id	sid	tid	token	lemma	pos
cana-803	1	1	communications	communication	NOUN
cana-803	1	2	on	on	ADP
cana-803	1	3	applied	apply	VERB
cana-803	1	4	nonlinear	nonlinear	ADJ
cana-803	1	5	analysis	analysis	NOUN
cana-803	1	6	issn	issn	NOUN
cana-803	1	7	:	:	PUNCT
cana-803	1	8	1074	1074	NUM
cana-803	1	9	-	-	PUNCT
cana-803	1	10	133x	133x	NUM
cana-803	1	11	vol	vol	NOUN
cana-803	1	12	31	31	NUM
cana-803	1	13	no	no	NOUN
cana-803	1	14	.	.	PUNCT
cana-803	2	1	3s	3s	NUM
cana-803	2	2	(	(	PUNCT
cana-803	2	3	2024	2024	NUM
cana-803	2	4	)	)	PUNCT
cana-803	2	5	487	487	NUM
cana-803	2	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-803	2	7	stochastic	stochastic	NOUN
cana-803	2	8	models	model	NOUN
cana-803	2	9	for	for	ADP
cana-803	2	10	cyber	cyber	NOUN
cana-803	2	11	attack	attack	NOUN
cana-803	2	12	detection	detection	NOUN
cana-803	2	13	and	and	CCONJ
cana-803	2	14	response	response	NOUN
cana-803	2	15	:	:	PUNCT
cana-803	2	16	a	a	DET
cana-803	2	17	mathematical	mathematical	ADJ
cana-803	2	18	approach	approach	NOUN
cana-803	2	19	to	to	ADP
cana-803	2	20	intrusion	intrusion	NOUN
cana-803	2	21	detection	detection	NOUN
cana-803	2	22	systems	system	NOUN
cana-803	2	23	rohit	rohit	VERB
cana-803	2	24	krishna	krishna	PROPN
cana-803	2	25	murti1	murti1	PROPN
cana-803	2	26	,	,	PUNCT
cana-803	2	27	vaibhav	vaibhav	VERB
cana-803	2	28	vijay	vijay	PROPN
cana-803	2	29	joshi2	joshi2	PROPN
cana-803	2	30	,	,	PUNCT
cana-803	2	31	rohini	rohini	PROPN
cana-803	2	32	wagh3	wagh3	PROPN
cana-803	2	33	,	,	PUNCT
cana-803	2	34	manisha	manisha	PROPN
cana-803	2	35	sagar	sagar	PROPN
cana-803	2	36	jangale4	jangale4	PROPN
cana-803	2	37	,	,	PUNCT
cana-803	2	38	ashvini	ashvini	VERB
cana-803	2	39	chandrakant	chandrakant	PROPN
cana-803	2	40	chaudhari5	chaudhari5	NOUN
cana-803	2	41	,	,	PUNCT
cana-803	2	42	madhavi	madhavi	PROPN
cana-803	2	43	wagh6	wagh6	PROPN
cana-803	3	1	1assistant	1assistant	NUM
cana-803	3	2	professor	professor	NOUN
cana-803	3	3	,	,	PUNCT
cana-803	3	4	department	department	NOUN
cana-803	3	5	of	of	ADP
cana-803	3	6	computer	computer	NOUN
cana-803	3	7	engineering	engineering	NOUN
cana-803	3	8	,	,	PUNCT
cana-803	3	9	sandip	sandip	PROPN
cana-803	3	10	university	university	NOUN
cana-803	3	11	,	,	PUNCT
cana-803	3	12	sijoul	sijoul	PROPN
cana-803	3	13	,	,	PUNCT
cana-803	3	14	bihar	bihar	NOUN
cana-803	3	15	,	,	PUNCT
cana-803	3	16	india	india	PROPN
cana-803	3	17	.	.	PUNCT
cana-803	4	1	rohit.murti@sandipuniversity.edu.in	rohit.murti@sandipuniversity.edu.in	PROPN
cana-803	4	2	2assistant	2assistant	PROPN
cana-803	4	3	professor	professor	NOUN
cana-803	4	4	,	,	PUNCT
