own	ADJ
cana-1862	315	10	strengths	strength	NOUN
cana-1862	315	11	,	,	PUNCT
cana-1862	315	12	depending	depend	VERB
cana-1862	315	13	on	on	ADP
cana-1862	315	14	the	the	DET
cana-1862	315	15	type	type	NOUN
cana-1862	315	16	of	of	ADP
cana-1862	315	17	cyber	cyber	NOUN
cana-1862	315	18	security	security	NOUN
cana-1862	315	19	scenario	scenario	NOUN
cana-1862	315	20	.	.	PUNCT
cana-1862	316	1	xgboost	xgboost	X
cana-1862	316	2	,	,	PUNCT
cana-1862	316	3	as	as	ADP
cana-1862	316	4	a	a	DET
cana-1862	316	5	supervised	supervised	ADJ
cana-1862	316	6	model	model	NOUN
cana-1862	316	7	,	,	PUNCT
cana-1862	316	8	works	work	VERB
cana-1862	316	9	really	really	ADV
cana-1862	316	10	well	well	ADV
cana-1862	316	11	with	with	ADP
cana-1862	316	12	labelled	label	VERB
cana-1862	316	13	data	datum	NOUN
cana-1862	316	14	and	and	CCONJ
cana-1862	316	15	we	we	PRON
cana-1862	316	16	get	get	VERB
cana-1862	316	17	accurate	accurate	ADJ
cana-1862	316	18	results	result	NOUN
cana-1862	316	19	out	out	ADP
cana-1862	316	20	of	of	ADP
cana-1862	316	21	it	it	PRON
cana-1862	316	22	as	as	ADV
cana-1862	316	23	well	well	ADV
cana-1862	316	24	false	false	ADJ
cana-1862	316	25	positives	positive	NOUN
cana-1862	316	26	are	be	AUX
cana-1862	316	27	low	low	ADJ
cana-1862	316	28	.	.	PUNCT
cana-1862	317	1	without	without	ADP
cana-1862	317	2	labelled	label	VERB
cana-1862	317	3	data	datum	NOUN
cana-1862	317	4	,	,	PUNCT
cana-1862	317	5	unsupervised	unsupervised	ADJ
cana-1862	317	6	models	model	NOUN
cana-1862	317	7	especially	especially	ADV
cana-1862	317	8	auto	auto	NOUN
cana-1862	317	9	-	-	PUNCT
cana-1862	317	10	encoders	encoder	NOUN
cana-1862	317	11	make	make	VERB
cana-1862	317	12	it	it	PRON
cana-1862	317	13	very	very	ADV
cana-1862	317	14	useful	useful	ADJ
cana-1862	317	15	for	for	ADP
cana-1862	317	16	identifying	identify	VERB
cana-1862	317	17	anomalies	anomaly	NOUN
cana-1862	317	18	and	and	CCONJ
cana-1862	317	19	zero	zero	NUM
cana-1862	317	20	-	-	PUNCT
cana-1862	317	21	day	day	NOUN
cana-1862	317	22	threats	threat	NOUN
cana-1862	317	23	.	.	PUNCT
cana-1862	318	1	in	in	ADP
cana-1862	318	2	a	a	DET
cana-1862	318	3	connected	connected	ADJ
cana-1862	318	4	system	system	NOUN
cana-1862	318	5	,	,	PUNCT
cana-1862	318	6	models	model	NOUN
cana-1862	318	7	like	like	ADP
cana-1862	318	8	bayesian	bayesian	NOUN
cana-1862	318	9	networks	network	NOUN
cana-1862	318	10	and	and	CCONJ
cana-1862	318	11	reinforcement	reinforcement	NOUN
cana-1862	318	12	learning	learning	NOUN
cana-1862	318	13	algorithms	algorithm	NOUN
cana-1862	318	14	help	help	VERB
cana-1862	318	15	maintain	maintain	VERB
cana-1862	318	16	robust	robust	ADJ
cana-1862	318	17	,	,	PUNCT
cana-1862	318	18	adaptive	adaptive	ADJ
cana-1862	318	19	security	security	NOUN
cana-1862	318	20	frameworks	framework	NOUN
cana-1862	318	21	with	with	ADP
cana-1862	318	22	the	the	DET
cana-1862	318	23	ability	ability	NOUN
cana-1862	318	24	to	to	PART
cana-1862	318	25	grow	grow	VERB
cana-1862	318	26	along	along	ADP
cana-1862	318	27	with	with	ADP
cana-1862	318	28	changes	change	NOUN
cana-1862	318	29	within	within	ADP
cana-1862	318	30	the	the	DET
cana-1862	318	31	network	network	NOUN
cana-1862	318	32	.	.	PUNCT
cana-1862	319	1	thus	thus	ADV
cana-1862	319	2	,	,	PUNCT
cana-1862	319	3	the	the	DET
cana-1862	319	4	hybrid	hybrid	ADJ
cana-1862	319	5	model	model	NOUN
cana-1862	319	6	(	(	PUNCT
cana-1862	319	7	anomaly	anomaly	NOUN
cana-1862	319	8	detection	detection	NOUN
cana-1862	319	9	aided	aid	VERB
cana-1862	319	10	by	by	ADP
cana-1862	319	11	advanced	advanced	ADJ
cana-1862	319	12	classification	classification	NOUN
cana-1862	319	13	techniques	technique	NOUN
cana-1862	319	14	)	)	PUNCT
cana-1862	319	15	with	with	ADP
cana-1862	319	16	appropriate	appropriate	ADJ
cana-1862	319	17	improvements	improvement	NOUN
cana-1862	319	18	has	have	AUX
cana-1862	319	19	displayed	display	VERB
cana-1862	319	20	the	the	DET
cana-1862	319	21	best	good	ADJ
cana-1862	319	22	performance	performance	NOUN
cana-1862	319	23	overall	overall	ADV
cana-1862	319	24	and	and	CCONJ
cana-1862	319	25	appears	appear	VERB
cana-1862	319	26	to	to	PART
cana-1862	319	27	be	be	AUX
cana-1862	319	28	a	a	DET
cana-1862	319	29	promising	promising	ADJ
cana-1862	319	30	solution	solution	NOUN
cana-1862	319	31	for	for	ADP
cana-1862	319	32	end	end	NOUN
cana-1862	319	33	-	-	PUNCT
cana-1862	319	34	to	to	ADP
cana-1862	319	35	-	-	PUNCT
cana-1862	319	36	end	end	VERB
cana-1862	319	37	real	real	ADJ
cana-1862	319	38	-	-	PUNCT
cana-1862	319	39	time	time	NOUN
cana-1862	319	40	evaluation	evaluation	NOUN
cana-1862	319	41	of	of	ADP
cana-1862	319	42	vulnerability	vulnerability	NOUN
cana-1862	319	43	.	.	PUNCT
cana-1862	320	1	one	one	NUM
cana-1862	320	2	important	important	ADJ
cana-1862	320	3	implication	implication	NOUN
cana-1862	320	4	of	of	ADP
cana-1862	320	5	these	these	DET
cana-1862	320	6	results	result	NOUN
cana-1862	320	7	is	be	AUX
cana-1862	320	8	that	that	SCONJ
cana-1862	320	9	combining	combine	VERB
cana-1862	320	10	a	a	DET
cana-1862	320	11	wide	wide	ADJ
cana-1862	320	12	array	array	NOUN
cana-1862	320	13	for	for	ADP
cana-1862	320	14	machine	machine	NOUN
cana-1862	320	15	learning	learn	VERB
cana-1862	320	16	techniques	technique	NOUN
cana-1862	320	17	and	and	CCONJ
cana-1862	320	18	mathematical	mathematical	ADJ
cana-1862	320	19	foundations	foundation	NOUN
cana-1862	320	20	can	can	AUX
cana-1862	320	21	improve	improve	VERB
cana-1862	320	22	the	the	DET
cana-1862	320	23	robustness	robustness	NOUN
cana-1862	320	24	and	and	CCONJ
cana-1862	320	25	efficiency	efficiency	NOUN
cana-1862	320	26	of	of	ADP
cana-1862	320	27	cybersecurity	cybersecurity	NOUN
cana-1862	320	28	defence	defence	NOUN
cana-1862	320	29	layers	layer	NOUN
cana-1862	320	30	.	.	PUNCT
cana-1862	321	1	5	5	X
cana-1862	321	2	.	.	X
cana-1862	321	3	conclusion	conclusion	NOUN
cana-1862	321	4	:	:	PUNCT
cana-1862	321	5	the	the	DET
cana-1862	321	6	complexity	complexity	NOUN
cana-1862	321	7	and	and	CCONJ
cana-1862	321	8	volume	volume	NOUN
cana-1862	321	9	of	of	ADP
cana-1862	321	10	cyber	cyber	PROPN
cana-1862	321	11	threats	threat	NOUN
cana-1862	321	12	is	be	AUX
cana-1862	321	13	increasing	increase	VERB
cana-1862	321	14	,	,	PUNCT
cana-1862	321	15	therefore	therefore	ADV
cana-1862	321	16	traditional	traditional	ADJ
cana-1862	321	17	methods	method	NOUN
cana-1862	321	18	to	to	PART
cana-1862	321	19	detect	detect	VERB
cana-1862	321	20	information	information	NOUN
cana-1862	321	21	security	security	NOUN
cana-1862	321	22	vulnerabilities	vulnerability	NOUN
cana-1862	321	23	as	as	ADP
cana-1862	321	24	part	part	NOUN
cana-1862	321	25	of	of	ADP
cana-1862	321	26	vulnerability	vulnerability	NOUN
cana-1862	321	27	management	management	NOUN
cana-1862	321	28	are	be	AUX
cana-1862	321	29	not	not	PART
cana-1862	321	30	enough	enough	ADJ
cana-1862	321	31	.	.	PUNCT
cana-1862	322	1	this	this	DET
cana-1862	322	2	method	method	NOUN
cana-1862	322	3	allows	allow	VERB
cana-1862	322	4	to	to	PART
cana-1862	322	5	automatically	automatically	ADV
cana-1862	322	6	identify	identify	VERB
cana-1862	322	7	and	and	CCONJ
cana-1862	322	8	prevent	prevent	VERB
cana-1862	322	9	known	know	VERB
cana-1862	322	10	threats	threat	NOUN
cana-1862	322	11	using	use	VERB
cana-1862	322	12	signature	signature	NOUN
cana-1862	322	13	-	-	PUNCT
cana-1862	322	14	based	base	VERB
cana-1862	322	15	recognition	recognition	NOUN
cana-1862	322	16	but	but	CCONJ
cana-1862	322	17	also	also	ADV
cana-1862	322	18	it	it	PRON
cana-1862	322	19	enables	enable	VERB
cana-1862	322	20	devices	device	NOUN
cana-1862	322	21	with	with	ADP
cana-1862	322	22	intelligent	intelligent	ADJ
cana-1862	322	23	security	security	NOUN
cana-1862	322	24	capable	capable	ADJ
cana-1862	322	25	of	of	ADP
cana-1862	322	26	identifying	identify	VERB
cana-1862	322	27	zero	zero	NUM
cana-1862	322	28	-	-	PUNCT
cana-1862	322	29	day	day	NOUN
cana-1862	322	30	vulnerabilities	vulnerability	NOUN
cana-1862	322	31	.	.	PUNCT
cana-1862	323	1	the	the	DET
cana-1862	323	2	contribution	contribution	NOUN
cana-1862	323	3	made	make	VERB
cana-1862	323	4	by	by	ADP
cana-1862	323	5	this	this	DET
cana-1862	323	6	research	research	NOUN
cana-1862	323	7	was	be	AUX
cana-1862	323	8	to	to	PART
cana-1862	323	9	investigate	investigate	VERB
cana-1862	323	10	in	in	ADP
cana-1862	323	11	what	what	DET
cana-1862	323	12	way	way	NOUN
cana-1862	323	13	the	the	DET
cana-1862	323	14	latest	late	ADJ
cana-1862	323	15	machine	machine	NOUN
cana-1862	323	16	learning	learning	NOUN
cana-1862	323	17	models	model	NOUN
cana-1862	323	18	can	can	AUX
cana-1862	323	19	be	be	AUX
cana-1862	323	20	combined	combine	VERB
cana-1862	323	21	with	with	ADP
cana-1862	323	22	advanced	advanced	ADJ
cana-1862	323	23	mathematical	mathematical	ADJ
cana-1862	323	24	techniques	technique	NOUN
cana-1862	323	25	to	to	PART
cana-1862	323	26	improve	improve	VERB
cana-1862	323	27	upon	upon	SCONJ
cana-1862	323	28	the	the	DET
cana-1862	323	29	effectiveness	effectiveness	NOUN
cana-1862	323	30	of	of	ADP
cana-1862	323	31	security	security	NOUN
cana-1862	323	32	vulnerability	vulnerability	NOUN
cana-1862	323	33	detection	detection	NOUN
cana-1862	323	34	of	of	ADP
cana-1862	323	35	information	information	NOUN
cana-1862	323	36	systems	system	NOUN
cana-1862	323	37	.	.	PUNCT
cana-1862	324	1	via	via	ADP
cana-1862	324	2	this	this	DET
cana-1862	324	3	journey	journey	NOUN
cana-1862	324	4	,	,	PUNCT
cana-1862	324	5	we	we	PRON
cana-1862	324	6	brought	bring	VERB
cana-1862	324	7	together	together	ADV
cana-1862	324	8	models	model	NOUN
cana-1862	324	9	rich	rich	ADJ
cana-1862	324	10	and	and	CCONJ
cana-1862	324	11	diverse	diverse	ADJ
cana-1862	324	12	:	:	PUNCT
cana-1862	324	13	from	from	ADP
cana-1862	324	14	supervised	supervised	ADJ
cana-1862	324	15	learning	learn	VERB
cana-1862	324	16	to	to	ADP
cana-1862	324	17	unsupervised	unsupervised	ADJ
cana-1862	324	18	learning	learning	NOUN
cana-1862	324	19	;	;	PUNCT
cana-1862	324	20	as	as	ADV
cana-1862	324	21	well	well	ADV
cana-1862	324	22	as	as	ADP
cana-1862	324	23	probabilistic	probabilistic	ADJ
cana-1862	324	24	and	and	CCONJ
cana-1862	324	25	hybrid	hybrid	NOUN
cana-1862	324	26	modals	modal	NOUN
cana-1862	324	27	supported	support	VERB
cana-1862	324	28	by	by	ADP
cana-1862	324	29	mathematical	mathematical	ADJ
cana-1862	324	30	tools	tool	NOUN
cana-1862	324	31	such	such	ADJ
cana-1862	324	32	optimization	optimization	NOUN
cana-1862	324	33	,	,	PUNCT
cana-1862	324	34	probability	probability	NOUN
cana-1862	324	35	inference	inference	NOUN
cana-1862	324	36	,	,	PUNCT
cana-1862	324	37	dimensionality	dimensionality	NOUN
cana-1862	324	38	reduction	reduction	NOUN
cana-1862	324	39	etc	etc	X
cana-1862	324	40	.	.	PUNCT
cana-1862	325	1	these	these	DET
cana-1862	325	2	results	result	NOUN
cana-1862	325	3	indicate	indicate	VERB
cana-1862	325	4	the	the	DET
cana-1862	325	5	importance	importance	NOUN
cana-1862	325	6	of	of	ADP
cana-1862	325	7	mathematics	mathematic	NOUN
cana-1862	325	8	and	and	CCONJ
cana-1862	325	9	machine	machine	NOUN
cana-1862	325	10	learning	learn	VERB
cana-1862	325	11	in	in	ADP
cana-1862	325	12	constructing	construct	VERB
cana-1862	325	13	resilient	resilient	ADJ
cana-1862	325	14	,	,	PUNCT
cana-1862	325	15	intelligent	intelligent	ADJ
cana-1862	325	16	systems	system	NOUN
cana-1862	325	17	that	that	PRON
cana-1862	325	18	can	can	AUX
cana-1862	325	19	detect	detect	VERB
cana-1862	325	20	vulnerabilities	vulnerability	NOUN
cana-1862	325	21	as	as	SCONJ
cana-1862	325	22	they	they	PRON
cana-1862	325	23	happen	happen	VERB
cana-1862	325	24	.	.	PUNCT
cana-1862	326	1	●	●	PUNCT
cana-1862	326	2	improving	improve	VERB
cana-1862	326	3	detection	detection	NOUN
cana-1862	326	4	with	with	ADP
cana-1862	326	5	advanced	advanced	ADJ
cana-1862	326	6	mathematical	mathematical	ADJ
cana-1862	326	7	techniques	technique	NOUN
cana-1862	326	8	modern	modern	ADJ
cana-1862	326	9	machine	machine	NOUN
cana-1862	326	10	learning	learn	VERB
cana-1862	326	11	algorithms	algorithm	NOUN
cana-1862	326	12	use	use	VERB
cana-1862	326	13	so	so	ADV
cana-1862	326	14	much	much	ADJ
cana-1862	326	15	math	math	NOUN
cana-1862	326	16	on	on	ADP
cana-1862	326	17	so	so	ADV
cana-1862	326	18	many	many	ADJ
cana-1862	326	19	points	point	NOUN
cana-1862	326	20	of	of	ADP
cana-1862	326	21	the	the	DET
cana-1862	326	22	vulnerability	vulnerability	NOUN
cana-1862	326	23	detection	detection	NOUN
cana-1862	326	24	.	.	PUNCT
cana-1862	327	1	level	level	NOUN
cana-1862	327	2	up	up	ADP
cana-1862	327	3	the	the	DET
cana-1862	327	4	machine	machine	NOUN
cana-1862	327	5	learning	learn	VERB
cana-1862	327	6	modelsdata	modelsdata	ADJ
cana-1862	327	7	preprocessing	preprocessing	NOUN
cana-1862	327	8	to	to	AUX
cana-1862	327	9	model	model	NOUN
cana-1862	327	10	optimization	optimization	NOUN
cana-1862	327	11	,	,	PUNCT
cana-1862	327	12	mathematical	mathematical	ADJ
cana-1862	327	13	methods	method	NOUN
cana-1862	327	14	guide	guide	VERB
cana-1862	327	15	introduce	introduce	VERB
cana-1862	327	16	a	a	DET
cana-1862	327	17	new	new	ADJ
cana-1862	327	18	beginning	beginning	NOUN
cana-1862	327	19	for	for	ADP
cana-1862	327	20	overall	overall	ADJ
cana-1862	327	21	performance	performance	NOUN
cana-1862	327	22	of	of	ADP
cana-1862	327	23	machine	machine	NOUN
cana-1862	327	24	learning	learning	NOUN
cana-1862	327	25	model	model	NOUN
cana-1862	327	26	.	.	PUNCT
cana-1862	328	1	namely	namely	ADV
cana-1862	328	2	,	,	PUNCT
cana-1862	328	3	linear	linear	ADJ
cana-1862	328	4	algebra	algebra	NOUN
cana-1862	328	5	techniques	technique	NOUN
cana-1862	328	6	like	like	ADP
cana-1862	328	7	principal	principal	ADJ
cana-1862	328	8	component	component	NOUN
cana-1862	328	9	analysis	analysis	NOUN
cana-1862	328	10	(	(	PUNCT
cana-1862	328	11	pca	pca	NOUN
cana-1862	328	12	)	)	PUNCT
cana-1862	328	13	and	and	CCONJ
cana-1862	328	14	singular	singular	ADJ
cana-1862	328	15	value	value	NOUN
cana-1862	328	16	decomposition	decomposition	NOUN
cana-1862	328	17	(	(	PUNCT
cana-1862	328	18	svd)—used	svd)—use	VERB
cana-1862	328	19	for	for	ADP
cana-1862	328	20	dimensionality	dimensionality	NOUN
cana-1862	328	21	reduction	reduction	NOUN
cana-1862	328	22	of	of	ADP
cana-1862	328	23	network	network	NOUN
cana-1862	328	24	traffic	traffic	NOUN
cana-1862	328	25	data	datum	NOUN
cana-1862	328	26	reduced	reduce	VERB
cana-1862	328	27	the	the	DET
cana-1862	328	28	"	"	PUNCT
cana-1862	328	29	curse	curse	NOUN
cana-1862	328	30	of	of	ADP
cana-1862	328	31	dimensionality	dimensionality	NOUN
cana-1862	328	32	"	"	PUNCT
cana-1862	328	33	yet	yet	ADV
cana-1862	328	34	retained	retain	VERB
cana-1862	328	35	pivotal	pivotal	ADJ
cana-1862	328	36	variance	variance	NOUN
cana-1862	328	37	for	for	ADP
cana-1862	328	38	model	model	NOUN
cana-1862	328	39	learning	learning	NOUN
cana-1862	328	40	.	.	PUNCT
cana-1862	329	1	we	we	PRON
cana-1862	329	2	found	find	VERB
cana-1862	329	3	that	that	SCONJ
cana-1862	329	4	this	this	DET
cana-1862	329	5	reduction	reduction	NOUN
cana-1862	329	6	not	not	PART
cana-1862	329	7	only	only	ADV
cana-1862	329	8	sped	speed	VERB
cana-1862	329	9	up	up	ADP
cana-1862	329	10	the	the	DET
cana-1862	329	11	training	training	NOUN
cana-1862	329	12	process	process	NOUN
cana-1862	329	13	but	but	CCONJ
cana-1862	329	14	also	also	ADV
cana-1862	329	15	increased	increase	VERB
cana-1862	329	16	accuracy	accuracy	NOUN
cana-1862	329	17	and	and	CCONJ
cana-1862	329	18	generalization	generalization	NOUN
cana-1862	329	19	,	,	PUNCT
cana-1862	329	20	illustrating	illustrate	VERB
cana-1862	329	21	how	how	SCONJ