cana-803	4	5	department	department	NOUN
cana-803	4	6	of	of	ADP
cana-803	4	7	electronics	electronic	NOUN
cana-803	4	8	and	and	CCONJ
cana-803	4	9	telecommunication	telecommunication	NOUN
cana-803	4	10	,	,	PUNCT
cana-803	4	11	sandip	sandip	PROPN
cana-803	4	12	institute	institute	PROPN
cana-803	4	13	of	of	ADP
cana-803	4	14	technology	technology	PROPN
cana-803	4	15	&	&	CCONJ
cana-803	4	16	research	research	PROPN
cana-803	4	17	centre	centre	NOUN
cana-803	4	18	,	,	PUNCT
cana-803	4	19	nashik	nashik	PROPN
cana-803	4	20	maharashtra	maharashtra	PROPN
cana-803	4	21	,	,	PUNCT
cana-803	4	22	india	india	PROPN
cana-803	4	23	.	.	PUNCT
cana-803	5	1	vaibhav.joshi@sitrc.org	vaibhav.joshi@sitrc.org	PROPN
cana-803	5	2	3assistant	3assistant	PROPN
cana-803	5	3	professor	professor	NOUN
cana-803	5	4	,	,	PUNCT
cana-803	5	5	department	department	NOUN
cana-803	5	6	of	of	ADP
cana-803	5	7	electronics	electronic	NOUN
cana-803	5	8	and	and	CCONJ
cana-803	5	9	telecommunication	telecommunication	NOUN
cana-803	5	10	,	,	PUNCT
cana-803	5	11	sandip	sandip	PROPN
cana-803	5	12	university	university	NOUN
cana-803	5	13	nashik	nashik	PROPN
cana-803	5	14	,	,	PUNCT
cana-803	5	15	maharashtra	maharashtra	PROPN
cana-803	5	16	,	,	PUNCT
cana-803	5	17	india	india	PROPN
cana-803	5	18	.	.	PUNCT
cana-803	6	1	rohini.wagh@sandipuniversity.edu.in	rohini.wagh@sandipuniversity.edu.in	PROPN
cana-803	6	2	4assistant	4assistant	NUM
cana-803	6	3	professor	professor	NOUN
cana-803	6	4	,	,	PUNCT
cana-803	6	5	department	department	NOUN
cana-803	6	6	of	of	ADP
cana-803	6	7	electronics	electronic	NOUN
cana-803	6	8	and	and	CCONJ
cana-803	6	9	telecommunication	telecommunication	NOUN
cana-803	6	10	,	,	PUNCT
cana-803	6	11	sandip	sandip	PROPN
cana-803	6	12	institute	institute	PROPN
cana-803	6	13	of	of	ADP
cana-803	6	14	engineering	engineering	PROPN
cana-803	6	15	&	&	CCONJ
cana-803	6	16	management	management	NOUN
cana-803	6	17	,	,	PUNCT
cana-803	6	18	nashik	nashik	PROPN
cana-803	6	19	,	,	PUNCT
cana-803	6	20	maharashtra	maharashtra	PROPN
cana-803	6	21	,	,	PUNCT
cana-803	6	22	india	india	PROPN
cana-803	6	23	.	.	PUNCT
cana-803	7	1	manisha.jangale@siem.org.in	manisha.jangale@siem.org.in	PROPN
cana-803	7	2	5assistant	5assistant	NUM
cana-803	7	3	professor	professor	NOUN
cana-803	7	4	,	,	PUNCT
cana-803	7	5	department	department	NOUN
cana-803	7	6	of	of	ADP
cana-803	7	7	electrical	electrical	ADJ
cana-803	7	8	engineering	engineering	NOUN
cana-803	7	9	,	,	PUNCT
cana-803	7	10	sandip	sandip	PROPN
cana-803	7	11	institute	institute	PROPN
cana-803	7	12	of	of	ADP
cana-803	7	13	technology	technology	PROPN
cana-803	7	14	&	&	CCONJ
cana-803	7	15	research	research	PROPN
cana-803	7	16	centre	centre	NOUN
cana-803	7	17	,	,	PUNCT
cana-803	7	18	nashik	nashik	PROPN
cana-803	7	19	maharashtra	maharashtra	PROPN
cana-803	7	20	,	,	PUNCT
cana-803	7	21	india	india	PROPN
cana-803	7	22	.	.	PUNCT
cana-803	8	1	ashwini.chaudhari@sitrc.org	ashwini.chaudhari@sitrc.org	X
cana-803	8	2	6assistant	6assistant	NUM
cana-803	8	3	professor	professor	NOUN
cana-803	8	4	,	,	PUNCT
cana-803	8	5	school	school	NOUN
cana-803	8	6	of	of	ADP
cana-803	8	7	science	science	NOUN
cana-803	8	8	,	,	PUNCT
cana-803	8	9	sandip	sandip	PROPN
cana-803	8	10	university	university	PROPN
cana-803	8	11	nashik	nashik	PROPN
cana-803	8	12	,	,	PUNCT
cana-803	8	13	maharashtra	maharashtra	PROPN
cana-803	8	14	,	,	PUNCT
cana-803	8	15	india	india	PROPN
cana-803	8	16	.	.	PUNCT
cana-803	9	1	madhavi.wagh@sandipuniversity.edu.in	madhavi.wagh@sandipuniversity.edu.in	PROPN
cana-803	9	2	.	.	PUNCT
cana-803	9	3	article	article	PROPN
cana-803	9	4	history	history	NOUN
cana-803	9	5	:	:	PUNCT
cana-803	9	6	received	receive	VERB
cana-803	9	7	:	:	PUNCT
cana-803	9	8	15	15	NUM
cana-803	9	9	-	-	PUNCT
cana-803	9	10	04	04	NUM
cana-803	9	11	-	-	PUNCT
cana-803	9	12	2024	2024	NUM
cana-803	9	13	revised	revise	VERB
cana-803	9	14	:	:	PUNCT
cana-803	9	15	30	30	NUM
cana-803	9	16	-	-	SYM
cana-803	9	17	05	05	NUM
cana-803	9	18	-	-	PUNCT
cana-803	9	19	2024	2024	NUM
cana-803	9	20	accepted	accept	VERB
cana-803	9	21	:	:	PUNCT
cana-803	9	22	14	14	NUM
cana-803	9	23	-	-	SYM
cana-803	9	24	06	06	NUM
cana-803	9	25	-	-	PUNCT
cana-803	9	26	2024	2024	NUM
cana-803	9	27	abstract	abstract	NOUN
cana-803	9	28	:	:	PUNCT
cana-803	9	29	cyberattacks	cyberattack	NOUN
cana-803	9	30	are	be	AUX
cana-803	9	31	a	a	DET
cana-803	9	32	big	big	ADJ
cana-803	9	33	problem	problem	NOUN
cana-803	9	34	in	in	ADP
cana-803	9	35	today	today	NOUN
cana-803	9	36	's	's	PART
cana-803	9	37	world	world	NOUN
cana-803	9	38	because	because	SCONJ
cana-803	9	39	everything	everything	PRON
cana-803	9	40	is	be	AUX
cana-803	9	41	linked	link	VERB
cana-803	9	42	online	online	ADV
cana-803	9	43	.	.	PUNCT
cana-803	10	1	they	they	PRON
cana-803	10	2	can	can	AUX
cana-803	10	3	damage	damage	VERB
cana-803	10	4	the	the	DET
cana-803	10	5	security	security	NOUN
cana-803	10	6	,	,	PUNCT
cana-803	10	7	privacy	privacy	NOUN
cana-803	10	8	,	,	PUNCT
cana-803	10	9	and	and	CCONJ
cana-803	10	10	access	access	NOUN
cana-803	10	11	of	of	ADP
cana-803	10	12	private	private	ADJ
cana-803	10	13	information	information	NOUN
cana-803	10	14	.	.	PUNCT
cana-803	11	1	intrusion	intrusion	NOUN