cana-1862	329	22	mathematical	mathematical	ADJ
cana-1862	329	23	approaches	approach	NOUN
cana-1862	329	24	can	can	AUX
cana-1862	329	25	be	be	AUX
cana-1862	329	26	used	use	VERB
cana-1862	329	27	to	to	PART
cana-1862	329	28	tame	tame	VERB
cana-1862	329	29	massive	massive	ADJ
cana-1862	329	30	cybersecurity	cybersecurity	NOUN
cana-1862	329	31	datasets	dataset	NOUN
cana-1862	329	32	with	with	ADP
cana-1862	329	33	high	high	ADJ
cana-1862	329	34	dimension	dimension	NOUN
cana-1862	329	35	and	and	CCONJ
cana-1862	329	36	scale	scale	NOUN
cana-1862	329	37	.	.	PUNCT
cana-1862	330	1	during	during	ADP
cana-1862	330	2	the	the	DET
cana-1862	330	3	training	training	NOUN
cana-1862	330	4	of	of	ADP
cana-1862	330	5	other	other	ADJ
cana-1862	330	6	models	model	NOUN
cana-1862	330	7	,	,	PUNCT
cana-1862	330	8	these	these	DET
cana-1862	330	9	cost	cost	NOUN
cana-1862	330	10	functions	function	NOUN
cana-1862	330	11	and	and	CCONJ
cana-1862	330	12	optimization	optimization	NOUN
cana-1862	330	13	methods	method	NOUN
cana-1862	330	14	were	be	AUX
cana-1862	330	15	minimized	minimize	VERB
cana-1862	330	16	using	use	VERB
cana-1862	330	17	gradient	gradient	ADJ
cana-1862	330	18	descent	descent	NOUN
cana-1862	330	19	(	(	PUNCT
cana-1862	330	20	and	and	CCONJ
cana-1862	330	21	its	its	PRON
cana-1862	330	22	variants	variant	NOUN
cana-1862	330	23	including	include	VERB
cana-1862	330	24	stochastic	stochastic	ADJ
cana-1862	330	25	gradient	gradient	ADJ
cana-1862	330	26	descent	descent	NOUN
cana-1862	330	27	)	)	PUNCT
cana-1862	330	28	,	,	PUNCT
cana-1862	330	29	lasso	lasso	NOUN
cana-1862	330	30	regression	regression	NOUN
cana-1862	330	31	,	,	PUNCT
cana-1862	330	32	etc	etc	X
cana-1862	330	33	.	.	X
cana-1862	330	34	,	,	PUNCT
cana-1862	330	35	to	to	PART
cana-1862	330	36	fit	fit	ADJ
cana-1862	330	37	model	model	NOUN
cana-1862	330	38	parameters	parameter	NOUN
cana-1862	330	39	.	.	PUNCT
cana-1862	331	1	these	these	DET
cana-1862	331	2	strategies	strategy	NOUN
cana-1862	331	3	allowed	allow	VERB
cana-1862	331	4	us	we	PRON
cana-1862	331	5	to	to	PART
cana-1862	331	6	ensure	ensure	VERB
cana-1862	331	7	that	that	SCONJ
cana-1862	331	8	machine	machine	NOUN
cana-1862	331	9	learning	learning	NOUN
cana-1862	331	10	models	model	NOUN
cana-1862	331	11	converged	converge	VERB
cana-1862	331	12	successfully	successfully	ADV
cana-1862	331	13	and	and	CCONJ
cana-1862	331	14	were	be	AUX
cana-1862	331	15	able	able	ADJ
cana-1862	331	16	to	to	PART
cana-1862	331	17	detect	detect	VERB
cana-1862	331	18	complex	complex	ADJ
cana-1862	331	19	security	security	NOUN
cana-1862	331	20	threats	threat	NOUN
cana-1862	331	21	at	at	ADP
cana-1862	331	22	maximum	maximum	ADJ
cana-1862	331	23	potential	potential	ADJ
cana-1862	331	24	--moreover	--moreover	PUNCT
cana-1862	331	25	,	,	PUNCT
cana-1862	331	26	probabilistic	probabilistic	ADJ
cana-1862	331	27	models	model	NOUN
cana-1862	331	28	such	such	ADJ
cana-1862	331	29	as	as	ADP
cana-1862	331	30	bayesian	bayesian	NOUN
cana-1862	331	31	networks	network	NOUN
cana-1862	331	32	used	use	VERB
cana-1862	331	33	probability	probability	NOUN
cana-1862	331	34	theory	theory	NOUN
cana-1862	331	35	to	to	PART
cana-1862	331	36	solve	solve	VERB
cana-1862	331	37	the	the	DET
cana-1862	331	38	ambiguous	ambiguous	ADJ
cana-1862	331	39	and	and	CCONJ
cana-1862	331	40	missing	miss	VERB
cana-1862	331	41	information	information	NOUN
cana-1862	331	42	to	to	PART
cana-1862	331	43	afford	afford	VERB
cana-1862	331	44	a	a	DET
cana-1862	331	45	state	state	NOUN
cana-1862	331	46	-	-	PUNCT
cana-1862	331	47	based	base	VERB
cana-1862	331	48	retelling	retelling	NOUN
cana-1862	331	49	of	of	ADP
cana-1862	331	50	the	the	DET
cana-1862	331	51	net	net	NOUN
cana-1862	331	52	by	by	ADP
cana-1862	331	53	contemplating	contemplate	VERB
cana-1862	331	54	new	new	ADJ
cana-1862	331	55	communications	communication	NOUN
cana-1862	331	56	on	on	ADP
cana-1862	331	57	applied	apply	VERB
cana-1862	331	58	nonlinear	nonlinear	ADJ
cana-1862	331	59	analysis	analysis	NOUN
cana-1862	331	60	issn	issn	NOUN
cana-1862	331	61	:	:	PUNCT
cana-1862	331	62	1074	1074	NUM
cana-1862	331	63	-	-	PUNCT
cana-1862	331	64	133x	133x	NUM
cana-1862	331	65	vol	vol	NOUN
cana-1862	331	66	32	32	NUM
cana-1862	331	67	no	no	NOUN
cana-1862	331	68	.	.	NOUN
cana-1862	331	69	2	2	NUM
cana-1862	331	70	(	(	PUNCT
cana-1862	331	71	2025	2025	NUM
cana-1862	331	72	)	)	PUNCT
cana-1862	332	1	713	713	NUM
cana-1862	332	2	https://internationalpubls.com	https://internationalpubls.com	NUM
cana-1862	332	3	evidences	evidence	NOUN
cana-1862	332	4	.	.	PUNCT
cana-1862	333	1	markov	markov	NOUN
cana-1862	333	2	chains	chain	NOUN
cana-1862	333	3	and	and	CCONJ
cana-1862	333	4	hidden	hide	VERB
cana-1862	333	5	markov	markov	NOUN
cana-1862	333	6	models	model	NOUN
cana-1862	333	7	existed	exist	VERB
cana-1862	333	8	as	as	ADP
cana-1862	333	9	a	a	DET
cana-1862	333	10	mathematical	mathematical	ADJ
cana-1862	333	11	foundation	foundation	NOUN
cana-1862	333	12	for	for	ADP
cana-1862	333	13	modelling	model	VERB
cana-1862	333	14	time	time	NOUN
cana-1862	333	15	-	-	PUNCT
cana-1862	333	16	series	series	NOUN
cana-1862	333	17	data	datum	NOUN
cana-1862	333	18	that	that	PRON
cana-1862	333	19	could	could	AUX
cana-1862	333	20	be	be	AUX
cana-1862	333	21	used	use	VERB
cana-1862	333	22	to	to	PART
cana-1862	333	23	recognize	recognize	VERB
cana-1862	333	24	vulnerabilities	vulnerability	NOUN
cana-1862	333	25	from	from	ADP
cana-1862	333	26	temporal	temporal	ADJ
cana-1862	333	27	patterns	pattern	NOUN
cana-1862	333	28	in	in	ADP
cana-1862	333	29	network	network	NOUN
cana-1862	333	30	traffic	traffic	NOUN
cana-1862	333	31	.	.	PUNCT
cana-1862	334	1	also	also	ADV
cana-1862	334	2	,	,	PUNCT
cana-1862	334	3	graph	graph	NOUN
cana-1862	334	4	theory	theory	NOUN
cana-1862	334	5	improved	improve	VERB
cana-1862	334	6	network	network	NOUN
cana-1862	334	7	security	security	NOUN
cana-1862	334	8	modelling	modelling	NOUN
cana-1862	334	9	by	by	ADP
cana-1862	334	10	casting	cast	VERB
cana-1862	334	11	(	(	PUNCT
cana-1862	334	12	encompassing	encompass	VERB
cana-1862	334	13	)	)	PUNCT
cana-1862	334	14	network	network	NOUN
cana-1862	334	15	entities	entity	NOUN
cana-1862	334	16	(	(	PUNCT
cana-1862	334	17	like	like	ADP
cana-1862	334	18	computers	computer	NOUN
cana-1862	334	19	and	and	CCONJ
cana-1862	334	20	users	user	NOUN
cana-1862	334	21	etc	etc	X
cana-1862	334	22	.	.	X
cana-1862	334	23	)	)	PUNCT
cana-1862	334	24	as	as	ADP
cana-1862	334	25	nodes	node	NOUN
cana-1862	334	26	,	,	PUNCT
cana-1862	334	27	while	while	SCONJ
cana-1862	334	28	interactions	interaction	NOUN
cana-1862	334	29	are	be	AUX
cana-1862	334	30	branded	brand	VERB
cana-1862	334	31	as	as	ADP
cana-1862	334	32	edges	edge	NOUN
cana-1862	334	33	.	.	PUNCT
cana-1862	335	1	this	this	PRON
cana-1862	335	2	enabled	enable	VERB
cana-1862	335	3	us	we	PRON
cana-1862	335	4	to	to	PART
cana-1862	335	5	use	use	VERB
cana-1862	335	6	centrality	centrality	NOUN
cana-1862	335	7	measures	measure	NOUN
cana-1862	335	8	and	and	CCONJ
cana-1862	335	9	community	community	NOUN
cana-1862	335	10	detection	detection	NOUN
cana-1862	335	11	algorithms	algorithm	NOUN
cana-1862	335	12	to	to	PART
cana-1862	335	13	extract	extract	VERB
cana-1862	335	14	the	the	DET
cana-1862	335	15	vulnerabilities	vulnerability	NOUN
cana-1862	335	16	,	,	PUNCT
cana-1862	335	17	attack	attack	NOUN
cana-1862	335	18	paths	path	NOUN
cana-1862	335	19	i.e	i.e	PRON
cana-1862	335	20	vulnerabilities	vulnerability	NOUN
cana-1862	335	21	exploited	exploit	VERB
cana-1862	335	22	in	in	ADP
cana-1862	335	23	series	series	NOUN
cana-1862	335	24	)	)	PUNCT
cana-1862	335	25	that	that	PRON
cana-1862	335	26	exist	exist	VERB
cana-1862	335	27	on	on	ADP
cana-1862	335	28	the	the	DET
cana-1862	335	29	network	network	NOUN
cana-1862	335	30	.	.	PUNCT
cana-1862	336	1	note	note	VERB
cana-1862	336	2	that	that	SCONJ
cana-1862	336	3	these	these	DET
cana-1862	336	4	math	math	NOUN
cana-1862	336	5	-	-	PUNCT
cana-1862	336	6	based	base	VERB
cana-1862	336	7	techniques	technique	NOUN
cana-1862	336	8	have	have	AUX
cana-1862	336	9	become	become	VERB
cana-1862	336	10	essential	essential	ADJ
cana-1862	336	11	to	to	ADP
cana-1862	336	12	building	build	VERB
cana-1862	336	13	the	the	DET
cana-1862	336	14	machines	machine	NOUN
cana-1862	336	15	learning	learn	VERB
cana-1862	336	16	models	model	NOUN
cana-1862	336	17	capable	capable	ADJ
cana-1862	336	18	of	of	ADP
cana-1862	336	19	spotting	spot	VERB
cana-1862	336	20	vulnerabilities	vulnerability	NOUN
cana-1862	336	21	in	in	ADP
cana-1862	336	22	real	real	ADJ
cana-1862	336	23	-	-	PUNCT
cana-1862	336	24	time	time	NOUN
cana-1862	336	25	.	.	PUNCT
cana-1862	337	1	●	●	PUNCT
cana-1862	337	2	watching	watch	VERB
cana-1862	337	3	-	-	PUNCT
cana-1862	337	4	over	over	NOUN
cana-1862	337	5	for	for	ADP
cana-1862	337	6	existing	exist	VERB
cana-1862	337	7	vulnerabilities	vulnerability	NOUN
cana-1862	337	8	using	use	VERB
cana-1862	337	9	supervised	supervised	ADJ
cana-1862	337	10	learning	learning	NOUN
cana-1862	337	11	apply	apply	VERB
cana-1862	337	12	supervised	supervised	ADJ
cana-1862	337	13	learning	learning	NOUN
cana-1862	337	14	(	(	PUNCT
cana-1862	337	15	xgboost	xgboost	ADV
cana-1862	337	16	,	,	PUNCT
cana-1862	337	17	neural	neural	ADJ
cana-1862	337	18	networks	network	NOUN
cana-1862	337	19	)	)	PUNCT
cana-1862	337	20	very	very	ADV
cana-1862	337	21	well	well	ADV
cana-1862	337	22	to	to	ADP
cana-1862	337	23	a	a	DET
cana-1862	337	24	labeled	label	VERB
cana-1862	337	25	data	datum	NOUN
cana-1862	337	26	set	set	VERB
cana-1862	337	27	it	it	PRON
cana-1862	337	28	was	be	AUX
cana-1862	337	29	the	the	DET
cana-1862	337	30	use	use	NOUN
cana-1862	337	31	of	of	ADP
cana-1862	337	32	an	an	DET
cana-1862	337	33	ensemble	ensemble	ADJ
cana-1862	337	34	learning	learning	NOUN
cana-1862	337	35	method	method	NOUN
cana-1862	337	36	based	base	VERB
cana-1862	337	37	on	on	ADP
cana-1862	337	38	decision	decision	NOUN
cana-1862	337	39	trees	tree	NOUN
cana-1862	337	40	and	and	CCONJ
cana-1862	337	41	something	something	PRON
cana-1862	337	42	else	else	ADV
cana-1862	337	43	(	(	PUNCT
cana-1862	337	44	gradient	gradient	ADJ
cana-1862	337	45	boosting	boosting	NOUN
cana-1862	337	46	)	)	PUNCT
cana-1862	337	47	that	that	PRON
cana-1862	337	48	allowed	allow	VERB
cana-1862	337	49	xgboost	xgboost	ADV
cana-1862	337	50	to	to	PART
cana-1862	337	51	handle	handle	VERB
cana-1862	337	52	learn	learn	VERB
cana-1862	337	53	from	from	ADP
cana-1862	337	54	both	both	PRON
cana-1862	337	55	categorical	categorical	ADJ
cana-1862	337	56	as	as	ADV
cana-1862	337	57	well	well	ADV
cana-1862	337	58	as	as	ADP
cana-1862	337	59	numerical	numerical	ADJ
cana-1862	337	60	data	datum	NOUN
cana-1862	337	61	types	type	NOUN
cana-1862	337	62	,	,	PUNCT
cana-1862	337	63	and	and	CCONJ
cana-1862	337	64	potentially	potentially	ADV
cana-1862	337	65	model	model	VERB
cana-1862	337	66	more	more	ADV
cana-1862	337	67	complex	complex	ADJ
cana-1862	337	68	interactions	interaction	NOUN
cana-1862	337	69	between	between	ADP
cana-1862	337	70	security	security	NOUN
cana-1862	337	71	features	feature	NOUN
cana-1862	337	72	.	.	PUNCT
cana-1862	338	1	it	it	PRON
cana-1862	338	2	demonstrated	demonstrate	VERB
cana-1862	338	3	high	high	ADJ
cana-1862	338	4	accuracy	accuracy	NOUN
cana-1862	338	5	rates	rate	NOUN
cana-1862	338	6	on	on	ADP
cana-1862	338	7	diverse	diverse	ADJ
cana-1862	338	8	datasets	dataset	NOUN
cana-1862	338	9	in	in	ADP
cana-1862	338	10	all	all	DET
cana-1862	338	11	network	network	NOUN
cana-1862	338	12	environments	environment	NOUN
cana-1862	338	13	illustrating	illustrate	VERB
cana-1862	338	14	its	its	PRON
cana-1862	338	15	consistency	consistency	NOUN
cana-1862	338	16	.	.	PUNCT
cana-1862	339	1	built	build	VERB
cana-1862	339	2	-	-	PUNCT
cana-1862	339	3	in	in	ADP
cana-1862	339	4	feature	feature	NOUN
cana-1862	339	5	importance	importance	NOUN
cana-1862	339	6	analysis	analysis	NOUN
cana-1862	339	7	for	for	ADP
cana-1862	339	8	the	the	DET
cana-1862	339	9	model	model	NOUN
cana-1862	339	10	could	could	AUX
cana-1862	339	11	identify	identify	VERB
cana-1862	339	12	the	the	DET
cana-1862	339	13	most	most	ADV
cana-1862	339	14	important	important	ADJ
cana-1862	339	15	attributes	attribute	NOUN
cana-1862	339	16	associated	associate	VERB
cana-1862	339	17	with	with	ADP
cana-1862	339	18	security	security	NOUN
cana-1862	339	19	breaches	breach	NOUN
cana-1862	339	20	and	and	CCONJ
cana-1862	339	21	allowed	allow	VERB
cana-1862	339	22	more	more	ADV
cana-1862	339	23	focused	focused	ADJ
cana-1862	339	24	threat	threat	NOUN
cana-1862	339	25	mitigation	mitigation	NOUN
cana-1862	339	26	efforts	effort	NOUN
cana-1862	339	27	.	.	PUNCT
cana-1862	340	1	the	the	DET
cana-1862	340	2	issue	issue	NOUN
cana-1862	340	3	is	be	AUX
cana-1862	340	4	that	that	SCONJ
cana-1862	340	5	the	the	DET
cana-1862	340	6	supervised	supervised	ADJ
cana-1862	340	7	learning	learning	NOUN
cana-1862	340	8	models	model	NOUN
cana-1862	340	9	require	require	VERB
cana-1862	340	10	some	some	DET
cana-1862	340	11	sort	sort	NOUN
cana-1862	340	12	of	of	ADP
cana-1862	340	13	labelled	label	VERB
cana-1862	340	14	datasets	dataset	NOUN
cana-1862	340	15	which	which	PRON
cana-1862	340	16	are	be	AUX
cana-1862	340	17	very	very	ADV
cana-1862	340	18	rare	rare	ADJ
cana-1862	340	19	in	in	ADP
cana-1862	340	20	cyber	cyber	ADJ
cana-1862	340	21	security	security	NOUN
cana-1862	340	22	area	area	NOUN
cana-1862	340	23	because	because	SCONJ
cana-1862	340	24	it	it	PRON
cana-1862	340	25	always	always	ADV
cana-1862	340	26	changes	change	VERB
cana-1862	340	27	.	.	PUNCT
cana-1862	341	1	strong	strong	ADJ
cana-1862	341	2	classification	classification	NOUN
cana-1862	341	3	ability	ability	NOUN
cana-1862	341	4	,	,	PUNCT
cana-1862	341	5	but	but	CCONJ
cana-1862	341	6	closely	closely	ADV
cana-1862	341	7	related	relate	VERB
cana-1862	341	8	to	to	ADP
cana-1862	341	9	the	the	DET
cana-1862	341	10	quality	quality	NOUN
cana-1862	341	11	of	of	ADP
cana-1862	341	12	the	the	DET
cana-1862	341	13	training	training	NOUN
cana-1862	341	14	data	datum	NOUN
cana-1862	341	15	:	:	PUNCT
cana-1862	341	16	for	for	ADP
cana-1862	341	17	examples	example	NOUN
cana-1862	341	18	,	,	PUNCT
cana-1862	341	19	fully	fully	ADV
cana-1862	341	20	connected	connected	ADJ
cana-1862	341	21	neural	neural	ADJ
cana-1862	341	22	network	network	NOUN
cana-1862	341	23	(	(	PUNCT
cana-1862	341	24	fcnn	fcnn	PROPN
cana-1862	341	25	)	)	PUNCT
cana-1862	341	26	has	have	VERB
cana-1862	341	27	a	a	DET
cana-1862	341	28	promising	promising	ADJ
cana-1862	341	29	performance	performance	NOUN
cana-1862	341	30	using	use	VERB
cana-1862	341	31	its	its	PRON
cana-1862	341	32	abundant	abundant	ADJ
cana-1862	341	33	learnable	learnable	ADJ
cana-1862	341	34	parameters	parameter	NOUN
cana-1862	341	35	but	but	CCONJ
cana-1862	341	36	they	they	PRON
cana-1862	341	37	need	need	AUX
cana-1862	341	38	labeled	label	VERB
cana-1862	341	39	in	in	ADP
cana-1862	341	40	million	million	NUM
cana-1862	341	41	scale	scale	NOUN
cana-1862	341	42	.	.	PUNCT
cana-1862	342	1	even	even	ADV
cana-1862	342	2	by	by	ADP
cana-1862	342	3	their	their	PRON
cana-1862	342	4	very	very	ADJ
cana-1862	342	5	nature	nature	NOUN
cana-1862	342	6	,	,	PUNCT
cana-1862	342	7	these	these	PRON
cana-1862	342	8	are	be	AUX
cana-1862	342	9	weak	weak	ADJ
cana-1862	342	10	against	against	ADP
cana-1862	342	11	zero	zero	NUM
cana-1862	342	12	-	-	PUNCT
cana-1862	342	13	day	day	NOUN
cana-1862	342	14	threats	threat	NOUN
cana-1862	342	15	and	and	CCONJ
cana-1862	342	16	they	they	PRON