cana-803	11	2	detection	detection	NOUN
cana-803	11	3	systems	system	NOUN
cana-803	11	4	(	(	PUNCT
cana-803	11	5	ids	id	NOUN
cana-803	11	6	)	)	PUNCT
cana-803	11	7	are	be	AUX
cana-803	11	8	very	very	ADV
cana-803	11	9	important	important	ADJ
cana-803	11	10	for	for	ADP
cana-803	11	11	keeping	keep	VERB
cana-803	11	12	networks	network	NOUN
cana-803	11	13	safe	safe	ADJ
cana-803	11	14	because	because	SCONJ
cana-803	11	15	they	they	PRON
cana-803	11	16	quickly	quickly	ADV
cana-803	11	17	find	find	VERB
cana-803	11	18	and	and	CCONJ
cana-803	11	19	stop	stop	VERB
cana-803	11	20	harmful	harmful	ADJ
cana-803	11	21	activity	activity	NOUN
cana-803	11	22	.	.	PUNCT
cana-803	12	1	to	to	PART
cana-803	12	2	successfully	successfully	ADV
cana-803	12	3	find	find	VERB
cana-803	12	4	and	and	CCONJ
cana-803	12	5	stop	stop	VERB
cana-803	12	6	attacks	attack	NOUN
cana-803	12	7	,	,	PUNCT
cana-803	12	8	however	however	ADV
cana-803	12	9	,	,	PUNCT
cana-803	12	10	we	we	PRON
cana-803	12	11	need	need	VERB
cana-803	12	12	more	more	ADV
cana-803	12	13	advanced	advanced	ADJ
cana-803	12	14	methods	method	NOUN
cana-803	12	15	because	because	SCONJ
cana-803	12	16	online	online	ADJ
cana-803	12	17	risks	risk	NOUN
cana-803	12	18	are	be	AUX
cana-803	12	19	always	always	ADV
cana-803	12	20	changing	change	VERB
cana-803	12	21	.	.	PUNCT
cana-803	13	1	this	this	DET
cana-803	13	2	paper	paper	NOUN
cana-803	13	3	suggests	suggest	VERB
cana-803	13	4	a	a	DET
cana-803	13	5	new	new	ADJ
cana-803	13	6	mathematical	mathematical	ADJ
cana-803	13	7	approach	approach	NOUN
cana-803	13	8	for	for	ADP
cana-803	13	9	improving	improve	VERB
cana-803	13	10	ids	id	NOUN
cana-803	13	11	that	that	PRON
cana-803	13	12	is	be	AUX
cana-803	13	13	based	base	VERB
cana-803	13	14	on	on	ADP
cana-803	13	15	random	random	ADJ
cana-803	13	16	models	model	NOUN
cana-803	13	17	.	.	PUNCT
cana-803	14	1	traditional	traditional	ADJ
cana-803	14	2	ways	way	NOUN
cana-803	14	3	of	of	ADP
cana-803	14	4	finding	find	VERB
cana-803	14	5	intrusions	intrusion	NOUN
cana-803	14	6	often	often	ADV
cana-803	14	7	use	use	VERB
cana-803	14	8	signatureor	signatureor	NOUN
cana-803	14	9	anomaly	anomaly	NOUN
cana-803	14	10	-	-	PUNCT
cana-803	14	11	based	base	VERB
cana-803	14	12	methods	method	NOUN
cana-803	14	13	,	,	PUNCT
cana-803	14	14	which	which	PRON
cana-803	14	15	might	might	AUX
cana-803	14	16	not	not	PART
cana-803	14	17	be	be	AUX
cana-803	14	18	able	able	ADJ
cana-803	14	19	to	to	PART
cana-803	14	20	keep	keep	VERB
cana-803	14	21	up	up	ADP
cana-803	14	22	with	with	ADP
cana-803	14	23	how	how	SCONJ