cana-1862	342	17	highlight	highlight	VERB
cana-1862	342	18	a	a	DET
cana-1862	342	19	key	key	ADJ
cana-1862	342	20	problem	problem	NOUN
cana-1862	342	21	in	in	ADP
cana-1862	342	22	cybersecurity	cybersecurity	NOUN
cana-1862	342	23	:	:	PUNCT
cana-1862	342	24	the	the	DET
cana-1862	342	25	requirement	requirement	NOUN
cana-1862	342	26	of	of	ADP
cana-1862	342	27	supervised	supervised	ADJ
cana-1862	342	28	prediction	prediction	NOUN
cana-1862	342	29	techniques	technique	NOUN
cana-1862	342	30	that	that	PRON
cana-1862	342	31	depend	depend	VERB
cana-1862	342	32	on	on	ADP
cana-1862	342	33	labeled	label	VERB
cana-1862	342	34	data	datum	NOUN
cana-1862	342	35	.	.	PUNCT
cana-1862	343	1	●	●	PUNCT
cana-1862	343	2	zero	zero	NUM
cana-1862	343	3	-	-	PUNCT
cana-1862	343	4	day	day	NOUN
cana-1862	343	5	vulnerability	vulnerability	NOUN
cana-1862	343	6	detection	detection	NOUN
cana-1862	343	7	with	with	ADP
cana-1862	343	8	unsupervised	unsupervised	ADJ
cana-1862	343	9	learning	learning	NOUN
cana-1862	343	10	in	in	ADP
cana-1862	343	11	order	order	NOUN
cana-1862	343	12	to	to	PART
cana-1862	343	13	address	address	VERB
cana-1862	343	14	zero	zero	NUM
cana-1862	343	15	-	-	PUNCT
cana-1862	343	16	day	day	NOUN
cana-1862	343	17	or	or	CCONJ
cana-1862	343	18	unknown	unknown	ADJ
cana-1862	343	19	vulnerabilities	vulnerability	NOUN
cana-1862	343	20	,	,	PUNCT
cana-1862	343	21	we	we	PRON
cana-1862	343	22	studied	study	VERB
cana-1862	343	23	unsupervised	unsupervised	ADJ
cana-1862	343	24	models	model	NOUN
cana-1862	343	25	to	to	PART
cana-1862	343	26	include	include	VERB
cana-1862	343	27	auto	auto	NOUN
cana-1862	343	28	-	-	PUNCT
cana-1862	343	29	encoders	encoder	NOUN
cana-1862	343	30	,	,	PUNCT
cana-1862	343	31	vaes	vaes	ADJ
cana-1862	343	32	,	,	PUNCT
cana-1862	343	33	isolation	isolation	NOUN
cana-1862	343	34	forest	forest	NOUN
cana-1862	343	35	and	and	CCONJ
cana-1862	343	36	gmm	gmm	PROPN
cana-1862	343	37	.	.	PUNCT
cana-1862	344	1	auto	auto	NOUN
cana-1862	344	2	-	-	PUNCT
cana-1862	344	3	encoders	encoder	NOUN
cana-1862	344	4	,	,	PUNCT
cana-1862	344	5	which	which	PRON
cana-1862	344	6	were	be	AUX
cana-1862	344	7	trained	train	VERB
cana-1862	344	8	to	to	PART
cana-1862	344	9	try	try	VERB
cana-1862	344	10	and	and	CCONJ
cana-1862	344	11	reconstruct	reconstruct	VERB
cana-1862	344	12	the	the	DET
cana-1862	344	13	input	input	NOUN
cana-1862	344	14	data	datum	NOUN
cana-1862	344	15	,	,	PUNCT
cana-1862	344	16	performed	perform	VERB
cana-1862	344	17	well	well	ADV
cana-1862	344	18	on	on	ADP
cana-1862	344	19	this	this	DET
cana-1862	344	20	topic	topic	NOUN
cana-1862	344	21	due	due	ADP
cana-1862	344	22	to	to	ADP
cana-1862	344	23	being	be	AUX
cana-1862	344	24	able	able	ADJ
cana-1862	344	25	pick	pick	VERB
cana-1862	344	26	up	up	ADP
cana-1862	344	27	deviations	deviation	NOUN
cana-1862	344	28	from	from	ADP
cana-1862	344	29	normal	normal	ADJ
cana-1862	344	30	network	network	NOUN
cana-1862	344	31	patterns	pattern	NOUN
cana-1862	344	32	.	.	PUNCT
cana-1862	345	1	the	the	DET
cana-1862	345	2	spike	spike	NOUN
cana-1862	345	3	in	in	ADP
cana-1862	345	4	reconstruction	reconstruction	NOUN
cana-1862	345	5	error	error	NOUN
cana-1862	345	6	signalled	signal	VERB
cana-1862	345	7	potential	potential	ADJ
cana-1862	345	8	areas	area	NOUN
cana-1862	345	9	of	of	ADP
cana-1862	345	10	attack	attack	NOUN
cana-1862	345	11	when	when	SCONJ
cana-1862	345	12	new	new	ADJ
cana-1862	345	13	and	and	CCONJ
cana-1862	345	14	malicious	malicious	ADJ
cana-1862	345	15	network	network	NOUN
cana-1862	345	16	traffic	traffic	NOUN
cana-1862	345	17	was	be	AUX
cana-1862	345	18	introduced	introduce	VERB
cana-1862	345	19	,	,	PUNCT
cana-1862	345	20	so	so	ADV
cana-1862	345	21	provided	provide	VERB
cana-1862	345	22	a	a	DET
cana-1862	345	23	way	way	NOUN
cana-1862	345	24	for	for	ADP
cana-1862	345	25	bootstrapping	bootstrappe	VERB
cana-1862	345	26	to	to	PART
cana-1862	345	27	automatically	automatically	ADV
cana-1862	345	28	detect	detect	VERB
cana-1862	345	29	new	new	ADJ
cana-1862	345	30	or	or	CCONJ
cana-1862	345	31	unseen	unseen	ADJ
cana-1862	345	32	threats	threat	NOUN
cana-1862	345	33	.	.	PUNCT
cana-1862	346	1	variational	variational	ADJ
cana-1862	346	2	auto	auto	NOUN
cana-1862	346	3	-	-	PUNCT
cana-1862	346	4	encoders	encoder	NOUN
cana-1862	346	5	which	which	PRON
cana-1862	346	6	are	be	AUX
cana-1862	346	7	the	the	DET
cana-1862	346	8	probabilistic	probabilistic	ADJ
cana-1862	346	9	extension	extension	NOUN
cana-1862	346	10	of	of	ADP
cana-1862	346	11	auto	auto	NOUN
cana-1862	346	12	-	-	PUNCT
cana-1862	346	13	encoders	encoder	NOUN
cana-1862	346	14	bring	bring	VERB
cana-1862	346	15	stochastic	stochastic	ADJ
cana-1862	346	16	input	input	NOUN
cana-1862	346	17	to	to	ADP
cana-1862	346	18	the	the	DET
cana-1862	346	19	generation	generation	NOUN
cana-1862	346	20	process	process	NOUN
cana-1862	346	21	and	and	CCONJ
cana-1862	346	22	make	make	VERB
cana-1862	346	23	it	it	PRON
cana-1862	346	24	much	much	ADV
cana-1862	346	25	more	more	ADV
cana-1862	346	26	capable	capable	ADJ
cana-1862	346	27	in	in	ADP
cana-1862	346	28	handling	handle	VERB
cana-1862	346	29	diverse	diverse	ADJ
cana-1862	346	30	data	datum	NOUN
cana-1862	346	31	.	.	PUNCT
cana-1862	347	1	both	both	DET
cana-1862	347	2	isolation	isolation	NOUN
cana-1862	347	3	forests	forest	NOUN
cana-1862	347	4	and	and	CCONJ
cana-1862	347	5	gmms	gmms	NOUN
cana-1862	347	6	modelled	model	VERB
cana-1862	347	7	the	the	DET
cana-1862	347	8	distribution	distribution	NOUN
cana-1862	347	9	of	of	ADP
cana-1862	347	10	network	network	NOUN
cana-1862	347	11	traffic	traffic	NOUN
cana-1862	347	12	data	datum	NOUN
cana-1862	347	13	,	,	PUNCT
cana-1862	347	14	providing	provide	VERB
cana-1862	347	15	an	an	DET
cana-1862	347	16	alternative	alternative	ADJ
cana-1862	347	17	view	view	NOUN
cana-1862	347	18	towards	towards	ADP
cana-1862	347	19	anomaly	anomaly	NOUN
cana-1862	347	20	detection	detection	NOUN
cana-1862	347	21	.	.	PUNCT
cana-1862	348	1	isolation	isolation	NOUN
cana-1862	348	2	forests	forest	NOUN
cana-1862	348	3	isolated	isolate	VERB
cana-1862	348	4	anomalies	anomaly	NOUN
cana-1862	348	5	by	by	ADP
cana-1862	348	6	partitioning	partition	VERB
cana-1862	348	7	the	the	DET
cana-1862	348	8	data	datum	NOUN
cana-1862	348	9	according	accord	VERB
cana-1862	348	10	to	to	ADP
cana-1862	348	11	how	how	SCONJ
cana-1862	348	12	much	much	ADJ
cana-1862	348	13	their	their	PRON
cana-1862	348	14	features	feature	NOUN
cana-1862	348	15	deviate	deviate	VERB
cana-1862	348	16	,	,	PUNCT
cana-1862	348	17	whereas	whereas	SCONJ
cana-1862	348	18	gmm	gmm	PROPN
cana-1862	348	19	captured	capture	VERB
cana-1862	348	20	network	network	NOUN
cana-1862	348	21	activity	activity	NOUN
cana-1862	348	22	distribution	distribution	NOUN
cana-1862	348	23	,	,	PUNCT
cana-1862	348	24	and	and	CCONJ
cana-1862	348	25	deviations	deviation	NOUN
cana-1862	348	26	from	from	ADP
cana-1862	348	27	normal	normal	ADJ
cana-1862	348	28	clusters	cluster	NOUN
cana-1862	348	29	were	be	AUX
cana-1862	348	30	considered	consider	VERB
cana-1862	348	31	anomalous	anomalous	ADJ
cana-1862	348	32	.	.	PUNCT
cana-1862	349	1	especially	especially	ADV
cana-1862	349	2	useful	useful	ADJ
cana-1862	349	3	in	in	ADP
cana-1862	349	4	cybersecurity	cybersecurity	NOUN
cana-1862	349	5	environments	environment	NOUN
cana-1862	349	6	with	with	ADP
cana-1862	349	7	few	few	ADJ
cana-1862	349	8	labelled	label	VERB
cana-1862	349	9	inputs	input	NOUN
cana-1862	349	10	,	,	PUNCT
cana-1862	349	11	these	these	DET
cana-1862	349	12	unsupervised	unsupervised	ADJ
cana-1862	349	13	methods	method	NOUN
cana-1862	349	14	are	be	AUX
cana-1862	349	15	not	not	PART
cana-1862	349	16	reliant	reliant	ADJ
cana-1862	349	17	on	on	ADP
cana-1862	349	18	predefined	predefine	VERB
cana-1862	349	19	categories	category	NOUN
cana-1862	349	20	by	by	ADP
cana-1862	349	21	which	which	PRON
cana-1862	349	22	to	to	PART
cana-1862	349	23	find	find	VERB
cana-1862	349	24	vulnerabilities	vulnerability	NOUN
cana-1862	349	25	.	.	PUNCT
cana-1862	350	1	the	the	DET
cana-1862	350	2	wide	wide	ADJ
cana-1862	350	3	range	range	NOUN
cana-1862	350	4	of	of	ADP
cana-1862	350	5	success	success	NOUN
cana-1862	350	6	unsupervised	unsupervised	ADJ
cana-1862	350	7	learning	learning	NOUN
cana-1862	350	8	models	model	NOUN
cana-1862	350	9	has	have	AUX
cana-1862	350	10	reinforced	reinforce	VERB
cana-1862	350	11	the	the	DET
cana-1862	350	12	notion	notion	NOUN
cana-1862	350	13	that	that	SCONJ
cana-1862	350	14	effective	effective	ADJ
cana-1862	350	15	security	security	NOUN
cana-1862	350	16	systems	system	NOUN
cana-1862	350	17	can	can	AUX
cana-1862	350	18	be	be	AUX
cana-1862	350	19	built	build	VERB
cana-1862	350	20	to	to	PART
cana-1862	350	21	detect	detect	VERB
cana-1862	350	22	both	both	PRON
cana-1862	350	23	known	known	ADJ
cana-1862	350	24	and	and	CCONJ
cana-1862	350	25	emerging	emerge	VERB
cana-1862	350	26	threats	threat	NOUN
cana-1862	350	27	without	without	ADP
cana-1862	350	28	needing	need	VERB
cana-1862	350	29	an	an	DET
cana-1862	350	30	extensive	extensive	ADJ
cana-1862	350	31	communications	communication	NOUN
cana-1862	350	32	on	on	ADP
cana-1862	350	33	applied	apply	VERB
cana-1862	350	34	nonlinear	nonlinear	ADJ
cana-1862	350	35	analysis	analysis	NOUN
cana-1862	350	36	issn	issn	NOUN
cana-1862	350	37	:	:	PUNCT
cana-1862	350	38	1074	1074	NUM
cana-1862	350	39	-	-	PUNCT
cana-1862	350	40	133x	133x	NUM
cana-1862	350	41	vol	vol	NOUN
cana-1862	350	42	32	32	NUM
cana-1862	350	43	no	no	NOUN
cana-1862	350	44	.	.	NOUN
cana-1862	350	45	2	2	NUM
cana-1862	350	46	(	(	PUNCT
cana-1862	350	47	2025	2025	NUM
cana-1862	350	48	)	)	PUNCT
cana-1862	350	49	714	714	NUM
cana-1862	350	50	https://internationalpubls.com	https://internationalpubls.com	NUM
cana-1862	350	51	labeled	label	VERB
cana-1862	350	52	dataset	dataset	NOUN
cana-1862	350	53	.	.	PUNCT
cana-1862	351	1	this	this	DET
cana-1862	351	2	agility	agility	NOUN
cana-1862	351	3	is	be	AUX
cana-1862	351	4	essential	essential	ADJ
cana-1862	351	5	in	in	ADP
cana-1862	351	6	ever	ever	ADV
cana-1862	351	7	changing	change	VERB
cana-1862	351	8	threat	threat	NOUN
cana-1862	351	9	environments	environment	NOUN
cana-1862	351	10	where	where	SCONJ
cana-1862	351	11	new	new	ADJ
cana-1862	351	12	vulnerabilities	vulnerability	NOUN
cana-1862	351	13	and	and	CCONJ
cana-1862	351	14	attack	attack	NOUN
cana-1862	351	15	vectors	vector	NOUN
cana-1862	351	16	are	be	AUX
cana-1862	351	17	discovered	discover	VERB
cana-1862	351	18	on	on	ADP
cana-1862	351	19	a	a	DET
cana-1862	351	20	regular	regular	ADJ
cana-1862	351	21	basis	basis	NOUN
cana-1862	351	22	.	.	PUNCT
cana-1862	352	1	●	●	PUNCT
cana-1862	352	2	dynamic	dynamic	ADJ
cana-1862	352	3	security	security	NOUN
cana-1862	352	4	event	event	NOUN
cana-1862	352	5	monitoring	monitor	VERB
cana-1862	352	6	with	with	ADP
cana-1862	352	7	probabilistic	probabilistic	ADJ
cana-1862	352	8	models	model	NOUN
cana-1862	352	9	such	such	DET
cana-1862	352	10	a	a	DET
cana-1862	352	11	methodology	methodology	NOUN
cana-1862	352	12	enhances	enhance	VERB
cana-1862	352	13	the	the	DET
cana-1862	352	14	performing	perform	VERB
cana-1862	352	15	accuracy	accuracy	NOUN
cana-1862	352	16	of	of	ADP
cana-1862	352	17	a	a	DET
cana-1862	352	18	method	method	NOUN
cana-1862	352	19	as	as	SCONJ
cana-1862	352	20	compared	compare	VERB
cana-1862	352	21	to	to	ADP
cana-1862	352	22	rule	rule	NOUN
cana-1862	352	23	-	-	PUNCT
cana-1862	352	24	based	base	VERB
cana-1862	352	25	techniques	technique	NOUN
cana-1862	352	26	,	,	PUNCT
cana-1862	352	27	probabilistic	probabilistic	ADJ
cana-1862	352	28	models	model	NOUN
cana-1862	352	29	like	like	ADP
cana-1862	352	30	bayesian	bayesian	NOUN
cana-1862	352	31	networks	network	NOUN
cana-1862	352	32	and	and	CCONJ
cana-1862	352	33	hidden	hide	VERB
cana-1862	352	34	markov	markov	NOUN
cana-1862	352	35	models	model	NOUN
cana-1862	352	36	(	(	PUNCT
cana-1862	352	37	hmms	hmms	NOUN
cana-1862	352	38	)	)	PUNCT
cana-1862	352	39	brought	bring	VERB
cana-1862	352	40	uncertainty	uncertainty	NOUN
cana-1862	352	41	handling	handling	NOUN
cana-1862	352	42	and	and	CCONJ
cana-1862	352	43	adaptation	adaptation	NOUN
cana-1862	352	44	in	in	ADP
cana-1862	352	45	vulnerability	vulnerability	NOUN
cana-1862	352	46	detection	detection	NOUN
cana-1862	352	47	which	which	PRON
cana-1862	352	48	is	be	AUX
cana-1862	352	49	complementing	complement	VERB
cana-1862	352	50	with	with	ADP
cana-1862	352	51	our	our	PRON
cana-1862	352	52	vagueness	vagueness	NOUN
cana-1862	352	53	in	in	ADP
cana-1862	352	54	natural	natural	ADJ
cana-1862	352	55	language	language	NOUN
cana-1862	352	56	.	.	PUNCT
cana-1862	353	1	dynamic	dynamic	ADJ
cana-1862	353	2	updates	update	NOUN
cana-1862	353	3	to	to	ADP
cana-1862	353	4	the	the	DET
cana-1862	353	5	probabilistic	probabilistic	ADJ
cana-1862	353	6	relationships	relationship	NOUN
cana-1862	353	7	between	between	ADP
cana-1862	353	8	security	security	NOUN
cana-1862	353	9	features	feature	NOUN
cana-1862	353	10	were	be	AUX
cana-1862	353	11	modelled	model	VERB
cana-1862	353	12	using	use	VERB
cana-1862	353	13	bayesian	bayesian	NOUN
cana-1862	353	14	networks	network	NOUN
cana-1862	353	15	as	as	SCONJ
cana-1862	353	16	new	new	ADJ
cana-1862	353	17	evidence	evidence	NOUN
cana-1862	353	18	became	become	VERB
cana-1862	353	19	available	available	ADJ
cana-1862	353	20	.	.	PUNCT
cana-1862	354	1	for	for	ADP
cana-1862	354	2	example	example	NOUN
cana-1862	354	3	,	,	PUNCT
cana-1862	354	4	the	the	DET
cana-1862	354	5	system	system	NOUN
cana-1862	354	6	is	be	AUX
cana-1862	354	7	able	able	ADJ
cana-1862	354	8	to	to	PART
cana-1862	354	9	re	re	VERB
cana-1862	354	10	-	-	VERB
cana-1862	354	11	evaluate	evaluate	VERB
cana-1862	354	12	how	how	SCONJ
cana-1862	354	13	likely	likely	ADJ
cana-1862	354	14	certain	certain	ADJ
cana-1862	354	15	vulnerabilities	vulnerability	NOUN
cana-1862	354	16	are	be	AUX
cana-1862	354	17	based	base	VERB
cana-1862	354	18	on	on	ADP
cana-1862	354	19	what	what	PRON
cana-1862	354	20	has	have	AUX
cana-1862	354	21	been	be	AUX
cana-1862	354	22	happening	happen	VERB
cana-1862	354	23	in	in	ADP
cana-1862	354	24	terms	term	NOUN
cana-1862	354	25	of	of	ADP
cana-1862	354	26	network	network	NOUN
cana-1862	354	27	traffic	traffic	NOUN
cana-1862	354	28	,	,	PUNCT
cana-1862	354	29	allowing	allow	VERB
cana-1862	354	30	for	for	ADP
cana-1862	354	31	an	an	DET
cana-1862	354	32	adaptive	adaptive	ADJ
cana-1862	354	33	,	,	PUNCT
cana-1862	354	34	real	real	ADJ
cana-1862	354	35	-	-	PUNCT
cana-1862	354	36	time	time	NOUN
cana-1862	354	37	reaction	reaction	NOUN
cana-1862	354	38	according	accord	VERB
cana-1862	354	39	to	to	ADP
cana-1862	354	40	current	current	ADJ
cana-1862	354	41	security	security	NOUN
cana-1862	354	42	situation	situation	NOUN
cana-1862	354	43	.	.	PUNCT
cana-1862	355	1	this	this	DET
cana-1862	355	2	probabilistic	probabilistic	ADJ
cana-1862	355	3	inference	inference	NOUN
cana-1862	355	4	feature	feature	NOUN
cana-1862	355	5	is	be	AUX
cana-1862	355	6	a	a	DET
cana-1862	355	7	requirement	requirement	NOUN
cana-1862	355	8	for	for	ADP
cana-1862	355	9	environments	environment	NOUN
cana-1862	355	10	in	in	ADP
cana-1862	355	11	which	which	PRON
cana-1862	355	12	network	network	NOUN
cana-1862	355	13	behaviours	behaviour	NOUN
cana-1862	355	14	may	may	AUX
cana-1862	355	15	change	change	VERB
cana-1862	355	16	without	without	ADP
cana-1862	355	17	explicit	explicit	ADJ
cana-1862	355	18	warning	warning	NOUN
cana-1862	355	19	and	and	CCONJ
cana-1862	355	20	the	the	DET
cana-1862	355	21	forms	form	NOUN