cana-803	14	24	attackers	attacker	NOUN
cana-803	14	25	'	'	PART
cana-803	14	26	strategies	strategy	NOUN
cana-803	14	27	change	change	VERB
cana-803	14	28	all	all	DET
cana-803	14	29	the	the	DET
cana-803	14	30	time	time	NOUN
cana-803	14	31	.	.	PUNCT
cana-803	15	1	by	by	ADP
cana-803	15	2	using	use	VERB
cana-803	15	3	random	random	ADJ
cana-803	15	4	processes	process	NOUN
cana-803	15	5	,	,	PUNCT
cana-803	15	6	our	our	PRON
cana-803	15	7	method	method	NOUN
cana-803	15	8	provides	provide	VERB
cana-803	15	9	a	a	DET
cana-803	15	10	more	more	ADV
cana-803	15	11	flexible	flexible	ADJ
cana-803	15	12	and	and	CCONJ
cana-803	15	13	adaptable	adaptable	ADJ
cana-803	15	14	way	way	NOUN
cana-803	15	15	to	to	PART
cana-803	15	16	find	find	VERB
cana-803	15	17	online	online	ADJ
cana-803	15	18	threats	threat	NOUN
cana-803	15	19	.	.	PUNCT
cana-803	16	1	ids	id	NOUN
cana-803	16	2	can	can	AUX
cana-803	16	3	tell	tell	VERB
cana-803	16	4	the	the	DET
cana-803	16	5	difference	difference	NOUN
cana-803	16	6	between	between	ADP
cana-803	16	7	normal	normal	ADJ
cana-803	16	8	network	network	NOUN
cana-803	16	9	traffic	traffic	NOUN
cana-803	16	10	and	and	CCONJ
cana-803	16	11	hostile	hostile	ADJ
cana-803	16	12	activities	activity	NOUN
cana-803	16	13	because	because	SCONJ
cana-803	16	14	stochastic	stochastic	ADJ
cana-803	16	15	models	model	NOUN
cana-803	16	16	use	use	VERB
cana-803	16	17	a	a	DET
cana-803	16	18	statistical	statistical	ADJ
cana-803	16	19	framework	framework	NOUN
cana-803	16	20	to	to	PART
cana-803	16	21	capture	capture	VERB
cana-803	16	22	the	the	DET
cana-803	16	23	uncertainty	uncertainty	NOUN
cana-803	16	24	that	that	PRON
cana-803	16	25	comes	come	VERB
cana-803	16	26	with	with	ADP
cana-803	16	27	cyberattack	cyberattack	NOUN
cana-803	16	28	behaviors	behavior	NOUN
cana-803	16	29	.	.	PUNCT
cana-803	17	1	we	we	PRON
cana-803	17	2	use	use	VERB
cana-803	17	3	methods	method	NOUN
cana-803	17	4	from	from	ADP
cana-803	17	5	probability	probability	NOUN
cana-803	17	6	theory	theory	NOUN
cana-803	17	7	,	,	PUNCT
cana-803	17	8	markov	markov	NOUN
cana-803	17	9	chains	chain	NOUN
cana-803	17	10	,	,	PUNCT
cana-803	17	11	and	and	CCONJ
cana-803	17	12	queue	queue	NOUN
cana-803	17	13	theory	theory	NOUN
cana-803	17	14	to	to	PART
cana-803	17	15	make	make	VERB
cana-803	17	16	models	model	NOUN
cana-803	17	17	of	of	ADP
cana-803	17	18	how	how	SCONJ
cana-803	17	19	network	network	NOUN
cana-803	17	20	traffic	traffic	NOUN
cana-803	17	21	and	and	CCONJ
cana-803	17	22	possible	possible	ADJ
cana-803	17	23	cyberattacks	cyberattack	NOUN
cana-803	17	24	might	might	AUX
cana-803	17	25	behave	behave	VERB