cana-1862	355	22	of	of	ADP
cana-1862	355	23	security	security	NOUN
cana-1862	355	24	threat	threat	NOUN
cana-1862	355	25	are	be	AUX
cana-1862	355	26	continuously	continuously	ADV
cana-1862	355	27	shifting	shift	VERB
cana-1862	355	28	.	.	PUNCT
cana-1862	356	1	hmms	hmms	PROPN
cana-1862	356	2	expanded	expand	VERB
cana-1862	356	3	this	this	DET
cana-1862	356	4	strategy	strategy	NOUN
cana-1862	356	5	through	through	ADP
cana-1862	356	6	modelling	model	VERB
cana-1862	356	7	the	the	DET
cana-1862	356	8	evolution	evolution	NOUN
cana-1862	356	9	of	of	ADP
cana-1862	356	10	network	network	NOUN
cana-1862	356	11	states	state	NOUN
cana-1862	356	12	over	over	ADP
cana-1862	356	13	time	time	NOUN
cana-1862	356	14	and	and	CCONJ
cana-1862	356	15	detecting	detect	VERB
cana-1862	356	16	temporal	temporal	ADJ
cana-1862	356	17	transitions	transition	NOUN
cana-1862	356	18	that	that	PRON
cana-1862	356	19	may	may	AUX
cana-1862	356	20	hint	hint	VERB
cana-1862	356	21	at	at	ADP
cana-1862	356	22	anomalies	anomaly	NOUN
cana-1862	356	23	caused	cause	VERB
cana-1862	356	24	by	by	ADP
cana-1862	356	25	a	a	DET
cana-1862	356	26	security	security	NOUN
cana-1862	356	27	breach	breach	NOUN
cana-1862	356	28	.	.	PUNCT
cana-1862	357	1	because	because	SCONJ
cana-1862	357	2	hmms	hmms	NOUN
cana-1862	357	3	learned	learn	VERB
cana-1862	357	4	state	state	NOUN
cana-1862	357	5	transition	transition	NOUN
cana-1862	357	6	and	and	CCONJ
cana-1862	357	7	emission	emission	NOUN
cana-1862	357	8	probabilities	probability	NOUN
cana-1862	357	9	,	,	PUNCT
cana-1862	357	10	we	we	PRON
cana-1862	357	11	could	could	AUX
cana-1862	357	12	pinpoint	pinpoint	VERB
cana-1862	357	13	sequences	sequence	NOUN
cana-1862	357	14	of	of	ADP
cana-1862	357	15	activities	activity	NOUN
cana-1862	357	16	matching	match	VERB
cana-1862	357	17	exploitation	exploitation	NOUN
cana-1862	357	18	attempts	attempt	NOUN
cana-1862	357	19	.	.	PUNCT
cana-1862	358	1	in	in	ADP
cana-1862	358	2	that	that	DET
cana-1862	358	3	instance	instance	NOUN
cana-1862	358	4	,	,	PUNCT
cana-1862	358	5	the	the	DET
cana-1862	358	6	time	time	NOUN
cana-1862	358	7	-	-	PUNCT
cana-1862	358	8	series	series	NOUN
cana-1862	358	9	analysis	analysis	NOUN
cana-1862	358	10	proved	prove	VERB
cana-1862	358	11	to	to	PART
cana-1862	358	12	be	be	AUX
cana-1862	358	13	extremely	extremely	ADV
cana-1862	358	14	powerful	powerful	ADJ
cana-1862	358	15	in	in	ADP
cana-1862	358	16	identifying	identify	VERB
cana-1862	358	17	temporal	temporal	ADJ
cana-1862	358	18	weaknesses	weakness	NOUN
cana-1862	358	19	concerning	concern	VERB
cana-1862	358	20	the	the	DET
cana-1862	358	21	attacks	attack	NOUN
cana-1862	358	22	placement	placement	NOUN
cana-1862	358	23	over	over	ADP
cana-1862	358	24	months	month	NOUN
cana-1862	358	25	of	of	ADP
cana-1862	358	26	period	period	NOUN
cana-1862	358	27	with	with	ADP
cana-1862	358	28	an	an	DET
cana-1862	358	29	eye	eye	NOUN
cana-1862	358	30	on	on	ADP
cana-1862	358	31	utilizing	utilize	VERB
cana-1862	358	32	probabilistic	probabilistic	ADJ
cana-1862	358	33	models	model	NOUN
cana-1862	358	34	as	as	ADP
cana-1862	358	35	a	a	DET
cana-1862	358	36	framework	framework	NOUN
cana-1862	358	37	for	for	ADP
cana-1862	358	38	building	build	VERB
cana-1862	358	39	proactive	proactive	ADJ
cana-1862	358	40	security	security	NOUN
cana-1862	358	41	responses	response	NOUN
cana-1862	358	42	.	.	PUNCT
cana-1862	359	1	●	●	PUNCT
cana-1862	359	2	adaptive	adaptive	ADJ
cana-1862	359	3	vulnerability	vulnerability	NOUN
cana-1862	359	4	management	management	NOUN
cana-1862	359	5	with	with	ADP
cana-1862	359	6	reinforcement	reinforcement	NOUN
cana-1862	359	7	learning	learn	VERB
cana-1862	359	8	agents	agent	NOUN
cana-1862	359	9	were	be	AUX
cana-1862	359	10	developed	develop	VERB
cana-1862	359	11	with	with	ADP
cana-1862	359	12	the	the	DET
cana-1862	359	13	help	help	NOUN
cana-1862	359	14	of	of	ADP
cana-1862	359	15	reinforcement	reinforcement	NOUN
cana-1862	359	16	learning	learning	NOUN
cana-1862	359	17	(	(	PUNCT
cana-1862	359	18	rl	rl	NOUN
cana-1862	359	19	)	)	PUNCT
cana-1862	359	20	,	,	PUNCT
cana-1862	359	21	forest	forest	NOUN
cana-1862	359	22	-	-	PUNCT
cana-1862	359	23	calling	call	VERB
cana-1862	359	24	q	q	NOUN
cana-1862	359	25	-	-	PUNCT
cana-1862	359	26	learning	learning	NOUN
cana-1862	359	27	which	which	PRON
cana-1862	359	28	could	could	AUX
cana-1862	359	29	execute	execute	VERB
cana-1862	359	30	dynamic	dynamic	ADJ
cana-1862	359	31	vulnerability	vulnerability	NOUN
cana-1862	359	32	management	management	NOUN
cana-1862	359	33	.	.	PUNCT
cana-1862	360	1	the	the	DET
cana-1862	360	2	rl	rl	PROPN
cana-1862	360	3	agent	agent	NOUN
cana-1862	360	4	interacted	interact	VERB
cana-1862	360	5	with	with	ADP
cana-1862	360	6	the	the	DET
cana-1862	360	7	environment	environment	NOUN
cana-1862	360	8	and	and	CCONJ
cana-1862	360	9	maximized	maximize	VERB
cana-1862	360	10	cumulative	cumulative	ADJ
cana-1862	360	11	rewards	reward	NOUN
cana-1862	360	12	over	over	ADP
cana-1862	360	13	time	time	NOUN
cana-1862	360	14	to	to	PART
cana-1862	360	15	learn	learn	VERB
cana-1862	360	16	optimal	optimal	ADJ
cana-1862	360	17	actions	action	NOUN
cana-1862	360	18	for	for	ADP
cana-1862	360	19	improved	improved	ADJ
cana-1862	360	20	network	network	NOUN
cana-1862	360	21	security	security	NOUN
cana-1862	360	22	.	.	PUNCT
cana-1862	361	1	the	the	DET
cana-1862	361	2	policy	policy	NOUN
cana-1862	361	3	was	be	AUX
cana-1862	361	4	adjusted	adjust	VERB
cana-1862	361	5	to	to	ADP
cana-1862	361	6	the	the	DET
cana-1862	361	7	outcomes	outcome	NOUN
cana-1862	361	8	and	and	CCONJ
cana-1862	361	9	response	response	NOUN
cana-1862	361	10	strategies	strategy	NOUN
cana-1862	361	11	were	be	AUX
cana-1862	361	12	honed	hone	VERB
cana-1862	361	13	over	over	ADP
cana-1862	361	14	time	time	NOUN
cana-1862	361	15	on	on	ADP
cana-1862	361	16	incorporating	incorporate	VERB
cana-1862	361	17	new	new	ADJ
cana-1862	361	18	threats	threat	NOUN
cana-1862	361	19	.	.	PUNCT
cana-1862	362	1	q	q	X
cana-1862	362	2	-	-	PUNCT
cana-1862	362	3	learning	learning	NOUN
cana-1862	362	4	opened	open	VERB
cana-1862	362	5	up	up	ADP
cana-1862	362	6	the	the	DET
cana-1862	362	7	realm	realm	NOUN
cana-1862	362	8	of	of	ADP
cana-1862	362	9	real	real	ADJ
cana-1862	362	10	-	-	PUNCT
cana-1862	362	11	time	time	NOUN
cana-1862	362	12	decision	decision	NOUN
cana-1862	362	13	-	-	PUNCT
cana-1862	362	14	making	making	NOUN
cana-1862	362	15	in	in	ADP
cana-1862	362	16	complex	complex	ADJ
cana-1862	362	17	,	,	PUNCT
cana-1862	362	18	dynamic	dynamic	ADJ
cana-1862	362	19	environments	environment	NOUN
cana-1862	362	20	,	,	PUNCT
cana-1862	362	21	and	and	CCONJ
cana-1862	362	22	hence	hence	ADV
cana-1862	362	23	was	be	AUX
cana-1862	362	24	a	a	DET
cana-1862	362	25	huge	huge	ADJ
cana-1862	362	26	step	step	NOUN
cana-1862	362	27	in	in	ADP
cana-1862	362	28	the	the	DET
cana-1862	362	29	direction	direction	NOUN
cana-1862	362	30	of	of	ADP
cana-1862	362	31	automated	automate	VERB
cana-1862	362	32	self	self	NOUN
cana-1862	362	33	-	-	PUNCT
cana-1862	362	34	improving	improve	VERB
cana-1862	362	35	cyber	cyber	ADJ
cana-1862	362	36	security	security	NOUN
cana-1862	362	37	systems	system	NOUN
cana-1862	362	38	.	.	PUNCT
cana-1862	363	1	reinforcement	reinforcement	NOUN
cana-1862	363	2	learning	learning	NOUN
cana-1862	363	3	helps	help	VERB
cana-1862	363	4	machine	machine	NOUN
cana-1862	363	5	learning	learning	NOUN
cana-1862	363	6	models	model	NOUN
cana-1862	363	7	act	act	VERB
cana-1862	363	8	in	in	ADP
cana-1862	363	9	addition	addition	NOUN
cana-1862	363	10	to	to	ADP
cana-1862	363	11	detecting	detect	VERB
cana-1862	363	12	against	against	ADP
cana-1862	363	13	network	network	NOUN
cana-1862	363	14	security	security	NOUN
cana-1862	363	15	.	.	PUNCT
cana-1862	364	1	we	we	PRON
cana-1862	364	2	designed	design	VERB
cana-1862	364	3	the	the	DET
cana-1862	364	4	rl	rl	PROPN
cana-1862	364	5	agent	agent	NOUN
cana-1862	364	6	to	to	PART
cana-1862	364	7	model	model	VERB
cana-1862	364	8	security	security	NOUN
cana-1862	364	9	landscape	landscape	NOUN
cana-1862	364	10	through	through	ADP
cana-1862	364	11	solving	solve	VERB
cana-1862	364	12	markov	markov	NOUN
cana-1862	364	13	decision	decision	NOUN
cana-1862	364	14	processes	process	NOUN
cana-1862	364	15	(	(	PUNCT
cana-1862	364	16	mdps	mdps	NOUN
cana-1862	364	17	)	)	PUNCT
cana-1862	364	18	and	and	CCONJ
cana-1862	364	19	dynamic	dynamic	ADJ
cana-1862	364	20	programming	programming	NOUN
cana-1862	364	21	based	base	VERB
cana-1862	364	22	policy	policy	NOUN
cana-1862	364	23	optimization	optimization	NOUN
cana-1862	364	24	problems	problem	NOUN
cana-1862	364	25	,	,	PUNCT
cana-1862	364	26	so	so	SCONJ
cana-1862	364	27	that	that	SCONJ
cana-1862	364	28	it	it	PRON
cana-1862	364	29	can	can	AUX
cana-1862	364	30	sense	sense	VERB
cana-1862	364	31	different	different	ADJ
cana-1862	364	32	types	type	NOUN
cana-1862	364	33	of	of	ADP
cana-1862	364	34	security	security	NOUN
cana-1862	364	35	threats	threat	NOUN
cana-1862	364	36	and	and	CCONJ
cana-1862	364	37	guide	guide	VERB
cana-1862	364	38	its	its	PRON
cana-1862	364	39	intention	intention	NOUN
cana-1862	364	40	towards	towards	ADP
cana-1862	364	41	mitigating	mitigate	VERB
cana-1862	364	42	the	the	DET
cana-1862	364	43	risk	risk	NOUN
cana-1862	364	44	associated	associate	VERB
cana-1862	364	45	attacks	attack	NOUN
cana-1862	364	46	,	,	PUNCT
cana-1862	364	47	when	when	SCONJ
cana-1862	364	48	it	it	PRON
cana-1862	364	49	learns	learn	VERB
cana-1862	364	50	with	with	ADP
cana-1862	364	51	simulated	simulated	ADJ
cana-1862	364	52	world	world	NOUN
cana-1862	364	53	.	.	PUNCT
cana-1862	365	1	this	this	PRON
cana-1862	365	2	is	be	AUX
cana-1862	365	3	a	a	DET
cana-1862	365	4	huge	huge	ADJ
cana-1862	365	5	benefit	benefit	NOUN
cana-1862	365	6	when	when	SCONJ
cana-1862	365	7	dealing	deal	VERB
cana-1862	365	8	with	with	ADP
cana-1862	365	9	security	security	NOUN
cana-1862	365	10	in	in	ADP
cana-1862	365	11	the	the	DET
cana-1862	365	12	largescale	largescale	NOUN
cana-1862	365	13	,	,	PUNCT
cana-1862	365	14	distributed	distribute	VERB
cana-1862	365	15	network	network	NOUN
cana-1862	365	16	environment	environment	NOUN
cana-1862	365	17	where	where	SCONJ
cana-1862	365	18	tight	tight	ADJ
cana-1862	365	19	monitoring	monitoring	NOUN
cana-1862	365	20	and	and	CCONJ
cana-1862	365	21	quick	quick	ADJ
cana-1862	365	22	response	response	NOUN
cana-1862	365	23	are	be	AUX
cana-1862	365	24	necessary	necessary	ADJ
cana-1862	365	25	to	to	PART
cana-1862	365	26	keep	keep	VERB
cana-1862	365	27	solid	solid	ADJ
cana-1862	365	28	security	security	NOUN
cana-1862	365	29	protocols	protocol	NOUN
cana-1862	365	30	intact	intact	ADJ
cana-1862	365	31	.	.	PUNCT
cana-1862	366	1	●	●	NUM
cana-1862	366	2	improved	improve	VERB
cana-1862	366	3	detection	detection	NOUN
cana-1862	366	4	accuracy	accuracy	NOUN
cana-1862	366	5	with	with	ADP
cana-1862	366	6	hybrid	hybrid	NOUN
cana-1862	366	7	models	model	NOUN
cana-1862	366	8	the	the	DET
cana-1862	366	9	combination	combination	NOUN
cana-1862	366	10	of	of	ADP
cana-1862	366	11	several	several	ADJ
cana-1862	366	12	machine	machine	NOUN
cana-1862	366	13	learning	learning	NOUN
cana-1862	366	14	models	model	NOUN
cana-1862	366	15	within	within	ADP
cana-1862	366	16	a	a	DET
cana-1862	366	17	hybrid	hybrid	ADJ
cana-1862	366	18	framework	framework	NOUN
cana-1862	366	19	outperformed	outperform	VERB
cana-1862	366	20	the	the	DET
cana-1862	366	21	rest	rest	NOUN
cana-1862	366	22	,	,	PUNCT
cana-1862	366	23	in	in	SCONJ
cana-1862	366	24	that	that	SCONJ
cana-1862	366	25	it	it	PRON
cana-1862	366	26	achieved	achieve	VERB
cana-1862	366	27	higher	high	ADJ
cana-1862	366	28	accuracy	accuracy	NOUN
cana-1862	366	29	,	,	PUNCT
cana-1862	366	30	precision	precision	NOUN
cana-1862	366	31	and	and	CCONJ
cana-1862	366	32	real	real	ADJ
cana-1862	366	33	time	time	NOUN
cana-1862	366	34	detection	detection	NOUN
cana-1862	366	35	.	.	PUNCT
cana-1862	367	1	for	for	ADP
cana-1862	367	2	example	example	NOUN
cana-1862	367	3	,	,	PUNCT
cana-1862	367	4	by	by	ADP
cana-1862	367	5	using	use	VERB
cana-1862	367	6	an	an	DET
cana-1862	367	7	autoencoder	autoencoder	NOUN
cana-1862	367	8	for	for	ADP
cana-1862	367	9	anomaly	anomaly	NOUN
cana-1862	367	10	detection	detection	NOUN
cana-1862	367	11	and	and	CCONJ
cana-1862	367	12	then	then	ADV
cana-1862	367	13	a	a	DET
cana-1862	367	14	semi	semi	ADV
cana-1862	367	15	-	-	ADJ
cana-1862	367	16	supervised	supervised	ADJ
cana-1862	368	1	xgboost	xgboost	DET
cana-1862	368	2	classifier	classifier	NOUN
cana-1862	368	3	that	that	PRON
cana-1862	368	4	takes	take	VERB
cana-1862	368	5	from	from	ADP
cana-1862	368	6	the	the	DET
cana-1862	368	7	autoencoder	autoencoder	NOUN
cana-1862	368	8	the	the	DET
cana-1862	368	9	detected	detect	VERB
cana-1862	368	10	anomalies	anomaly	NOUN
cana-1862	368	11	as	as	ADP
cana-1862	368	12	input	input	NOUN
cana-1862	368	13	features	feature	NOUN
cana-1862	368	14	—	—	PUNCT
cana-1862	368	15	reconstruction	reconstruction	NOUN
cana-1862	368	16	errors	error	NOUN
cana-1862	368	17	(	(	PUNCT
cana-1862	368	18	unsupervised	unsupervised	ADJ
cana-1862	368	19	)	)	PUNCT
cana-1862	368	20	,	,	PUNCT
cana-1862	368	21	routes	route	NOUN
cana-1862	368	22	can	can	AUX
cana-1862	368	23	be	be	AUX
cana-1862	368	24	chosen	choose	VERB
cana-1862	368	25	which	which	PRON
cana-1862	368	26	better	well	ADJ
cana-1862	368	27	leverage	leverage	NOUN
cana-1862	368	28	supervised	supervise	VERB
cana-1862	368	29	learning	learn	VERB
cana-1862	368	30	in	in	ADP
cana-1862	368	31	threat	threat	NOUN
cana-1862	368	32	prediction	prediction	NOUN
cana-1862	368	33	.	.	PUNCT
cana-1862	369	1	this	this	DET
cana-1862	369	2	hybrid	hybrid	ADJ
cana-1862	369	3	approach	approach	NOUN
cana-1862	369	4	communications	communication	NOUN
cana-1862	369	5	on	on	ADP
cana-1862	369	6	applied	apply	VERB
cana-1862	369	7	nonlinear	nonlinear	ADJ
cana-1862	369	8	analysis	analysis	NOUN
cana-1862	369	9	issn	issn	NOUN
cana-1862	369	10	:	:	PUNCT
cana-1862	369	11	1074	1074	NUM
cana-1862	369	12	-	-	PUNCT
cana-1862	369	13	133x	133x	NUM
cana-1862	369	14	vol	vol	NOUN
cana-1862	369	15	32	32	NUM
cana-1862	369	16	no	no	NOUN
cana-1862	369	17	.	.	NOUN
cana-1862	369	18	2	2	NUM
cana-1862	369	19	(	(	PUNCT
cana-1862	369	20	2025	2025	NUM
cana-1862	369	21	)	)	PUNCT
cana-1862	370	1	715	715	NUM
cana-1862	370	2	https://internationalpubls.com	https://internationalpubls.com	NUM
cana-1862	370	3	achieved	achieve	VERB
cana-1862	370	4	high	high	ADJ
cana-1862	370	5	performance	performance	NOUN
cana-1862	370	6	accuracy	accuracy	NOUN
cana-1862	370	7	,	,	PUNCT
cana-1862	370	8	low	low	ADJ
cana-1862	370	9	false	false	ADJ
cana-1862	370	10	positive	positive	ADJ
cana-1862	370	11	rates	rate	NOUN
cana-1862	370	12	over	over	ADP
cana-1862	370	13	several	several	ADJ
cana-1862	370	14	datasets	dataset	NOUN
cana-1862	370	15	(	(	PUNCT
cana-1862	370	16	cicids	cicid	NOUN
cana-1862	370	17	2017	2017	NUM
cana-1862	370	18	standard	standard	ADJ
cana-1862	370	19	benchmark	benchmark	NOUN
cana-1862	370	20	,	,	PUNCT
cana-1862	370	21	unsw	unsw	NOUN
cana-1862	370	22	-	-	PUNCT
cana-1862	370	23	nb15	nb15	PROPN
cana-1862	370	24	standard	standard	ADJ
cana-1862	370	25	benchmark	benchmark	NOUN
cana-1862	370	26	and	and	CCONJ
cana-1862	370	27	custom	custom	NOUN
cana-1862	370	28	live	live	ADJ
cana-1862	370	29	network	network	NOUN
cana-1862	370	30	)	)	PUNCT
cana-1862	370	31	.	.	PUNCT
cana-1862	371	1	in	in	ADP
cana-1862	371	2	reality	reality	NOUN
cana-1862	371	3	,	,	PUNCT
cana-1862	371	4	the	the	DET
cana-1862	371	5	success	success	NOUN