cana-803	17	26	.	.	PUNCT
cana-803	18	1	our	our	PRON
cana-803	18	2	random	random	ADJ
cana-803	18	3	models	model	NOUN
cana-803	18	4	can	can	AUX
cana-803	18	5	find	find	VERB
cana-803	18	6	differences	difference	NOUN
cana-803	18	7	that	that	PRON
cana-803	18	8	could	could	AUX
cana-803	18	9	mean	mean	VERB
cana-803	18	10	someone	someone	PRON
cana-803	18	11	is	be	AUX
cana-803	18	12	doing	do	VERB
cana-803	18	13	something	something	PRON
cana-803	18	14	bad	bad	ADJ
cana-803	18	15	by	by	ADP
cana-803	18	16	looking	look	VERB
cana-803	18	17	at	at	ADP
cana-803	18	18	the	the	DET
cana-803	18	19	statistical	statistical	ADJ
cana-803	18	20	features	feature	NOUN
cana-803	18	21	of	of	ADP
cana-803	18	22	different	different	ADJ
cana-803	18	23	network	network	NOUN
cana-803	18	24	factors	factor	NOUN
cana-803	18	25	,	,	PUNCT
cana-803	18	26	like	like	ADP
cana-803	18	27	the	the	DET
cana-803	18	28	rate	rate	NOUN
cana-803	18	29	at	at	ADP
cana-803	18	30	which	which	PRON
cana-803	18	31	packets	packet	NOUN
cana-803	18	32	arrive	arrive	VERB
cana-803	18	33	,	,	PUNCT
cana-803	18	34	the	the	DET
cana-803	18	35	length	length	NOUN
cana-803	18	36	of	of	ADP
cana-803	18	37	a	a	DET
cana-803	18	38	link	link	NOUN
cana-803	18	39	,	,	PUNCT
cana-803	18	40	and	and	CCONJ
cana-803	18	41	the	the	DET
cana-803	18	42	size	size	NOUN
cana-803	18	43	of	of	ADP
cana-803	18	44	the	the	DET
cana-803	18	45	payloads	payload	NOUN
cana-803	18	46	.	.	PUNCT
cana-803	19	1	using	use	VERB
cana-803	19	2	markov	markov	NOUN
cana-803	19	3	models	model	NOUN
cana-803	19	4	,	,	PUNCT
cana-803	19	5	the	the	DET
cana-803	19	6	ids	id	NOUN
cana-803	19	7	can	can	AUX
cana-803	19	8	also	also	ADV
cana-803	19	9	guess	guess	VERB
cana-803	19	10	how	how	SCONJ
cana-803	19	11	likely	likely	ADJ
cana-803	19	12	it	it	PRON
cana-803	19	13	is	be	AUX
cana-803	19	14	that	that	SCONJ
cana-803	19	15	an	an	DET
cana-803	19	16	attack	attack	NOUN
cana-803	19	17	will	will	AUX
cana-803	19	18	happen	happen	VERB
cana-803	19	19	in	in	ADP
cana-803	19	20	the	the	DET
cana-803	19	21	future	future	NOUN
cana-803	19	22	based	base	VERB
cana-803	19	23	on	on	ADP
cana-803	19	24	past	past	ADJ
cana-803	19	25	data	data	PROPN
cana-803	19	26	,	,	PUNCT
cana-803	19	27	which	which	PRON
cana-803	19	28	helps	help	VERB
cana-803	19	29	with	with	ADP
cana-803	19	30	strategic	strategic	ADJ
cana-803	19	31	strategies	strategy	NOUN
cana-803	19	32	for	for	ADP
cana-803	19	33	reducing	reduce	VERB
cana-803	19	34	threats	threat	NOUN
cana-803	19	35	.	.	PUNCT
cana-803	20	1	along	along	ADP
cana-803	20	2	with	with	ADP
cana-803	20	3	monitoring	monitoring	NOUN
cana-803	20	4	,	,	PUNCT
cana-803	20	5	our	our	PRON
cana-803	20	6	system	system	NOUN
cana-803	20	7	includes	include	VERB
cana-803	20	8	ways	way	NOUN
cana-803	20	9	to	to	PART
cana-803	20	10	respond	respond	VERB
cana-803	20	11	to	to	ADP
cana-803	20	12	cyberattacks	cyberattack	NOUN
cana-803	20	13	and	and	CCONJ
cana-803	20	14	lessen	lessen	VERB
cana-803	20	15	their	their	PRON
cana-803	20	16	effects	effect	NOUN
cana-803	20	17	.	.	PUNCT
cana-803	21	1	by	by	ADP
cana-803	21	2	using	use	VERB
cana-803	21	3	stochastic	stochastic	ADJ
cana-803	21	4	optimization	optimization	NOUN
cana-803	21	5	methods	method	NOUN
cana-803	21	6	,	,	PUNCT
cana-803	21	7	we	we	PRON
cana-803	21	8	can	can	AUX
cana-803	21	9	change	change	VERB
cana-803	21	10	how	how	SCONJ
cana-803	21	11	resources	resource	NOUN
cana-803	21	12	are	be	AUX
cana-803	21	13	used	use	VERB
cana-803	21	14	and	and	CCONJ
cana-803	21	15	how	how	SCONJ
cana-803	21	16	reactions	reaction	NOUN
cana-803	21	17	are	be	AUX
cana-803	21	18	prioritized	prioritize	VERB
cana-803	21	19	based	base	VERB
cana-803	21	20	on	on	ADP
cana-803	21	21	how	how	SCONJ
cana-803	21	22	likely	likely	ADJ
cana-803	21	23	and	and	CCONJ
cana-803	21	24	how	how	SCONJ
cana-803	21	25	bad	bad	ADJ
cana-803	21	26	the	the	DET
cana-803	21	27	threats	threat	NOUN
cana-803	21	28	are	be	AUX
cana-803	21	29	to	to	PART
cana-803	21	30	be	be	AUX
cana-803	21	31	.	.	PUNCT
cana-803	22	1	this	this	DET
cana-803	22	2	flexible	flexible	ADJ
cana-803	22	3	method	method	NOUN
cana-803	22	4	makes	make	VERB
cana-803	22	5	the	the	DET
cana-803	22	6	network	network	NOUN
cana-803	22	7	infrastructure	infrastructure	NOUN
cana-803	22	8	more	more	ADV
cana-803	22	9	resistant	resistant	ADJ
cana-803	22	10	to	to	ADP
cana-803	22	11	complex	complex	ADJ
cana-803	22	12	attack	attack	NOUN
cana-803	22	13	routes	route	NOUN
cana-803	22	14	,	,	PUNCT
cana-803	22	15	which	which	PRON
cana-803	22	16	lowers	lower	VERB
cana-803	22	17	the	the	DET
cana-803	22	18	damage	damage	NOUN
cana-803	22	19	and	and	CCONJ
cana-803	22	20	downtime	downtime	NOUN
cana-803	22	21	that	that	PRON
cana-803	22	22	can	can	AUX
cana-803	22	23	happen	happen	VERB
cana-803	22	24	during	during	ADP
cana-803	22	25	cyber	cyber	ADJ
cana-803	22	26	events	event	NOUN
cana-803	22	27	.	.	PUNCT
cana-803	23	1	we	we	PRON
cana-803	23	2	show	show	VERB
cana-803	23	3	that	that	SCONJ
cana-803	23	4	our	our	PRON
cana-803	23	5	stochastic	stochastic	ADJ
cana-803	23	6	models	model	NOUN
cana-803	23	7	can	can	AUX
cana-803	23	8	improve	improve	VERB
cana-803	23	9	the	the	DET
cana-803	23	10	performance	performance	NOUN