cana-1862	371	6	of	of	ADP
cana-1862	371	7	hybrid	hybrid	NOUN
cana-1862	371	8	models	model	NOUN
cana-1862	371	9	advocates	advocate	VERB
cana-1862	371	10	for	for	ADP
cana-1862	371	11	the	the	DET
cana-1862	371	12	necessity	necessity	NOUN
cana-1862	371	13	of	of	ADP
cana-1862	371	14	a	a	DET
cana-1862	371	15	more	more	ADV
cana-1862	371	16	layered	layered	ADJ
cana-1862	371	17	approach	approach	NOUN
cana-1862	371	18	to	to	ADP
cana-1862	371	19	security	security	NOUN
cana-1862	371	20	.	.	PUNCT
cana-1862	372	1	this	this	DET
cana-1862	372	2	system	system	NOUN
cana-1862	372	3	integrated	integrate	VERB
cana-1862	372	4	multiple	multiple	ADJ
cana-1862	372	5	machine	machine	NOUN
cana-1862	372	6	learning	learning	NOUN
cana-1862	372	7	methods	method	NOUN
cana-1862	372	8	to	to	PART
cana-1862	372	9	provide	provide	VERB
cana-1862	372	10	a	a	DET
cana-1862	372	11	broad	broad	ADJ
cana-1862	372	12	variety	variety	NOUN
cana-1862	372	13	of	of	ADP
cana-1862	372	14	threat	threat	NOUN
cana-1862	372	15	detection	detection	NOUN
cana-1862	372	16	,	,	PUNCT
cana-1862	372	17	which	which	PRON
cana-1862	372	18	included	include	VERB
cana-1862	372	19	known	know	VERB
cana-1862	372	20	vulnerabilities	vulnerability	NOUN
cana-1862	372	21	as	as	ADV
cana-1862	372	22	well	well	ADV
cana-1862	372	23	as	as	ADP
cana-1862	372	24	zero	zero	NUM
cana-1862	372	25	-	-	PUNCT
cana-1862	372	26	day	day	NOUN
cana-1862	372	27	exploits	exploit	NOUN
cana-1862	372	28	and	and	CCONJ
cana-1862	372	29	everything	everything	PRON
cana-1862	372	30	in	in	ADP
cana-1862	372	31	between	between	ADP
cana-1862	372	32	.	.	PUNCT
cana-1862	373	1	the	the	DET
cana-1862	373	2	mathematical	mathematical	ADJ
cana-1862	373	3	methodologies	methodology	NOUN
cana-1862	373	4	of	of	ADP
cana-1862	373	5	the	the	DET
cana-1862	373	6	pca	pca	NOUN
cana-1862	373	7	used	use	VERB
cana-1862	373	8	for	for	ADP
cana-1862	373	9	dimensionality	dimensionality	NOUN
cana-1862	373	10	reduction	reduction	NOUN
cana-1862	373	11	and	and	CCONJ
cana-1862	373	12	bayesian	bayesian	NOUN
cana-1862	373	13	inference	inference	NOUN
cana-1862	373	14	utilized	utilize	VERB
cana-1862	373	15	by	by	ADP
cana-1862	373	16	the	the	DET
cana-1862	373	17	hybrid	hybrid	ADJ
cana-1862	373	18	approach	approach	NOUN
cana-1862	373	19	were	be	AUX
cana-1862	373	20	more	more	ADV
cana-1862	373	21	powerful	powerful	ADJ
cana-1862	373	22	in	in	ADP
cana-1862	373	23	terms	term	NOUN
cana-1862	373	24	of	of	ADP
cana-1862	373	25	performance	performance	NOUN
cana-1862	373	26	and	and	CCONJ
cana-1862	373	27	interpretability	interpretability	NOUN
cana-1862	373	28	.	.	PUNCT
cana-1862	374	1	this	this	DET
cana-1862	374	2	combination	combination	NOUN
cana-1862	374	3	provides	provide	VERB
cana-1862	374	4	a	a	DET
cana-1862	374	5	reference	reference	NOUN
cana-1862	374	6	model	model	NOUN
cana-1862	374	7	of	of	ADP
cana-1862	374	8	dynamic	dynamic	ADJ
cana-1862	374	9	,	,	PUNCT
cana-1862	374	10	intelligent	intelligent	ADJ
cana-1862	374	11	cybersecurity	cybersecurity	NOUN
cana-1862	374	12	frameworks	framework	NOUN
cana-1862	374	13	to	to	PART
cana-1862	374	14	proactively	proactively	ADV
cana-1862	374	15	and	and	CCONJ
cana-1862	374	16	responsively	responsively	ADV
cana-1862	374	17	detect	detect	VERB
cana-1862	374	18	threats	threat	NOUN
cana-1862	374	19	in	in	ADP
cana-1862	374	20	real	real	ADJ
cana-1862	374	21	-	-	PUNCT
cana-1862	374	22	time	time	NOUN
cana-1862	374	23	.	.	PUNCT
cana-1862	375	1	●	●	PUNCT
cana-1862	375	2	limitations	limitation	NOUN
cana-1862	375	3	and	and	CCONJ
cana-1862	375	4	future	future	ADJ
cana-1862	375	5	directions	direction	NOUN
cana-1862	375	6	although	although	SCONJ
cana-1862	375	7	the	the	DET
cana-1862	375	8	study	study	NOUN
cana-1862	375	9	showed	show	VERB
cana-1862	375	10	that	that	SCONJ
cana-1862	375	11	mathematical	mathematical	ADJ
cana-1862	375	12	techniques	technique	NOUN
cana-1862	375	13	can	can	AUX
cana-1862	375	14	enhance	enhance	VERB
cana-1862	375	15	machine	machine	NOUN
cana-1862	375	16	learning	learning	NOUN
cana-1862	375	17	in	in	ADP
cana-1862	375	18	vulnerability	vulnerability	NOUN
cana-1862	375	19	detection	detection	NOUN
cana-1862	375	20	,	,	PUNCT
cana-1862	375	21	common	common	ADJ
cana-1862	375	22	issues	issue	NOUN
cana-1862	375	23	remain	remain	VERB
cana-1862	375	24	.	.	PUNCT
cana-1862	376	1	data	datum	NOUN
cana-1862	376	2	quality	quality	NOUN
cana-1862	376	3	and	and	CCONJ
cana-1862	376	4	labelling	labelling	NOUN
cana-1862	376	5	–	–	PUNCT
cana-1862	376	6	this	this	PRON
cana-1862	376	7	remains	remain	VERB
cana-1862	376	8	one	one	NUM
cana-1862	376	9	of	of	ADP
cana-1862	376	10	the	the	DET
cana-1862	376	11	most	most	ADV
cana-1862	376	12	challenging	challenging	ADJ
cana-1862	376	13	areas	area	NOUN
cana-1862	376	14	.	.	PUNCT
cana-1862	377	1	most	most	ADJ
cana-1862	377	2	machine	machine	NOUN
cana-1862	377	3	learning	learning	NOUN
cana-1862	377	4	models	model	NOUN
cana-1862	377	5	require	require	VERB
cana-1862	377	6	good	good	ADJ
cana-1862	377	7	quality	quality	NOUN
cana-1862	377	8	,	,	PUNCT
cana-1862	377	9	labelled	label	VERB
cana-1862	377	10	datawhich	datawhich	NOUN
cana-1862	377	11	is	be	AUX
cana-1862	377	12	often	often	ADV
cana-1862	377	13	scarce	scarce	ADJ
cana-1862	377	14	in	in	ADP
cana-1862	377	15	security	security	NOUN
cana-1862	377	16	as	as	ADP
cana-1862	377	17	the	the	DET
cana-1862	377	18	landscape	landscape	NOUN
cana-1862	377	19	evolves	evolve	VERB
cana-1862	377	20	and	and	CCONJ
cana-1862	377	21	threats	threat	NOUN
cana-1862	377	22	are	be	AUX
cana-1862	377	23	frequently	frequently	ADV
cana-1862	377	24	changing.there	changing.there	NOUN
cana-1862	377	25	appears	appear	VERB
cana-1862	377	26	to	to	PART
cana-1862	377	27	be	be	AUX
cana-1862	377	28	a	a	DET
cana-1862	377	29	lack	lack	NOUN
cana-1862	377	30	-	-	PUNCT
cana-1862	377	31	of	of	ADP
cana-1862	377	32	exploration	exploration	NOUN
cana-1862	377	33	of	of	ADP
cana-1862	377	34	more	more	ADJ
cana-1862	377	35	start	start	VERB
cana-1862	377	36	-	-	PUNCT
cana-1862	377	37	of	of	ADP
cana-1862	377	38	-	-	PUNCT
cana-1862	377	39	the	the	DET
cana-1862	377	40	-	-	PUNCT
cana-1862	377	41	art	art	NOUN
cana-1862	377	42	second	second	ADJ
cana-1862	377	43	-	-	PUNCT
cana-1862	377	44	stage	stage	NOUN
cana-1862	377	45	/	/	SYM
cana-1862	377	46	simple	simple	ADJ
cana-1862	377	47	retrieval	retrieval	NOUN
cana-1862	377	48	(	(	PUNCT
cana-1862	377	49	on	on	ADP
cana-1862	377	50	compact	compact	ADJ
cana-1862	377	51	/	/	SYM
cana-1862	377	52	native	native	ADJ
cana-1862	377	53	data	data	NOUN
cana-1862	377	54	representations	representation	NOUN
cana-1862	377	55	)	)	PUNCT
cana-1862	377	56	cleverness	cleverness	NOUN
cana-1862	377	57	for	for	ADP
cana-1862	377	58	semi	semi	ADJ
cana-1862	377	59	/	/	ADJ
cana-1862	377	60	unsupervised	unsupervised	ADJ
cana-1862	377	61	learning	learning	NOUN
cana-1862	377	62	directly	directly	ADV
cana-1862	377	63	on	on	ADP
cana-1862	377	64	all	all	PRON
cana-1862	377	65	probing	probe	VERB
cana-1862	377	66	architectures	architecture	NOUN
cana-1862	377	67	with	with	ADP
cana-1862	377	68	little	little	ADJ
cana-1862	377	69	or	or	CCONJ
cana-1862	377	70	low	low	ADJ
cana-1862	377	71	tagged	tag	VERB
cana-1862	377	72	/	/	SYM
cana-1862	377	73	gold	gold	NOUN
cana-1862	377	74	-	-	PUNCT
cana-1862	377	75	standard	standard	NOUN
cana-1862	377	76	data	datum	NOUN
cana-1862	377	77	though	though	ADV
cana-1862	377	78	.	.	PUNCT
cana-1862	378	1	this	this	PRON
cana-1862	378	2	also	also	ADV
cana-1862	378	3	creates	create	VERB
cana-1862	378	4	a	a	DET
cana-1862	378	5	challenge	challenge	NOUN
cana-1862	378	6	for	for	ADP
cana-1862	378	7	scalability	scalability	NOUN
cana-1862	378	8	,	,	PUNCT
cana-1862	378	9	as	as	SCONJ
cana-1862	378	10	the	the	DET
cana-1862	378	11	volume	volume	NOUN
cana-1862	378	12	of	of	ADP
cana-1862	378	13	data	datum	NOUN
cana-1862	378	14	is	be	AUX
cana-1862	378	15	generated	generate	VERB
cana-1862	378	16	in	in	ADP
cana-1862	378	17	real	real	ADJ
cana-1862	378	18	-	-	PUNCT
cana-1862	378	19	time	time	NOUN
cana-1862	378	20	in	in	ADP
cana-1862	378	21	your	your	PRON
cana-1862	378	22	cybersecurity	cybersecurity	NOUN
cana-1862	378	23	systems	system	NOUN
cana-1862	378	24	.	.	PUNCT
cana-1862	379	1	the	the	DET
cana-1862	379	2	models	model	NOUN
cana-1862	379	3	develop	develop	VERB
cana-1862	379	4	in	in	ADP
cana-1862	379	5	this	this	DET
cana-1862	379	6	paper	paper	NOUN
cana-1862	379	7	look	look	VERB
cana-1862	379	8	quite	quite	ADV
cana-1862	379	9	promising	promising	ADJ
cana-1862	379	10	for	for	ADP
cana-1862	379	11	being	be	AUX
cana-1862	379	12	able	able	ADJ
cana-1862	379	13	to	to	PART
cana-1862	379	14	scale	scale	VERB
cana-1862	379	15	up	up	ADP
cana-1862	379	16	to	to	ADP
cana-1862	379	17	large	large	ADJ
cana-1862	379	18	-	-	PUNCT
cana-1862	379	19	scale	scale	NOUN
cana-1862	379	20	datasets	dataset	NOUN
cana-1862	379	21	,	,	PUNCT
cana-1862	379	22	but	but	CCONJ
cana-1862	379	23	computational	computational	ADJ
cana-1862	379	24	efficiency	efficiency	NOUN
cana-1862	379	25	and	and	CCONJ
cana-1862	379	26	resource	resource	NOUN
cana-1862	379	27	management	management	NOUN
cana-1862	379	28	is	be	AUX
cana-1862	379	29	critical	critical	ADJ
cana-1862	379	30	for	for	ADP
cana-1862	379	31	real	real	ADJ
cana-1862	379	32	world	world	NOUN
cana-1862	379	33	applicability	applicability	NOUN
cana-1862	379	34	.	.	PUNCT
cana-1862	380	1	our	our	PRON
cana-1862	380	2	future	future	ADJ
cana-1862	380	3	work	work	NOUN
cana-1862	380	4	will	will	AUX
cana-1862	380	5	try	try	VERB
cana-1862	380	6	to	to	PART
cana-1862	380	7	extend	extend	VERB
cana-1862	380	8	these	these	DET
cana-1862	380	9	models	model	NOUN
cana-1862	380	10	and	and	CCONJ
cana-1862	380	11	make	make	VERB
cana-1862	380	12	them	they	PRON
cana-1862	380	13	acceptable	acceptable	ADJ
cana-1862	380	14	in	in	ADP
cana-1862	380	15	cloud	cloud	NOUN
cana-1862	380	16	-	-	PUNCT
cana-1862	380	17	based	base	VERB
cana-1862	380	18	environments	environment	NOUN
cana-1862	380	19	or	or	CCONJ
cana-1862	380	20	distributed	distribute	VERB
cana-1862	380	21	network	network	NOUN
cana-1862	380	22	architectures	architecture	NOUN
cana-1862	380	23	where	where	SCONJ
cana-1862	380	24	it	it	PRON
cana-1862	380	25	may	may	AUX
cana-1862	380	26	scale	scale	VERB
cana-1862	380	27	well	well	ADV
cana-1862	380	28	yet	yet	ADV
cana-1862	380	29	have	have	VERB
cana-1862	380	30	appealing	appeal	VERB
cana-1862	380	31	detection	detection	NOUN
cana-1862	380	32	accuracy	accuracy	NOUN
cana-1862	380	33	.	.	PUNCT
cana-1862	381	1	interpretability	interpretability	NOUN
cana-1862	381	2	of	of	ADP
cana-1862	381	3	complex	complex	ADJ
cana-1862	381	4	models	model	NOUN
cana-1862	381	5	,	,	PUNCT
cana-1862	381	6	especially	especially	ADV
cana-1862	381	7	deep	deep	ADJ
cana-1862	381	8	neural	neural	ADJ
cana-1862	381	9	networks	network	NOUN
cana-1862	381	10	,	,	PUNCT
cana-1862	381	11	on	on	ADP
cana-1862	381	12	the	the	DET
cana-1862	381	13	other	other	ADJ
cana-1862	381	14	hand	hand	NOUN
cana-1862	381	15	continues	continue	VERB
cana-1862	381	16	to	to	PART
cana-1862	381	17	be	be	AUX
cana-1862	381	18	an	an	DET
cana-1862	381	19	open	open	ADJ
cana-1862	381	20	problem	problem	NOUN
cana-1862	381	21	.	.	PUNCT
cana-1862	382	1	so	so	ADV
cana-1862	382	2	understanding	understand	VERB
cana-1862	382	3	why	why	SCONJ
cana-1862	382	4	the	the	DET
cana-1862	382	5	model	model	NOUN
cana-1862	382	6	makes	make	VERB
cana-1862	382	7	decisions	decision	NOUN
cana-1862	382	8	is	be	AUX
cana-1862	382	9	a	a	DET
cana-1862	382	10	critical	critical	ADJ
cana-1862	382	11	part	part	NOUN
cana-1862	382	12	of	of	ADP
cana-1862	382	13	justifying	justify	VERB
cana-1862	382	14	actions	action	NOUN
cana-1862	382	15	and	and	CCONJ
cana-1862	382	16	building	build	VERB
cana-1862	382	17	better	well	ADJ
cana-1862	382	18	defences	defence	NOUN
cana-1862	382	19	in	in	ADP
cana-1862	382	20	security	security	NOUN
cana-1862	382	21	operations	operation	NOUN
cana-1862	382	22	.	.	PUNCT
cana-1862	383	1	future	future	ADJ
cana-1862	383	2	-	-	PUNCT
cana-1862	383	3	make	make	VERB
cana-1862	383	4	pipeline	pipeline	NOUN
cana-1862	383	5	efforts	effort	NOUN
cana-1862	383	6	of	of	ADP
cana-1862	383	7	explainable	explainable	ADJ
cana-1862	383	8	ai	ai	NOUN
cana-1862	383	9	(	(	PUNCT
cana-1862	383	10	xai	xai	PROPN
cana-1862	383	11	)	)	PUNCT
cana-1862	383	12	and	and	CCONJ
cana-1862	383	13	model	model	NOUN
cana-1862	383	14	interpretability	interpretability	NOUN
cana-1862	383	15	integration	integration	NOUN
cana-1862	383	16	are	be	AUX
cana-1862	383	17	required	require	VERB
cana-1862	383	18	to	to	PART
cana-1862	383	19	bridge	bridge	VERB
cana-1862	383	20	the	the	DET
cana-1862	383	21	gulf	gulf	NOUN
cana-1862	383	22	between	between	ADP
cana-1862	383	23	model	model	NOUN
cana-1862	383	24	accuracy	accuracy	NOUN
cana-1862	383	25	and	and	CCONJ
cana-1862	383	26	actionable	actionable	ADJ
cana-1862	383	27	insights	insight	NOUN
cana-1862	383	28	.	.	PUNCT
cana-1862	384	1	finally	finally	ADV
cana-1862	384	2	,	,	PUNCT
cana-1862	384	3	the	the	DET
cana-1862	384	4	learnability	learnability	NOUN
cana-1862	384	5	of	of	ADP
cana-1862	384	6	rapidly	rapidly	ADV
cana-1862	384	7	-	-	PUNCT
cana-1862	384	8	evolving	evolve	VERB
cana-1862	384	9	threats	threat	NOUN
cana-1862	384	10	implied	imply	VERB
cana-1862	384	11	by	by	ADP
cana-1862	384	12	their	their	PRON
cana-1862	384	13	machine	machine	NOUN
cana-1862	384	14	-	-	PUNCT
cana-1862	384	15	based	base	VERB
cana-1862	384	16	models	model	NOUN
cana-1862	384	17	;	;	PUNCT
cana-1862	384	18	methods	method	NOUN
cana-1862	384	19	such	such	ADJ
cana-1862	384	20	as	as	ADP
cana-1862	384	21	reinforcement	reinforcement	NOUN
cana-1862	384	22	learning	learning	NOUN
cana-1862	384	23	and	and	CCONJ
cana-1862	384	24	continual	continual	ADJ
cana-1862	384	25	learning	learning	NOUN
cana-1862	384	26	show	show	VERB
cana-1862	384	27	promise	promise	NOUN
cana-1862	384	28	in	in	ADP
cana-1862	384	29	developing	develop	VERB
cana-1862	384	30	systems	system	NOUN
cana-1862	384	31	that	that	PRON
cana-1862	384	32	adapt	adapt	VERB
cana-1862	384	33	with	with	ADP
cana-1862	384	34	the	the	DET
cana-1862	384	35	threat	threat	NOUN
cana-1862	384	36	landscape	landscape	NOUN
cana-1862	384	37	,	,	PUNCT
cana-1862	384	38	but	but	CCONJ
cana-1862	384	39	continued	continued	ADJ
cana-1862	384	40	research	research	NOUN
cana-1862	384	41	is	be	AUX
cana-1862	384	42	required	require	VERB
cana-1862	384	43	to	to	PART
cana-1862	384	44	fully	fully	ADV
cana-1862	384	45	exploit	exploit	VERB
cana-1862	384	46	their	their	PRON
cana-1862	384	47	capabilities	capability	NOUN
cana-1862	384	48	for	for	ADP
cana-1862	384	49	cyber	cyber	ADJ
cana-1862	384	50	security	security	NOUN
cana-1862	384	51	contexts	contexts	NOUN
cana-1862	384	52	.	.	PUNCT
cana-1862	385	1	concluding	conclude	VERB
cana-1862	385	2	,	,	PUNCT
cana-1862	385	3	the	the	DET
cana-1862	385	4	research	research	NOUN
cana-1862	385	5	presents	present	VERB
cana-1862	385	6	an	an	DET
cana-1862	385	7	exhibition	exhibition	NOUN
cana-1862	385	8	where	where	SCONJ
cana-1862	385	9	mathematical	mathematical	ADJ
cana-1862	385	10	models	model	NOUN
cana-1862	385	11	are	be	AUX
cana-1862	385	12	applied	apply	VERB
cana-1862	385	13	with	with	ADP
cana-1862	385	14	machine	machine	NOUN
cana-1862	385	15	learning	learning	NOUN
cana-1862	385	16	models	model	NOUN
cana-1862	385	17	to	to	PART
cana-1862	385	18	ensure	ensure	VERB
cana-1862	385	19	vulnerability	vulnerability	NOUN
cana-1862	385	20	detection	detection	NOUN
cana-1862	385	21	in	in	ADP
cana-1862	385	22	information	information	NOUN
cana-1862	385	23	security	security	NOUN
cana-1862	385	24	.	.	PUNCT
cana-1862	386	1	a	a	DET
cana-1862	386	2	unified	unified	ADJ
cana-1862	386	3	approach	approach	NOUN
cana-1862	386	4	to	to	ADP
cana-1862	386	5	supervised	supervised	ADJ
cana-1862	386	6	learning	learning	NOUN
cana-1862	386	7	,	,	PUNCT
cana-1862	386	8	unsupervised	unsupervised	ADJ
cana-1862	386	9	learning	learning	NOUN
cana-1862	386	10	,	,	PUNCT
cana-1862	386	11	probabilistic	probabilistic	ADJ
cana-1862	386	12	modelling	modelling	NOUN
cana-1862	386	13	and	and	CCONJ
cana-1862	386	14	reinforcement	reinforcement	NOUN
cana-1862	386	15	allows	allow	VERB
cana-1862	386	16	the	the	DET
cana-1862	386	17	complete	complete	ADJ
cana-1862	386	18	nameless	nameless	ADJ
cana-1862	386	19	detection	detection	NOUN
cana-1862	386	20	of	of	ADP
cana-1862	386	21	known	known	ADJ
cana-1862	386	22	and	and	CCONJ
cana-1862	386	23	unknown	unknown	ADJ
cana-1862	386	24	vulnerabilities	vulnerability	NOUN
cana-1862	386	25	in	in	ADP
cana-1862	386	26	real	real	ADJ
cana-1862	386	27	time	time	NOUN
cana-1862	386	28	.	.	PUNCT
cana-1862	387	1	our	our	PRON
cana-1862	387	2	results	result	NOUN
cana-1862	387	3	suggest	suggest	VERB
cana-1862	387	4	that	that	SCONJ
cana-1862	387	5	integrating	integrate	VERB
cana-1862	387	6	multiple	multiple	ADJ
cana-1862	387	7	layers	layer	NOUN
cana-1862	387	8	of	of	ADP
cana-1862	387	9	mathematical	mathematical	ADJ
cana-1862	387	10	techniques	technique	NOUN
cana-1862	387	11	for	for	ADP
cana-1862	387	12	data	datum	NOUN
cana-1862	387	13	pre	pre	ADJ
cana-1862	387	14	-	-	ADJ
cana-1862	387	15	processing	processing	ADJ
cana-1862	387	16	,	,	PUNCT
cana-1862	387	17	optimization	optimization	NOUN
cana-1862	387	18	and	and	CCONJ
cana-1862	387	19	probabilistic	probabilistic	ADJ
cana-1862	387	20	inference	inference	NOUN
cana-1862	387	21	can	can	AUX
cana-1862	387	22	considerably	considerably	ADV
cana-1862	387	23	improve	improve	VERB
cana-1862	387	24	both	both	DET
cana-1862	387	25	the	the	DET
cana-1862	387	26	performance	performance	NOUN
cana-1862	387	27	and	and	CCONJ
cana-1862	387	28	robustness	robustness	NOUN
cana-1862	387	29	of	of	ADP
cana-1862	387	30	cybersecurity	cybersecurity	NOUN
cana-1862	387	31	systems	system	NOUN
cana-1862	387	32	.	.	PUNCT
cana-1862	388	1	communications	communication	NOUN
cana-1862	388	2	on	on	ADP
cana-1862	388	3	applied	apply	VERB
cana-1862	388	4	nonlinear	nonlinear	ADJ
cana-1862	388	5	analysis	analysis	NOUN
cana-1862	388	6	issn	issn	NOUN
cana-1862	388	7	:	:	PUNCT
cana-1862	388	8	1074	1074	NUM
cana-1862	388	9	-	-	PUNCT
cana-1862	388	10	133x	133x	NUM
cana-1862	388	11	vol	vol	NOUN
cana-1862	388	12	32	32	NUM
cana-1862	388	13	no	no	NOUN
cana-1862	388	14	.	.	NOUN
cana-1862	388	15	2	2	NUM
cana-1862	388	16	(	(	PUNCT
cana-1862	388	17	2025	2025	NUM
cana-1862	388	18	)	)	PUNCT
cana-1862	388	19	716	716	NUM
cana-1862	388	20	https://internationalpubls.com	https://internationalpubls.com	X
cana-1862	388	21	the	the	DET
cana-1862	388	22	results	result	NOUN
cana-1862	388	23	of	of	ADP
cana-1862	388	24	this	this	DET
cana-1862	388	25	study	study	NOUN
cana-1862	388	26	seem	seem	VERB
cana-1862	388	27	to	to	PART
cana-1862	388	28	point	point	VERB
cana-1862	388	29	the	the	DET
cana-1862	388	30	way	way	NOUN
cana-1862	388	31	for	for	ADP
cana-1862	388	32	positive	positive	ADJ
cana-1862	388	33	advancements	advancement	NOUN
cana-1862	388	34	in	in	ADP
cana-1862	388	35	intelligent	intelligent	ADJ
cana-1862	388	36	,	,	PUNCT
cana-1862	388	37	adaptive	adaptive	ADJ
cana-1862	388	38	cybersecurity	cybersecurity	NOUN
cana-1862	388	39	frameworks	framework	NOUN
cana-1862	388	40	.	.	PUNCT
cana-1862	389	1	whilst	whilst	SCONJ
cana-1862	389	2	doing	do	VERB
cana-1862	389	3	so	so	ADV
cana-1862	389	4	,	,	PUNCT
cana-1862	389	5	the	the	DET
cana-1862	389	6	cybersecurity	cybersecurity	NOUN
cana-1862	389	7	community	community	NOUN
cana-1862	389	8	will	will	AUX
cana-1862	389	9	hopefully	hopefully	ADV
cana-1862	389	10	progress	progress	VERB
cana-1862	389	11	on	on	ADP
cana-1862	389	12	our	our	PRON
cana-1862	389	13	path	path	NOUN
cana-1862	389	14	towards	towards	ADP
cana-1862	389	15	being	be	AUX
cana-1862	389	16	able	able	ADJ
cana-1862	389	17	to	to	PART
cana-1862	389	18	develop	develop	VERB
cana-1862	389	19	systems	system	NOUN
cana-1862	389	20	which	which	PRON
cana-1862	389	21	not	not	PART
cana-1862	389	22	only	only	ADV
cana-1862	389	23	meet	meet	VERB
cana-1862	389	24	this	this	DET
cana-1862	389	25	requirement	requirement	NOUN
cana-1862	389	26	of	of	ADP
cana-1862	389	27	identifying	identify	VERB
cana-1862	389	28	threats	threat	NOUN
cana-1862	389	29	and	and	CCONJ
cana-1862	389	30	vulnerabilities	vulnerability	NOUN
cana-1862	389	31	,	,	PUNCT
cana-1862	389	32	but	but	CCONJ
cana-1862	389	33	also	also	ADV
cana-1862	389	34	have	have	VERB
cana-1862	389	35	capabilities	capability	NOUN
cana-1862	389	36	enabling	enable	VERB
cana-1862	389	37	us	we	PRON
cana-1862	389	38	to	to	PART
cana-1862	389	39	make	make	VERB
cana-1862	389	40	networks	network	NOUN
cana-1862	389	41	secure	secure	ADJ
cana-1862	389	42	in	in	ADP
cana-1862	389	43	an	an	DET
cana-1862	389	44	everchanging	everchanging	ADJ
cana-1862	389	45	digital	digital	ADJ
cana-1862	389	46	landscape	landscape	NOUN
cana-1862	389	47	.	.	PUNCT
cana-1862	390	1	these	these	DET
cana-1862	390	2	findings	finding	NOUN
cana-1862	390	3	pave	pave	VERB
cana-1862	390	4	the	the	DET
cana-1862	390	5	way	way	NOUN
cana-1862	390	6	for	for	ADP
cana-1862	390	7	a	a	DET
cana-1862	390	8	new	new	ADJ
cana-1862	390	9	breed	breed	NOUN
cana-1862	390	10	of	of	ADP
cana-1862	390	11	real	real	ADJ
cana-1862	390	12	-	-	PUNCT
cana-1862	390	13	time	time	NOUN
cana-1862	390	14	alarm	alarm	NOUN
cana-1862	390	15	systems	system	NOUN
cana-1862	390	16	that	that	PRON
cana-1862	390	17	will	will	AUX
cana-1862	390	18	protect	protect	VERB
cana-1862	390	19	essential	essential	ADJ
cana-1862	390	20	information	information	NOUN
cana-1862	390	21	by	by	ADP
cana-1862	390	22	securing	secure	VERB
cana-1862	390	23	privacy	privacy	NOUN
cana-1862	390	24	and	and	CCONJ
cana-1862	390	25	security	security	NOUN
cana-1862	390	26	in	in	ADP
cana-1862	390	27	an	an	DET
cana-1862	390	28	age	age	NOUN
cana-1862	390	29	of	of	ADP
cana-1862	390	30	growing	grow	VERB
cana-1862	390	31	dependence	dependence	NOUN
cana-1862	390	32	on	on	ADP
cana-1862	390	33	digital	digital	ADJ
cana-1862	390	34	connectivity	connectivity	NOUN
cana-1862	390	35	.	.	PUNCT
cana-1862	391	1	references	reference	NOUN
cana-1862	391	2	:	:	PUNCT
cana-1862	392	1	[	[	X
cana-1862	392	2	1	1	NUM
cana-1862	392	3	]	]	X
cana-1862	392	4	khan	khan	PROPN
cana-1862	392	5	,	,	PUNCT
cana-1862	392	6	muskan	muskan	ADJ
cana-1862	392	7	,	,	PUNCT
cana-1862	392	8	and	and	CCONJ
cana-1862	392	9	laiba	laiba	ADJ
cana-1862	392	10	ghafoor	ghafoor	NOUN
cana-1862	392	11	.	.	PUNCT
cana-1862	393	1	"	"	PUNCT
cana-1862	393	2	adversarial	adversarial	ADJ
cana-1862	393	3	machine	machine	NOUN
cana-1862	393	4	learning	learn	VERB
cana-1862	393	5	in	in	ADP
cana-1862	393	6	the	the	DET
cana-1862	393	7	context	context	NOUN
cana-1862	393	8	of	of	ADP
cana-1862	393	9	network	network	NOUN
cana-1862	393	10	security	security	NOUN
cana-1862	393	11	:	:	PUNCT
cana-1862	393	12	challenges	challenge	NOUN
cana-1862	393	13	and	and	CCONJ
cana-1862	393	14	solutions	solution	NOUN
cana-1862	393	15	.	.	PUNCT
cana-1862	393	16	"	"	PUNCT
cana-1862	393	17	journal	journal	NOUN
cana-1862	393	18	of	of	ADP
cana-1862	393	19	computational	computational	ADJ
cana-1862	393	20	intelligence	intelligence	NOUN
cana-1862	393	21	and	and	CCONJ
cana-1862	393	22	robotics	robotic	NOUN
cana-1862	393	23	4.1	4.1	NUM
cana-1862	393	24	(	(	PUNCT
cana-1862	393	25	2024	2024	NUM
cana-1862	393	26	):	):	PUNCT
cana-1862	393	27	51	51	NUM
cana-1862	393	28	-	-	SYM
cana-1862	393	29	63	63	NUM
cana-1862	393	30	.	.	PUNCT
cana-1862	394	1	[	[	X
cana-1862	394	2	2	2	NUM
cana-1862	394	3	]	]	X
cana-1862	394	4	bharathi	bharathi	NOUN
cana-1862	394	5	,	,	PUNCT
cana-1862	394	6	v.	v.	ADP
cana-1862	394	7	"	"	PUNCT
cana-1862	394	8	vulnerability	vulnerability	NOUN
cana-1862	394	9	detection	detection	NOUN
cana-1862	394	10	in	in	ADP
cana-1862	394	11	cyber	cyber	ADJ
cana-1862	394	12	-	-	PUNCT
cana-1862	394	13	physical	physical	ADJ
cana-1862	394	14	system	system	NOUN
cana-1862	394	15	using	use	VERB
cana-1862	394	16	machine	machine	NOUN
cana-1862	394	17	learning	learning	NOUN
cana-1862	394	18	.	.	PUNCT
cana-1862	394	19	"	"	PUNCT
cana-1862	394	20	scalable	scalable	ADJ
cana-1862	394	21	computing	computing	NOUN
cana-1862	394	22	:	:	PUNCT
cana-1862	394	23	practice	practice	NOUN
cana-1862	394	24	and	and	CCONJ
cana-1862	394	25	experience	experience	NOUN
cana-1862	394	26	25.1	25.1	NUM
cana-1862	394	27	(	(	PUNCT
cana-1862	394	28	2024	2024	NUM
cana-1862	394	29	):	):	PUNCT
cana-1862	394	30	577	577	NUM
cana-1862	394	31	-	-	SYM
cana-1862	394	32	591	591	NUM
cana-1862	394	33	.	.	PUNCT
cana-1862	395	1	[	[	X
cana-1862	395	2	3	3	NUM
cana-1862	395	3	]	]	X
cana-1862	395	4	gong	gong	NOUN
cana-1862	395	5	,	,	PUNCT
cana-1862	395	6	yulu	yulu	VERB
cana-1862	395	7	,	,	PUNCT
cana-1862	395	8	et	et	PROPN
cana-1862	395	9	al	al	PROPN
cana-1862	395	10	.	.	PUNCT
cana-1862	396	1	"	"	PUNCT
cana-1862	396	2	enhancing	enhance	VERB
cana-1862	396	3	cybersecurity	cybersecurity	NOUN
cana-1862	396	4	resilience	resilience	NOUN
cana-1862	396	5	in	in	ADP
cana-1862	396	6	finance	finance	NOUN
cana-1862	396	7	with	with	ADP
cana-1862	396	8	deep	deep	ADJ
cana-1862	396	9	learning	learning	NOUN
cana-1862	396	10	for	for	ADP
cana-1862	396	11	advanced	advanced	ADJ
cana-1862	396	12	threat	threat	NOUN
cana-1862	396	13	detection	detection	NOUN
cana-1862	396	14	.	.	PUNCT
cana-1862	396	15	"	"	PUNCT
cana-1862	397	1	arxiv	arxiv	PROPN
cana-1862	397	2	preprint	preprint	NOUN
cana-1862	397	3	arxiv:2402.09820	arxiv:2402.09820	NOUN
cana-1862	397	4	(	(	PUNCT
cana-1862	397	5	2024	2024	NUM
cana-1862	397	6	)	)	PUNCT
cana-1862	397	7	.	.	PUNCT
cana-1862	398	1	[	[	X
cana-1862	398	2	4	4	NUM
cana-1862	398	3	]	]	SYM
cana-1862	398	4	yang	yang	PROPN
cana-1862	398	5	,	,	PUNCT
cana-1862	398	6	peng	peng	PROPN
cana-1862	398	7	,	,	PUNCT
cana-1862	398	8	and	and	CCONJ
cana-1862	398	9	xiaofeng	xiaofeng	PROPN
cana-1862	398	10	wang	wang	PROPN
cana-1862	398	11	.	.	PUNCT
cana-1862	399	1	"	"	PUNCT
cana-1862	399	2	vulnerability	vulnerability	NOUN
cana-1862	399	3	extraction	extraction	NOUN
cana-1862	399	4	and	and	CCONJ
cana-1862	399	5	prediction	prediction	NOUN
cana-1862	399	6	method	method	NOUN
cana-1862	399	7	based	base	VERB
cana-1862	399	8	on	on	ADP
cana-1862	399	9	improved	improved	ADJ
cana-1862	399	10	information	information	NOUN
cana-1862	399	11	gain	gain	NOUN
cana-1862	399	12	algorithm	algorithm	NOUN
cana-1862	399	13	.	.	PUNCT
cana-1862	399	14	"	"	PUNCT
cana-1862	400	1	plos	plo	VERB
cana-1862	400	2	one	one	NUM
cana-1862	400	3	19.9	19.9	NUM
cana-1862	400	4	(	(	PUNCT
cana-1862	400	5	2024	2024	NUM
cana-1862	400	6	):	):	PUNCT
cana-1862	400	7	e0309809	e0309809	NOUN
cana-1862	400	8	.	.	PUNCT
cana-1862	401	1	[	[	X
cana-1862	401	2	5	5	NUM
cana-1862	401	3	]	]	PUNCT
cana-1862	401	4	ozkan	ozkan	NOUN
cana-1862	401	5	-	-	PUNCT
cana-1862	401	6	ozay	ozay	ADV
cana-1862	401	7	,	,	PUNCT
cana-1862	401	8	merve	merve	NOUN
cana-1862	401	9	,	,	PUNCT
cana-1862	401	10	et	et	PROPN
cana-1862	401	11	al	al	PROPN
cana-1862	401	12	.	.	PUNCT
cana-1862	402	1	"	"	PUNCT
cana-1862	402	2	a	a	DET
cana-1862	402	3	comprehensive	comprehensive	ADJ
cana-1862	402	4	survey	survey	NOUN
cana-1862	402	5	:	:	PUNCT
cana-1862	402	6	evaluating	evaluate	VERB
cana-1862	402	7	the	the	DET
cana-1862	402	8	efficiency	efficiency	NOUN
cana-1862	402	9	of	of	ADP
cana-1862	402	10	artificial	artificial	ADJ
cana-1862	402	11	intelligence	intelligence	NOUN
cana-1862	402	12	and	and	CCONJ
cana-1862	402	13	machine	machine	NOUN
cana-1862	402	14	learning	learn	VERB
cana-1862	402	15	techniques	technique	NOUN
cana-1862	402	16	on	on	ADP
cana-1862	402	17	cyber	cyber	ADJ
cana-1862	402	18	security	security	NOUN
cana-1862	402	19	solutions	solution	NOUN
cana-1862	402	20	.	.	PUNCT
cana-1862	402	21	"	"	PUNCT
cana-1862	403	1	ieee	ieee	NOUN
cana-1862	403	2	access	access	NOUN
cana-1862	403	3	(	(	PUNCT
cana-1862	403	4	2024	2024	NUM
cana-1862	403	5	)	)	PUNCT
cana-1862	403	6	.	.	PUNCT
cana-1862	404	1	[	[	X
cana-1862	404	2	6	6	NUM
cana-1862	404	3	]	]	SYM
cana-1862	404	4	ni	ni	PROPN
cana-1862	404	5	,	,	PUNCT
cana-1862	404	6	chunchun	chunchun	NOUN
cana-1862	404	7	,	,	PUNCT
cana-1862	404	8	and	and	CCONJ
cana-1862	404	9	shan	shan	PROPN
cana-1862	404	10	cang	cang	PROPN
cana-1862	404	11	li	li	PROPN
cana-1862	404	12	.	.	PUNCT
cana-1862	405	1	"	"	PUNCT
cana-1862	405	2	machine	machine	NOUN
cana-1862	405	3	learning	learning	NOUN
cana-1862	405	4	enabled	enable	VERB
cana-1862	405	5	industrial	industrial	ADJ
cana-1862	405	6	iot	iot	NOUN
cana-1862	405	7	security	security	NOUN
cana-1862	405	8	:	:	PUNCT
cana-1862	405	9	challenges	challenge	NOUN
cana-1862	405	10	,	,	PUNCT
cana-1862	405	11	trends	trend	NOUN
cana-1862	405	12	and	and	CCONJ
cana-1862	405	13	solutions	solution	NOUN
cana-1862	405	14	.	.	PUNCT
cana-1862	405	15	"	"	PUNCT
cana-1862	406	1	journal	journal	NOUN
cana-1862	406	2	of	of	ADP
cana-1862	406	3	industrial	industrial	ADJ
cana-1862	406	4	information	information	NOUN
cana-1862	406	5	integration	integration	NOUN
cana-1862	406	6	(	(	PUNCT
cana-1862	406	7	2024	2024	NUM
cana-1862	406	8	):	):	PUNCT
cana-1862	406	9	100549	100549	NUM
cana-1862	406	10	.	.	PUNCT
cana-1862	407	1	[	[	X
cana-1862	407	2	7	7	NUM
cana-1862	407	3	]	]	X
cana-1862	407	4	labu	labu	NOUN
cana-1862	407	5	,	,	PUNCT
cana-1862	407	6	md	md	PROPN
cana-1862	407	7	rasheduzzaman	rasheduzzaman	PROPN
cana-1862	407	8	,	,	PUNCT
cana-1862	407	9	and	and	CCONJ
cana-1862	407	10	md	md	PROPN
cana-1862	407	11	fahim	fahim	PROPN
cana-1862	407	12	ahammed	ahamme	VERB
cana-1862	407	13	.	.	PUNCT
cana-1862	408	1	"	"	PUNCT
cana-1862	408	2	next	next	ADJ
cana-1862	408	3	-	-	PUNCT
cana-1862	408	4	generation	generation	NOUN
cana-1862	408	5	cyber	cyber	NOUN
cana-1862	408	6	threat	threat	NOUN
cana-1862	408	7	detection	detection	NOUN
cana-1862	408	8	and	and	CCONJ
cana-1862	408	9	mitigation	mitigation	NOUN
cana-1862	408	10	strategies	strategy	NOUN
cana-1862	408	11	:	:	PUNCT
cana-1862	408	12	a	a	DET
cana-1862	408	13	focus	focus	NOUN
cana-1862	408	14	on	on	ADP
cana-1862	408	15	artificial	artificial	ADJ
cana-1862	408	16	intelligence	intelligence	NOUN
cana-1862	408	17	and	and	CCONJ
cana-1862	408	18	machine	machine	NOUN
cana-1862	408	19	learning	learning	NOUN
cana-1862	408	20	.	.	PUNCT
cana-1862	408	21	"	"	PUNCT
cana-1862	409	1	journal	journal	NOUN
cana-1862	409	2	of	of	ADP
cana-1862	409	3	computer	computer	NOUN
cana-1862	409	4	science	science	NOUN
cana-1862	409	5	and	and	CCONJ
cana-1862	409	6	technology	technology	NOUN
cana-1862	409	7	studies	study	NOUN
cana-1862	409	8	6.1	6.1	NUM
cana-1862	409	9	(	(	PUNCT
cana-1862	409	10	2024	2024	NUM
cana-1862	409	11	):	):	PUNCT
cana-1862	409	12	179	179	NUM
cana-1862	409	13	-	-	SYM
cana-1862	409	14	188	188	NUM
cana-1862	409	15	.	.	PUNCT
cana-1862	410	1	[	[	X
cana-1862	410	2	8	8	NUM
cana-1862	410	3	]	]	X
cana-1862	410	4	jimmy	jimmy	PROPN
cana-1862	410	5	,	,	PUNCT
cana-1862	410	6	f.	f.	PROPN
cana-1862	410	7	n.	n.	PROPN
cana-1862	410	8	u.	u.	PROPN
cana-1862	410	9	"	"	PUNCT
cana-1862	410	10	cyber	cyber	ADJ
cana-1862	410	11	security	security	NOUN
cana-1862	410	12	vulnerabilities	vulnerability	NOUN
cana-1862	410	13	and	and	CCONJ
cana-1862	410	14	remediation	remediation	NOUN
cana-1862	410	15	through	through	ADP
cana-1862	410	16	cloud	cloud	ADJ
cana-1862	410	17	security	security	NOUN
cana-1862	410	18	tools	tool	NOUN
cana-1862	410	19	.	.	PUNCT
cana-1862	410	20	"	"	PUNCT
cana-1862	411	1	journal	journal	NOUN
cana-1862	411	2	of	of	ADP
cana-1862	411	3	artificial	artificial	ADJ
cana-1862	411	4	intelligence	intelligence	NOUN
cana-1862	411	5	general	general	ADJ
cana-1862	411	6	science	science	PROPN
cana-1862	411	7	(	(	PUNCT
cana-1862	411	8	jaigs	jaigs	PROPN
cana-1862	411	9	)	)	PUNCT
cana-1862	411	10	issn	issn	PROPN
cana-1862	411	11	:	:	PUNCT
cana-1862	411	12	3006	3006	NUM
cana-1862	411	13	-	-	SYM
cana-1862	411	14	4023	4023	NUM
cana-1862	411	15	2.1	2.1	NUM
cana-1862	411	16	(	(	PUNCT
cana-1862	411	17	2024	2024	NUM
cana-1862	411	18	):	):	PUNCT
cana-1862	411	19	129	129	NUM
cana-1862	411	20	-	-	SYM
cana-1862	411	21	171	171	NUM
cana-1862	411	22	.	.	PUNCT
cana-1862	412	1	[	[	X
cana-1862	412	2	9	9	NUM
cana-1862	412	3	]	]	SYM
cana-1862	412	4	hashmi	hashmi	PROPN
cana-1862	412	5	,	,	PUNCT
cana-1862	412	6	ehtesham	ehtesham	PROPN
cana-1862	412	7	,	,	PUNCT
cana-1862	412	8	muhammad	muhammad	PROPN
cana-1862	412	9	mudassar	mudassar	PROPN
cana-1862	412	10	yamin	yamin	PROPN
cana-1862	412	11	,	,	PUNCT
cana-1862	412	12	and	and	CCONJ
cana-1862	412	13	sule	sule	PROPN
cana-1862	412	14	yildirim	yildirim	PROPN
cana-1862	412	15	yayilgan	yayilgan	PROPN
cana-1862	412	16	.	.	PUNCT
cana-1862	413	1	"	"	PUNCT
cana-1862	413	2	securing	secure	VERB
cana-1862	413	3	tomorrow	tomorrow	NOUN
cana-1862	413	4	:	:	PUNCT
cana-1862	413	5	a	a	DET
cana-1862	413	6	comprehensive	comprehensive	ADJ
cana-1862	413	7	survey	survey	NOUN
cana-1862	413	8	on	on	ADP
cana-1862	413	9	the	the	DET
cana-1862	413	10	synergy	synergy	NOUN
cana-1862	413	11	of	of	ADP
cana-1862	413	12	artificial	artificial	ADJ
cana-1862	413	13	intelligence	intelligence	NOUN
cana-1862	413	14	and	and	CCONJ
cana-1862	413	15	information	information	NOUN
cana-1862	413	16	security	security	NOUN
cana-1862	413	17	.	.	PUNCT
cana-1862	413	18	"	"	PUNCT
cana-1862	414	1	ai	ai	VERB
cana-1862	414	2	and	and	CCONJ
cana-1862	414	3	ethics	ethic	NOUN
cana-1862	414	4	(	(	PUNCT
cana-1862	414	5	2024	2024	NUM
cana-1862	414	6	):	):	PUNCT
cana-1862	414	7	119	119	NUM
cana-1862	414	8	.	.	PUNCT
cana-1862	415	1	[	[	X
cana-1862	415	2	10	10	NUM
cana-1862	415	3	]	]	SYM
cana-1862	415	4	okoli	okoli	NOUN
cana-1862	415	5	,	,	PUNCT
cana-1862	415	6	ugochukwu	ugochukwu	NOUN
cana-1862	415	7	ikechukwu	ikechukwu	NOUN
cana-1862	415	8	,	,	PUNCT
cana-1862	415	9	et	et	PROPN
cana-1862	415	10	al	al	PROPN
cana-1862	415	11	.	.	PUNCT
cana-1862	416	1	"	"	PUNCT
cana-1862	416	2	machine	machine	NOUN
cana-1862	416	3	learning	learning	NOUN
cana-1862	416	4	in	in	ADP
cana-1862	416	5	cybersecurity	cybersecurity	NOUN
cana-1862	416	6	:	:	PUNCT
cana-1862	416	7	a	a	DET
cana-1862	416	8	review	review	NOUN
cana-1862	416	9	of	of	ADP
cana-1862	416	10	threat	threat	NOUN
cana-1862	416	11	detection	detection	NOUN
cana-1862	416	12	and	and	CCONJ
cana-1862	416	13	defense	defense	NOUN
cana-1862	416	14	mechanisms	mechanism	NOUN
cana-1862	416	15	.	.	PUNCT
cana-1862	416	16	"	"	PUNCT
cana-1862	417	1	world	world	PROPN
cana-1862	417	2	journal	journal	NOUN
cana-1862	417	3	of	of	ADP
cana-1862	417	4	advanced	advanced	ADJ
cana-1862	417	5	research	research	NOUN
cana-1862	417	6	and	and	CCONJ
cana-1862	417	7	reviews	review	NOUN
cana-1862	417	8	21.1	21.1	NUM
cana-1862	417	9	(	(	PUNCT
cana-1862	417	10	2024	2024	NUM
cana-1862	417	11	):	):	PUNCT
cana-1862	417	12	2286	2286	NUM
cana-1862	417	13	-	-	SYM
cana-1862	417	14	2295	2295	NUM
cana-1862	417	15	.	.	PUNCT
cana-1862	418	1	[	[	X
cana-1862	418	2	11	11	NUM
cana-1862	418	3	]	]	SYM
cana-1862	418	4	atadoga	atadoga	NOUN
cana-1862	418	5	,	,	PUNCT
cana-1862	418	6	a.	a.	PROPN
cana-1862	418	7	,	,	PUNCT
cana-1862	418	8	sodiya	sodiya	PROPN
cana-1862	418	9	,	,	PUNCT
cana-1862	418	10	e.	e.	PROPN
cana-1862	418	11	o.	o.	PROPN
cana-1862	418	12	,	,	PUNCT
cana-1862	418	13	umoga	umoga	PROPN
cana-1862	418	14	,	,	PUNCT
cana-1862	418	15	u.	u.	PROPN
cana-1862	418	16	j.	j.	PROPN
cana-1862	418	17	,	,	PUNCT
cana-1862	418	18	&	&	CCONJ
cana-1862	418	19	amoo	amoo	PROPN
cana-1862	418	20	,	,	PUNCT
cana-1862	418	21	o.	o.	NOUN
cana-1862	418	22	o.	o.	PROPN
cana-1862	418	23	(	(	PUNCT
cana-1862	418	24	2024	2024	NUM
cana-1862	418	25	)	)	PUNCT
cana-1862	418	26	.	.	PUNCT
cana-1862	419	1	a	a	DET
cana-1862	419	2	comprehensive	comprehensive	ADJ
cana-1862	419	3	review	review	NOUN
cana-1862	419	4	of	of	ADP
cana-1862	419	5	machine	machine	NOUN
cana-1862	419	6	learning	learning	NOUN
cana-1862	419	7	's	's	PART
cana-1862	419	8	role	role	NOUN
cana-1862	419	9	in	in	ADP
cana-1862	419	10	enhancing	enhance	VERB
cana-1862	419	11	network	network	NOUN
cana-1862	419	12	security	security	NOUN
cana-1862	419	13	and	and	CCONJ
cana-1862	419	14	threat	threat	NOUN
cana-1862	419	15	detection	detection	NOUN
cana-1862	419	16	.	.	PUNCT
cana-1862	420	1	world	world	PROPN
cana-1862	420	2	journal	journal	PROPN
cana-1862	420	3	of	of	ADP
cana-1862	420	4	advanced	advanced	ADJ
cana-1862	420	5	research	research	NOUN
cana-1862	420	6	and	and	CCONJ
cana-1862	420	7	reviews	review	NOUN
cana-1862	420	8	,	,	PUNCT
cana-1862	420	9	21(2	21(2	NUM
cana-1862	420	10	)	)	PUNCT
cana-1862	420	11	,	,	PUNCT
cana-1862	420	12	877	877	NUM
cana-1862	420	13	-	-	SYM
cana-1862	420	14	886	886	NUM
cana-1862	420	15	.	.	PUNCT
cana-1862	421	1	[	[	X
cana-1862	421	2	12	12	NUM
cana-1862	421	3	]	]	X
cana-1862	421	4	sejfia	sejfia	PROPN
cana-1862	421	5	,	,	PUNCT
cana-1862	421	6	a.	a.	PROPN
cana-1862	421	7	,	,	PUNCT
cana-1862	421	8	das	das	PROPN
cana-1862	421	9	,	,	PUNCT
cana-1862	421	10	s.	s.	PROPN
cana-1862	421	11	,	,	PUNCT
cana-1862	421	12	shafiq	shafiq	PROPN
cana-1862	421	13	,	,	PUNCT
cana-1862	421	14	s.	s.	PROPN
cana-1862	421	15	,	,	PUNCT
cana-1862	421	16	&	&	CCONJ
cana-1862	421	17	medvidović	medvidović	PROPN
cana-1862	421	18	,	,	PUNCT
cana-1862	421	19	n.	n.	PROPN
cana-1862	421	20	(	(	PUNCT
cana-1862	421	21	2024	2024	NUM
cana-1862	421	22	,	,	PUNCT
cana-1862	421	23	february	february	PROPN
cana-1862	421	24	)	)	PUNCT
cana-1862	421	25	.	.	PUNCT
cana-1862	422	1	toward	toward	ADP
cana-1862	422	2	improved	improve	VERB
cana-1862	422	3	deep	deep	ADJ
cana-1862	422	4	learning	learning	NOUN
cana-1862	422	5	-	-	PUNCT
cana-1862	422	6	based	base	VERB
cana-1862	422	7	vulnerability	vulnerability	NOUN
cana-1862	422	8	detection	detection	NOUN
cana-1862	422	9	.	.	PUNCT
cana-1862	423	1	in	in	ADP
cana-1862	423	2	proceedings	proceeding	NOUN
cana-1862	423	3	of	of	ADP
cana-1862	423	4	the	the	DET
cana-1862	423	5	46th	46th	ADJ
cana-1862	423	6	ieee	ieee	PROPN
cana-1862	423	7	/	/	SYM
cana-1862	423	8	acm	acm	PROPN
cana-1862	423	9	international	international	ADJ
cana-1862	423	10	conference	conference	NOUN
cana-1862	423	11	on	on	ADP
cana-1862	423	12	software	software	NOUN
cana-1862	423	13	engineering	engineering	NOUN
cana-1862	423	14	(	(	PUNCT
cana-1862	423	15	pp	pp	ADJ
cana-1862	423	16	.	.	PUNCT
cana-1862	424	1	1	1	NUM
cana-1862	424	2	-	-	SYM
cana-1862	424	3	12	12	NUM
cana-1862	424	4	)	)	PUNCT
cana-1862	424	5	.	.	PUNCT
cana-1862	425	1	[	[	X
cana-1862	425	2	13	13	NUM
cana-1862	425	3	]	]	SYM
cana-1862	425	4	lad	lad	ADJ
cana-1862	425	5	,	,	PUNCT
cana-1862	425	6	sumit	sumit	PROPN
cana-1862	425	7	.	.	PUNCT
cana-1862	426	1	"	"	PUNCT
cana-1862	426	2	harnessing	harness	VERB
cana-1862	426	3	machine	machine	NOUN
cana-1862	426	4	learning	learning	NOUN
cana-1862	426	5	for	for	ADP
cana-1862	426	6	advanced	advanced	ADJ
cana-1862	426	7	threat	threat	NOUN
cana-1862	426	8	detection	detection	NOUN
cana-1862	426	9	in	in	ADP
cana-1862	426	10	cybersecurity	cybersecurity	NOUN
cana-1862	426	11	.	.	PUNCT
cana-1862	426	12	"	"	PUNCT
cana-1862	427	1	innovative	innovative	ADJ
cana-1862	427	2	computer	computer	NOUN
cana-1862	427	3	sciences	sciences	PROPN
cana-1862	427	4	journal	journal	NOUN
cana-1862	427	5	10.1	10.1	NUM
cana-1862	427	6	(	(	PUNCT
cana-1862	427	7	2024	2024	NUM
cana-1862	427	8	)	)	PUNCT
cana-1862	427	9	.	.	PUNCT
cana-1862	428	1	[	[	X
cana-1862	428	2	14	14	NUM
cana-1862	428	3	]	]	X
cana-1862	428	4	jain	jain	PROPN
cana-1862	428	5	,	,	PUNCT
cana-1862	428	6	vikas	vikas	PROPN
cana-1862	428	7	kumar	kumar	PROPN
cana-1862	428	8	,	,	PUNCT
cana-1862	428	9	and	and	CCONJ
cana-1862	428	10	meenakshi	meenakshi	PROPN
cana-1862	428	11	tripathi	tripathi	PROPN
cana-1862	428	12	.	.	PUNCT
cana-1862	429	1	"	"	PUNCT
cana-1862	429	2	an	an	DET
cana-1862	429	3	integrated	integrated	ADJ
cana-1862	429	4	deep	deep	ADJ
cana-1862	429	5	learning	learning	NOUN
cana-1862	429	6	model	model	NOUN
cana-1862	429	7	for	for	ADP
cana-1862	429	8	ethereum	ethereum	NOUN
cana-1862	429	9	smart	smart	ADJ
cana-1862	429	10	contract	contract	NOUN
cana-1862	429	11	vulnerability	vulnerability	NOUN
cana-1862	429	12	detection	detection	NOUN
cana-1862	429	13	.	.	PUNCT
cana-1862	429	14	"	"	PUNCT
cana-1862	430	1	international	international	ADJ
cana-1862	430	2	journal	journal	NOUN
cana-1862	430	3	of	of	ADP
cana-1862	430	4	information	information	NOUN
cana-1862	430	5	security	security	NOUN
cana-1862	430	6	23.1	23.1	NUM
cana-1862	430	7	(	(	PUNCT
cana-1862	430	8	2024	2024	NUM
cana-1862	430	9	):	):	PUNCT
cana-1862	430	10	557	557	NUM
cana-1862	430	11	-	-	SYM
cana-1862	430	12	575	575	NUM
cana-1862	430	13	.	.	PUNCT
cana-1862	431	1	[	[	X
cana-1862	431	2	15	15	NUM
cana-1862	431	3	]	]	X
cana-1862	431	4	taofeek	taofeek	NOUN
cana-1862	431	5	,	,	PUNCT
cana-1862	431	6	agboola	agboola	PROPN
cana-1862	431	7	olayinka	olayinka	PROPN
cana-1862	431	8	.	.	PUNCT
cana-1862	432	1	"	"	PUNCT
cana-1862	432	2	development	development	NOUN
cana-1862	432	3	of	of	ADP
cana-1862	432	4	a	a	DET
cana-1862	432	5	novel	novel	ADJ
cana-1862	432	6	approach	approach	NOUN
cana-1862	432	7	to	to	ADP
cana-1862	432	8	phishing	phishe	VERB
cana-1862	432	9	detection	detection	NOUN
cana-1862	432	10	using	use	VERB
cana-1862	432	11	machine	machine	NOUN
cana-1862	432	12	learning	learning	NOUN
cana-1862	432	13	.	.	PUNCT
cana-1862	432	14	"	"	PUNCT
cana-1862	433	1	atbu	atbu	NOUN
cana-1862	433	2	journal	journal	NOUN
cana-1862	433	3	of	of	ADP
cana-1862	433	4	science	science	NOUN
cana-1862	433	5	,	,	PUNCT
cana-1862	433	6	technology	technology	NOUN
cana-1862	433	7	and	and	CCONJ
cana-1862	433	8	education	education	NOUN
cana-1862	433	9	12.2	12.2	NUM
cana-1862	433	10	(	(	PUNCT
cana-1862	433	11	2024	2024	NUM
cana-1862	433	12	):	):	PUNCT
cana-1862	433	13	336	336	NUM
cana-1862	433	14	-	-	SYM
cana-1862	433	15	351	351	NUM
cana-1862	433	16	.	.	PUNCT
cana-1862	434	1	[	[	X
cana-1862	434	2	16	16	NUM
cana-1862	434	3	]	]	PUNCT
cana-1862	434	4	alwahedi	alwahedi	PROPN
cana-1862	434	5	,	,	PUNCT
cana-1862	434	6	f.	f.	PROPN
cana-1862	434	7	,	,	PUNCT
cana-1862	434	8	aldhaheri	aldhaheri	PROPN
cana-1862	434	9	,	,	PUNCT
cana-1862	434	10	a.	a.	NOUN
cana-1862	434	11	,	,	PUNCT
cana-1862	434	12	ferrag	ferrag	NOUN
cana-1862	434	13	,	,	PUNCT
cana-1862	434	14	m.	m.	NOUN
cana-1862	434	15	a.	a.	PROPN
cana-1862	434	16	,	,	PUNCT
cana-1862	434	17	battah	battah	PROPN
cana-1862	434	18	,	,	PUNCT
cana-1862	434	19	a.	a.	PROPN
cana-1862	434	20	,	,	PUNCT
cana-1862	434	21	&	&	CCONJ
cana-1862	434	22	tihanyi	tihanyi	PROPN
cana-1862	434	23	,	,	PUNCT
cana-1862	434	24	n.	n.	PROPN
cana-1862	434	25	(	(	PUNCT
cana-1862	434	26	2024	2024	NUM
cana-1862	434	27	)	)	PUNCT
cana-1862	434	28	.	.	PUNCT
cana-1862	435	1	machine	machine	NOUN
cana-1862	435	2	learning	learn	VERB
cana-1862	435	3	techniques	technique	NOUN
cana-1862	435	4	for	for	ADP
cana-1862	435	5	iot	iot	ADJ
cana-1862	435	6	security	security	NOUN
cana-1862	435	7	:	:	PUNCT
cana-1862	435	8	current	current	ADJ
cana-1862	435	9	research	research	NOUN
cana-1862	435	10	and	and	CCONJ
cana-1862	435	11	future	future	ADJ
cana-1862	435	12	vision	vision	NOUN
cana-1862	435	13	with	with	ADP
cana-1862	435	14	generative	generative	ADJ
cana-1862	435	15	ai	ai	NOUN
cana-1862	435	16	and	and	CCONJ
cana-1862	435	17	large	large	ADJ
cana-1862	435	18	language	language	NOUN
cana-1862	435	19	models	model	NOUN
cana-1862	435	20	.	.	PUNCT
cana-1862	436	1	internet	internet	NOUN
cana-1862	436	2	of	of	ADP
cana-1862	436	3	things	thing	NOUN
cana-1862	436	4	and	and	CCONJ
cana-1862	436	5	cyber	cyber	NOUN
cana-1862	436	6	-	-	PUNCT
cana-1862	436	7	physical	physical	ADJ
cana-1862	436	8	systems	system	NOUN
cana-1862	436	9	.	.	PUNCT
cana-1862	437	1	[	[	X
cana-1862	437	2	17	17	NUM
cana-1862	437	3	]	]	X
cana-1862	437	4	liang	liang	PROPN
cana-1862	437	5	,	,	PUNCT
cana-1862	437	6	p.	p.	PROPN
cana-1862	437	7	,	,	PUNCT
cana-1862	437	8	wu	wu	PROPN
cana-1862	437	9	,	,	PUNCT
cana-1862	437	10	y.	y.	PROPN
cana-1862	437	11	,	,	PUNCT
cana-1862	437	12	xu	xu	PROPN
cana-1862	437	13	,	,	PUNCT
cana-1862	437	14	z.	z.	PROPN
cana-1862	437	15	,	,	PUNCT
cana-1862	437	16	xiao	xiao	PROPN
cana-1862	437	17	,	,	PUNCT
cana-1862	437	18	s.	s.	PROPN
cana-1862	437	19	,	,	PUNCT
cana-1862	437	20	&	&	CCONJ
cana-1862	437	21	yuan	yuan	PROPN
cana-1862	437	22	,	,	PUNCT
cana-1862	437	23	j.	j.	PROPN
cana-1862	437	24	(	(	PUNCT
cana-1862	437	25	2024	2024	NUM
cana-1862	437	26	)	)	PUNCT
cana-1862	437	27	.	.	PUNCT
cana-1862	438	1	enhancing	enhance	VERB
cana-1862	438	2	security	security	NOUN
cana-1862	438	3	in	in	ADP
cana-1862	438	4	devops	devop	NOUN
cana-1862	438	5	by	by	ADP
cana-1862	438	6	integrating	integrate	VERB
cana-1862	438	7	artificial	artificial	ADJ
cana-1862	438	8	intelligence	intelligence	NOUN
cana-1862	438	9	and	and	CCONJ
cana-1862	438	10	machine	machine	NOUN
cana-1862	438	11	learning	learning	NOUN
cana-1862	438	12	.	.	PUNCT
cana-1862	439	1	journal	journal	PROPN
cana-1862	439	2	of	of	ADP
cana-1862	439	3	theory	theory	NOUN
cana-1862	439	4	and	and	CCONJ
cana-1862	439	5	practice	practice	NOUN
cana-1862	439	6	of	of	ADP
cana-1862	439	7	engineering	engineering	NOUN
cana-1862	439	8	science	science	NOUN
cana-1862	439	9	,	,	PUNCT
cana-1862	439	10	4(02	4(02	NUM
cana-1862	439	11	)	)	PUNCT
cana-1862	439	12	,	,	PUNCT
cana-1862	439	13	31	31	NUM
cana-1862	439	14	-	-	SYM
cana-1862	439	15	37	37	NUM
cana-1862	439	16	.	.	PUNCT
cana-1862	440	1	communications	communication	NOUN
cana-1862	440	2	on	on	ADP
cana-1862	440	3	applied	apply	VERB
cana-1862	440	4	nonlinear	nonlinear	ADJ
cana-1862	440	5	analysis	analysis	NOUN
cana-1862	440	6	issn	issn	NOUN
cana-1862	440	7	:	:	PUNCT
cana-1862	440	8	1074	1074	NUM
cana-1862	440	9	-	-	PUNCT
cana-1862	440	10	133x	133x	NUM
cana-1862	440	11	vol	vol	NOUN
cana-1862	440	12	32	32	NUM
cana-1862	440	13	no	no	NOUN
cana-1862	440	14	.	.	NOUN
cana-1862	440	15	2	2	NUM
cana-1862	440	16	(	(	PUNCT
cana-1862	440	17	2025	2025	NUM
cana-1862	440	18	)	)	PUNCT
cana-1862	441	1	717	717	NUM
cana-1862	441	2	https://internationalpubls.com	https://internationalpubls.com	X
cana-1862	441	3	[	[	X
cana-1862	441	4	18	18	NUM
cana-1862	441	5	]	]	SYM
cana-1862	441	6	regano	regano	NOUN
cana-1862	441	7	,	,	PUNCT
cana-1862	441	8	leonardo	leonardo	PROPN
cana-1862	441	9	,	,	PUNCT
cana-1862	441	10	daniele	daniele	PROPN
cana-1862	441	11	canavese	canavese	PROPN
cana-1862	441	12	,	,	PUNCT
cana-1862	441	13	and	and	CCONJ
cana-1862	441	14	luca	luca	PROPN
cana-1862	441	15	mannella	mannella	PROPN
cana-1862	441	16	.	.	PUNCT
cana-1862	442	1	"	"	PUNCT
cana-1862	442	2	a	a	DET
cana-1862	442	3	privacy	privacy	NOUN
cana-1862	442	4	-	-	PUNCT
cana-1862	442	5	preserving	preserve	VERB
cana-1862	442	6	approach	approach	NOUN
cana-1862	442	7	for	for	ADP
cana-1862	442	8	vulnerability	vulnerability	NOUN
cana-1862	442	9	scanning	scanning	NOUN
cana-1862	442	10	detection	detection	NOUN
cana-1862	442	11	.	.	PUNCT
cana-1862	442	12	"	"	PUNCT
cana-1862	443	1	proceedings	proceeding	NOUN
cana-1862	443	2	of	of	ADP
cana-1862	443	3	the	the	DET
cana-1862	443	4	italian	italian	ADJ
cana-1862	443	5	conference	conference	NOUN
cana-1862	443	6	on	on	ADP
cana-1862	443	7	cybersecurity	cybersecurity	NOUN
cana-1862	443	8	(	(	PUNCT
cana-1862	443	9	itasec	itasec	PROPN
cana-1862	443	10	2024	2024	NUM
cana-1862	443	11	)	)	PUNCT
cana-1862	443	12	.	.	PUNCT
cana-1862	444	1	ceur	ceur	PROPN
cana-1862	444	2	-	-	PUNCT
cana-1862	444	3	ws	ws	PROPN
cana-1862	444	4	.	.	PUNCT
cana-1862	444	5	2024	2024	NUM
cana-1862	444	6	.	.	PUNCT
cana-1862	445	1	[	[	X
cana-1862	445	2	19	19	NUM
cana-1862	445	3	]	]	X
cana-1862	445	4	arif	arif	PROPN
cana-1862	445	5	,	,	PUNCT
cana-1862	445	6	h.	h.	PROPN
cana-1862	445	7	,	,	PUNCT
cana-1862	445	8	kumar	kumar	PROPN
cana-1862	445	9	,	,	PUNCT
cana-1862	445	10	a.	a.	PROPN
cana-1862	445	11	,	,	PUNCT
cana-1862	445	12	fahad	fahad	PROPN
cana-1862	445	13	,	,	PUNCT
cana-1862	445	14	m.	m.	NOUN
cana-1862	445	15	,	,	PUNCT
cana-1862	445	16	&	&	CCONJ
cana-1862	445	17	hussain	hussain	PROPN
cana-1862	445	18	,	,	PUNCT
cana-1862	445	19	h.	h.	PROPN
cana-1862	445	20	k.	k.	PROPN
cana-1862	445	21	(	(	PUNCT
cana-1862	445	22	2024	2024	NUM
cana-1862	445	23	)	)	PUNCT
cana-1862	445	24	.	.	PUNCT
cana-1862	446	1	future	future	ADJ
cana-1862	446	2	horizons	horizon	NOUN
cana-1862	446	3	:	:	PUNCT
cana-1862	446	4	ai	ai	AUX
cana-1862	446	5	-	-	PUNCT
cana-1862	446	6	enhanced	enhance	VERB
cana-1862	446	7	threat	threat	NOUN
cana-1862	446	8	detection	detection	NOUN
cana-1862	446	9	in	in	ADP
cana-1862	446	10	cloud	cloud	ADJ
cana-1862	446	11	environments	environment	NOUN
cana-1862	446	12	:	:	PUNCT
cana-1862	446	13	unveiling	unveil	VERB
cana-1862	446	14	opportunities	opportunity	NOUN
cana-1862	446	15	for	for	ADP
cana-1862	446	16	research	research	NOUN
cana-1862	446	17	.	.	PUNCT
cana-1862	447	1	international	international	ADJ
cana-1862	447	2	journal	journal	NOUN
cana-1862	447	3	of	of	ADP
cana-1862	447	4	multidisciplinary	multidisciplinary	ADJ
cana-1862	447	5	sciences	science	NOUN
cana-1862	447	6	and	and	CCONJ
cana-1862	447	7	arts	art	NOUN
cana-1862	447	8	,	,	PUNCT
cana-1862	447	9	3(1	3(1	NUM
cana-1862	447	10	)	)	PUNCT
cana-1862	447	11	,	,	PUNCT
cana-1862	447	12	242	242	NUM
cana-1862	447	13	-	-	SYM
cana-1862	447	14	251	251	NUM
cana-1862	447	15	.	.	PUNCT
cana-1862	448	1	[	[	X
cana-1862	448	2	20	20	NUM
cana-1862	448	3	]	]	SYM
cana-1862	448	4	maddireddy	maddireddy	NOUN
cana-1862	448	5	,	,	PUNCT
cana-1862	448	6	bharath	bharath	PROPN
cana-1862	448	7	reddy	reddy	PROPN
cana-1862	448	8	,	,	PUNCT
cana-1862	448	9	and	and	CCONJ
cana-1862	448	10	bhargava	bhargava	PROPN
cana-1862	448	11	reddy	reddy	PROPN
cana-1862	448	12	maddireddy	maddireddy	PROPN
cana-1862	448	13	.	.	PUNCT
cana-1862	449	1	"	"	PUNCT
cana-1862	449	2	advancing	advance	VERB
cana-1862	449	3	threat	threat	NOUN
cana-1862	449	4	detection	detection	NOUN
cana-1862	449	5	:	:	PUNCT
cana-1862	449	6	utilizing	utilize	VERB
cana-1862	449	7	deep	deep	ADJ
cana-1862	449	8	learning	learning	NOUN
cana-1862	449	9	models	model	NOUN
cana-1862	449	10	for	for	ADP
cana-1862	449	11	enhanced	enhanced	ADJ
cana-1862	449	12	cybersecurity	cybersecurity	NOUN
cana-1862	449	13	protocols	protocol	NOUN
cana-1862	449	14	.	.	PUNCT
cana-1862	449	15	"	"	PUNCT
cana-1862	450	1	revista	revista	PROPN
cana-1862	450	2	espanola	espanola	PROPN
cana-1862	450	3	de	de	PROPN
cana-1862	450	4	documentacion	documentacion	PROPN
cana-1862	450	5	cientifica	cientifica	PROPN
cana-1862	450	6	18.02	18.02	NUM
cana-1862	450	7	(	(	PUNCT
cana-1862	450	8	2024	2024	NUM
cana-1862	450	9	):	):	PUNCT
cana-1862	450	10	325	325	NUM
cana-1862	450	11	-	-	SYM
cana-1862	450	12	355	355	NUM
cana-1862	450	13	.	.	PUNCT
cana-1862	451	1	[	[	X
cana-1862	451	2	21	21	NUM
cana-1862	451	3	]	]	X
cana-1862	451	4	ceschin	ceschin	PROPN
cana-1862	451	5	,	,	PUNCT
cana-1862	451	6	f.	f.	PROPN
cana-1862	451	7	,	,	PUNCT
cana-1862	451	8	botacin	botacin	PROPN
cana-1862	451	9	,	,	PUNCT
cana-1862	451	10	m.	m.	NOUN
cana-1862	451	11	,	,	PUNCT
cana-1862	451	12	bifet	bifet	PROPN
cana-1862	451	13	,	,	PUNCT
cana-1862	451	14	a.	a.	NOUN
cana-1862	451	15	,	,	PUNCT
cana-1862	451	16	pfahringer	pfahringer	NOUN
cana-1862	451	17	,	,	PUNCT
cana-1862	451	18	b.	b.	PROPN
cana-1862	451	19	,	,	PUNCT
cana-1862	451	20	oliveira	oliveira	PROPN
cana-1862	451	21	,	,	PUNCT
cana-1862	451	22	l.	l.	PROPN
cana-1862	451	23	s.	s.	PROPN
cana-1862	451	24	,	,	PUNCT
cana-1862	451	25	gomes	gomes	PROPN
cana-1862	451	26	,	,	PUNCT
cana-1862	451	27	h.	h.	PROPN
cana-1862	451	28	m.	m.	PROPN
cana-1862	451	29	,	,	PUNCT
cana-1862	451	30	&	&	CCONJ
cana-1862	451	31	grégio	grégio	PROPN
cana-1862	451	32	,	,	PUNCT
cana-1862	451	33	a.	a.	NOUN
cana-1862	451	34	(	(	PUNCT
cana-1862	451	35	2024	2024	NUM
cana-1862	451	36	)	)	PUNCT
cana-1862	451	37	.	.	PUNCT
cana-1862	452	1	machine	machine	NOUN
cana-1862	452	2	learning	learning	NOUN
cana-1862	452	3	(	(	PUNCT
cana-1862	452	4	in	in	ADP
cana-1862	452	5	)	)	PUNCT
cana-1862	452	6	security	security	NOUN
cana-1862	452	7	:	:	PUNCT
cana-1862	452	8	a	a	DET
cana-1862	452	9	stream	stream	NOUN
cana-1862	452	10	of	of	ADP
cana-1862	452	11	problems	problem	NOUN
cana-1862	452	12	.	.	PUNCT
cana-1862	453	1	digital	digital	ADJ
cana-1862	453	2	threats	threat	NOUN
cana-1862	453	3	:	:	PUNCT
cana-1862	453	4	research	research	NOUN
cana-1862	453	5	and	and	CCONJ
cana-1862	453	6	practice	practice	NOUN
cana-1862	453	7	,	,	PUNCT
cana-1862	453	8	5(1	5(1	NUM
cana-1862	453	9	)	)	PUNCT
cana-1862	453	10	,	,	PUNCT
cana-1862	453	11	1	1	NUM
cana-1862	453	12	-	-	SYM
cana-1862	453	13	32	32	NUM
cana-1862	453	14	.	.	PUNCT
cana-1862	454	1	[	[	X
cana-1862	454	2	22	22	NUM
cana-1862	454	3	]	]	PUNCT
cana-1862	454	4	steenhoek	steenhoek	VERB
cana-1862	454	5	,	,	PUNCT
cana-1862	454	6	benjamin	benjamin	PROPN
cana-1862	454	7	,	,	PUNCT
cana-1862	454	8	hongyang	hongyang	PROPN
cana-1862	454	9	gao	gao	PROPN
cana-1862	454	10	,	,	PUNCT
cana-1862	454	11	and	and	CCONJ
cana-1862	454	12	wei	wei	PROPN
cana-1862	454	13	le	le	PROPN
cana-1862	454	14	.	.	PUNCT
cana-1862	455	1	"	"	PUNCT
cana-1862	455	2	dataflow	dataflow	ADJ
cana-1862	455	3	analysis	analysis	NOUN
cana-1862	455	4	-	-	PUNCT
cana-1862	455	5	inspired	inspire	VERB
cana-1862	455	6	deep	deep	ADJ
cana-1862	455	7	learning	learning	NOUN
cana-1862	455	8	for	for	ADP
cana-1862	455	9	efficient	efficient	ADJ
cana-1862	455	10	vulnerability	vulnerability	NOUN
cana-1862	455	11	detection	detection	NOUN
cana-1862	455	12	.	.	PUNCT
cana-1862	455	13	"	"	PUNCT
cana-1862	456	1	proceedings	proceeding	NOUN
cana-1862	456	2	of	of	ADP
cana-1862	456	3	the	the	DET
cana-1862	456	4	46th	46th	ADJ
cana-1862	456	5	ieee	ieee	PROPN
cana-1862	456	6	/	/	SYM
cana-1862	456	7	acm	acm	PROPN
cana-1862	456	8	international	international	ADJ
cana-1862	456	9	conference	conference	NOUN
cana-1862	456	10	on	on	ADP
cana-1862	456	11	software	software	NOUN
cana-1862	456	12	engineering	engineering	NOUN
cana-1862	456	13	.	.	PUNCT
cana-1862	457	1	2024	2024	NUM
cana-1862	457	2	.	.	PUNCT
cana-1862	458	1	[	[	X
cana-1862	458	2	23	23	NUM
cana-1862	458	3	]	]	X
cana-1862	458	4	seas	sea	NOUN
cana-1862	458	5	,	,	PUNCT
cana-1862	458	6	c.	c.	PROPN
cana-1862	458	7	,	,	PUNCT
cana-1862	458	8	fitzpatrick	fitzpatrick	PROPN
cana-1862	458	9	,	,	PUNCT
cana-1862	458	10	g.	g.	PROPN
cana-1862	458	11	,	,	PUNCT
cana-1862	458	12	hamilton	hamilton	PROPN
cana-1862	458	13	,	,	PUNCT
cana-1862	458	14	j.	j.	PROPN
cana-1862	458	15	a.	a.	PROPN
cana-1862	458	16	,	,	PUNCT
cana-1862	458	17	&	&	CCONJ
cana-1862	458	18	carlisle	carlisle	PROPN
cana-1862	458	19	,	,	PUNCT
cana-1862	458	20	m.	m.	NOUN
cana-1862	458	21	c.	c.	PROPN
cana-1862	458	22	(	(	PUNCT
cana-1862	458	23	2024	2024	NUM
cana-1862	458	24	,	,	PUNCT
cana-1862	458	25	january	january	PROPN
cana-1862	458	26	)	)	PUNCT
cana-1862	458	27	.	.	PUNCT
cana-1862	459	1	automated	automate	VERB
cana-1862	459	2	vulnerability	vulnerability	NOUN
cana-1862	459	3	detection	detection	NOUN
cana-1862	459	4	in	in	ADP
cana-1862	459	5	source	source	NOUN
cana-1862	459	6	code	code	NOUN
cana-1862	459	7	using	use	VERB
cana-1862	459	8	deep	deep	ADJ
cana-1862	459	9	representation	representation	NOUN
cana-1862	459	10	learning	learning	NOUN
cana-1862	459	11	.	.	PUNCT
cana-1862	460	1	in	in	ADP
cana-1862	460	2	2024	2024	NUM
cana-1862	460	3	ieee	ieee	NOUN
cana-1862	460	4	14th	14th	ADJ
cana-1862	460	5	annual	annual	ADJ
cana-1862	460	6	computing	computing	NOUN
cana-1862	460	7	and	and	CCONJ
cana-1862	460	8	communication	communication	NOUN
cana-1862	460	9	workshop	workshop	NOUN
cana-1862	460	10	and	and	CCONJ
cana-1862	460	11	conference	conference	NOUN
cana-1862	460	12	(	(	PUNCT
cana-1862	460	13	ccwc	ccwc	PROPN
cana-1862	460	14	)	)	PUNCT
cana-1862	460	15	(	(	PUNCT
cana-1862	460	16	pp	pp	ADP
cana-1862	460	17	.	.	PUNCT
cana-1862	460	18	0484	0484	NOUN
cana-1862	460	19	-	-	SYM
cana-1862	460	20	0490	0490	NUM
cana-1862	460	21	)	)	PUNCT
cana-1862	460	22	.	.	PUNCT
cana-1862	461	1	ieee	ieee	PROPN
cana-1862	461	2	.	.	PUNCT
cana-1862	462	1	[	[	X
cana-1862	462	2	24	24	NUM
cana-1862	462	3	]	]	PUNCT
cana-1862	462	4	mohammed	mohammed	PROPN
cana-1862	462	5	,	,	PUNCT
cana-1862	462	6	ahmed	ahmed	PROPN
cana-1862	462	7	.	.	PUNCT
cana-1862	463	1	"	"	PUNCT
cana-1862	463	2	the	the	DET
cana-1862	463	3	web	web	NOUN
cana-1862	463	4	technology	technology	NOUN
cana-1862	463	5	and	and	CCONJ
cana-1862	463	6	cloud	cloud	NOUN
cana-1862	463	7	computing	compute	VERB
cana-1862	463	8	security	security	NOUN
cana-1862	463	9	based	base	VERB
cana-1862	463	10	machine	machine	NOUN
cana-1862	463	11	learning	learn	VERB
cana-1862	463	12	algorithms	algorithm	NOUN
cana-1862	463	13	for	for	ADP
cana-1862	463	14	detect	detect	NOUN
cana-1862	463	15	ddos	ddos	NOUN
cana-1862	463	16	attacks	attack	NOUN
cana-1862	463	17	.	.	PUNCT
cana-1862	463	18	"	"	PUNCT
cana-1862	464	1	journal	journal	NOUN
cana-1862	464	2	of	of	ADP
cana-1862	464	3	information	information	NOUN
cana-1862	464	4	technology	technology	NOUN
cana-1862	464	5	and	and	CCONJ
cana-1862	464	6	informatics	informatic	NOUN
cana-1862	464	7	3.1	3.1	NUM
cana-1862	464	8	(	(	PUNCT
cana-1862	464	9	2024	2024	NUM
cana-1862	464	10	)	)	PUNCT
cana-1862	464	11	.	.	PUNCT
cana-1862	465	1	[	[	X
cana-1862	465	2	25	25	NUM
cana-1862	465	3	]	]	X
cana-1862	465	4	wang	wang	PROPN
cana-1862	465	5	,	,	PUNCT
cana-1862	465	6	r.	r.	PROPN
cana-1862	465	7	,	,	PUNCT
cana-1862	465	8	xu	xu	PROPN
cana-1862	465	9	,	,	PUNCT
cana-1862	465	10	s.	s.	PROPN
cana-1862	465	11	,	,	PUNCT
cana-1862	465	12	ji	ji	PROPN
cana-1862	465	13	,	,	PUNCT
cana-1862	465	14	x.	x.	PROPN
cana-1862	465	15	,	,	PUNCT
cana-1862	465	16	tian	tian	PROPN
cana-1862	465	17	,	,	PUNCT
cana-1862	465	18	y.	y.	PROPN
cana-1862	465	19	,	,	PUNCT
cana-1862	465	20	gong	gong	PROPN
cana-1862	465	21	,	,	PUNCT
cana-1862	465	22	l.	l.	PROPN
cana-1862	465	23	,	,	PUNCT
cana-1862	465	24	&	&	CCONJ
cana-1862	465	25	wang	wang	PROPN
cana-1862	465	26	,	,	PUNCT
cana-1862	465	27	k.	k.	PROPN
cana-1862	465	28	(	(	PUNCT
cana-1862	465	29	2024	2024	NUM
cana-1862	465	30	)	)	PUNCT
cana-1862	465	31	.	.	PUNCT
cana-1862	466	1	an	an	DET
cana-1862	466	2	extensive	extensive	ADJ
cana-1862	466	3	study	study	NOUN
cana-1862	466	4	of	of	ADP
cana-1862	466	5	the	the	DET
cana-1862	466	6	effects	effect	NOUN
cana-1862	466	7	of	of	ADP
cana-1862	466	8	different	different	ADJ
cana-1862	466	9	deep	deep	ADJ
cana-1862	466	10	learning	learning	NOUN
cana-1862	466	11	models	model	NOUN
cana-1862	466	12	on	on	ADP
cana-1862	466	13	code	code	NOUN
cana-1862	466	14	vulnerability	vulnerability	NOUN
cana-1862	466	15	detection	detection	NOUN
cana-1862	466	16	in	in	ADP
cana-1862	466	17	python	python	PROPN
cana-1862	466	18	code	code	PROPN
cana-1862	466	19	.	.	PUNCT
cana-1862	467	1	automated	automate	VERB
cana-1862	467	2	software	software	NOUN
cana-1862	467	3	engineering	engineering	NOUN
cana-1862	467	4	,	,	PUNCT
cana-1862	467	5	31(1	31(1	NUM
cana-1862	467	6	)	)	PUNCT
cana-1862	467	7	,	,	PUNCT
cana-1862	467	8	15	15	NUM
cana-1862	467	9	.	.	PUNCT
cana-1862	468	1	[	[	X
cana-1862	468	2	26	26	NUM
cana-1862	468	3	]	]	X
cana-1862	468	4	reddy	reddy	PROPN
cana-1862	468	5	,	,	PUNCT
cana-1862	468	6	premkumar	premkumar	PROPN
cana-1862	468	7	,	,	PUNCT
cana-1862	468	8	yemi	yemi	PROPN
cana-1862	468	9	adetuwo	adetuwo	PROPN
cana-1862	468	10	,	,	PUNCT
cana-1862	468	11	and	and	CCONJ
cana-1862	468	12	anil	anil	PROPN
cana-1862	468	13	kumar	kumar	PROPN
cana-1862	468	14	jakkani	jakkani	PROPN
cana-1862	468	15	.	.	PUNCT
cana-1862	469	1	"	"	PUNCT
cana-1862	469	2	implementation	implementation	NOUN
cana-1862	469	3	of	of	ADP
cana-1862	469	4	machine	machine	NOUN
cana-1862	469	5	learning	learn	VERB
cana-1862	469	6	techniques	technique	NOUN
cana-1862	469	7	for	for	ADP
cana-1862	469	8	cloud	cloud	ADJ
cana-1862	469	9	security	security	NOUN
cana-1862	469	10	in	in	ADP
cana-1862	469	11	detection	detection	NOUN
cana-1862	469	12	of	of	ADP
cana-1862	469	13	ddos	ddos	NOUN
cana-1862	469	14	attacks	attack	NOUN
cana-1862	469	15	.	.	PUNCT
cana-1862	469	16	"	"	PUNCT
cana-1862	470	1	international	international	ADJ
cana-1862	470	2	journal	journal	NOUN
cana-1862	470	3	of	of	ADP
cana-1862	470	4	computer	computer	NOUN
cana-1862	470	5	engineering	engineering	NOUN
cana-1862	470	6	and	and	CCONJ
cana-1862	470	7	technology(ijcet	technology(ijcet	PROPN
cana-1862	470	8	)	)	PUNCT
cana-1862	470	9	15.2	15.2	NUM
cana-1862	470	10	(	(	PUNCT
cana-1862	470	11	2024	2024	NUM
cana-1862	470	12	)	)	PUNCT
cana-1862	470	13	.	.	PUNCT
cana-1862	471	1	[	[	X
cana-1862	471	2	27	27	NUM
cana-1862	471	3	]	]	X
cana-1862	471	4	sun	sun	PROPN
cana-1862	471	5	,	,	PUNCT
cana-1862	471	6	h.	h.	PROPN
cana-1862	471	7	,	,	PUNCT
cana-1862	471	8	cui	cui	PROPN
cana-1862	471	9	,	,	PUNCT
cana-1862	471	10	l.	l.	PROPN
cana-1862	471	11	,	,	PUNCT
cana-1862	471	12	li	li	PROPN
cana-1862	471	13	,	,	PUNCT
cana-1862	471	14	l.	l.	PROPN
cana-1862	471	15	,	,	PUNCT
cana-1862	471	16	ding	ding	PROPN
cana-1862	471	17	,	,	PUNCT
cana-1862	471	18	z.	z.	PROPN
cana-1862	471	19	,	,	PUNCT
cana-1862	471	20	li	li	PROPN
cana-1862	471	21	,	,	PUNCT
cana-1862	471	22	s.	s.	PROPN
cana-1862	471	23	,	,	PUNCT
cana-1862	471	24	hao	hao	PROPN
cana-1862	471	25	,	,	PUNCT
cana-1862	471	26	z.	z.	PROPN
cana-1862	471	27	,	,	PUNCT
cana-1862	471	28	&	&	CCONJ
cana-1862	471	29	zhu	zhu	PROPN
cana-1862	471	30	,	,	PUNCT
cana-1862	471	31	h.	h.	PROPN
cana-1862	471	32	(	(	PUNCT
cana-1862	471	33	2024	2024	NUM
cana-1862	471	34	)	)	PUNCT
cana-1862	471	35	.	.	PUNCT
cana-1862	472	1	vdtriplet	vdtriplet	NOUN
cana-1862	472	2	:	:	PUNCT
cana-1862	473	1	vulnerability	vulnerability	NOUN
cana-1862	473	2	detection	detection	NOUN
cana-1862	473	3	with	with	ADP
cana-1862	473	4	graph	graph	NOUN
cana-1862	473	5	semantics	semantic	NOUN
cana-1862	473	6	using	use	VERB
cana-1862	473	7	triplet	triplet	NOUN
cana-1862	473	8	model	model	NOUN
cana-1862	473	9	.	.	PUNCT
cana-1862	474	1	computers	computer	NOUN
cana-1862	474	2	&	&	CCONJ
cana-1862	474	3	security	security	NOUN
cana-1862	474	4	,	,	PUNCT
cana-1862	474	5	139	139	NUM
cana-1862	474	6	,	,	PUNCT
cana-1862	474	7	103732	103732	NUM
cana-1862	474	8	.	.	PUNCT