cana-803	23	11	of	of	ADP
cana-803	23	12	ids	id	NOUN
cana-803	23	13	in	in	ADP
cana-803	23	14	real	real	ADJ
cana-803	23	15	-	-	PUNCT
cana-803	23	16	world	world	NOUN
cana-803	23	17	situations	situation	NOUN
cana-803	23	18	by	by	ADP
cana-803	23	19	analyzing	analyze	VERB
cana-803	23	20	them	they	PRON
cana-803	23	21	theoretically	theoretically	ADV
cana-803	23	22	and	and	CCONJ
cana-803	23	23	running	run	VERB
cana-803	23	24	simulations	simulation	NOUN
cana-803	23	25	.	.	PUNCT
cana-803	24	1	adopting	adopt	VERB
cana-803	24	2	a	a	DET
cana-803	24	3	scientific	scientific	ADJ
cana-803	24	4	approach	approach	NOUN
cana-803	24	5	to	to	ADP
cana-803	24	6	communications	communication	NOUN
cana-803	24	7	on	on	ADP
cana-803	24	8	applied	apply	VERB
cana-803	24	9	nonlinear	nonlinear	ADJ
cana-803	24	10	analysis	analysis	NOUN
cana-803	24	11	issn	issn	AUX
cana-803	24	12	:	:	PUNCT
cana-803	24	13	1074	1074	NUM
cana-803	24	14	-	-	PUNCT
cana-803	24	15	133x	133x	NUM
cana-803	24	16	vol	vol	NOUN
cana-803	24	17	31	31	NUM
cana-803	24	18	no	no	NOUN
cana-803	24	19	.	.	PUNCT
cana-803	25	1	3s	3s	NUM
cana-803	25	2	(	(	PUNCT
cana-803	25	3	2024	2024	NUM
cana-803	25	4	)	)	PUNCT
cana-803	25	5	488	488	NUM
cana-803	25	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-803	25	7	cyber	cyber	NOUN
cana-803	25	8	security	security	NOUN
cana-803	25	9	makes	make	VERB
cana-803	25	10	it	it	PRON
cana-803	25	11	possible	possible	ADJ
cana-803	25	12	for	for	ADP
cana-803	25	13	stronger	strong	ADJ
cana-803	25	14	and	and	CCONJ
cana-803	25	15	smarter	smart	ADJ
cana-803	25	16	defenses	defense	NOUN
cana-803	25	17	against	against	ADP
cana-803	25	18	cyber	cyber	ADJ
cana-803	25	19	risks	risk	NOUN
cana-803	25	20	that	that	PRON
cana-803	25	21	are	be	AUX
cana-803	25	22	always	always	ADV
cana-803	25	23	changing	change	VERB
cana-803	25	24	.	.	PUNCT
cana-803	26	1	keywords	keyword	NOUN
cana-803	26	2	:	:	PUNCT
cana-803	26	3	stochastic	stochastic	ADJ
cana-803	26	4	models	model	NOUN
cana-803	26	5	,	,	PUNCT
cana-803	26	6	cyber	cyber	NOUN
cana-803	26	7	attack	attack	NOUN
cana-803	26	8	detection	detection	NOUN
cana-803	26	9	,	,	PUNCT
cana-803	26	10	,	,	PUNCT
cana-803	26	11	intrusion	intrusion	NOUN
cana-803	26	12	detection	detection	NOUN
cana-803	26	13	systems	system	NOUN
cana-803	26	14	,	,	PUNCT
cana-803	26	15	probability	probability	NOUN
cana-803	26	16	theory	theory	NOUN
cana-803	26	17	,	,	PUNCT
cana-803	26	18	markov	markov	NOUN
cana-803	26	19	chains	chain	NOUN
cana-803	26	20	,	,	PUNCT
cana-803	26	21	queuing	queue	VERB
cana-803	26	22	theory	theory	NOUN
cana-803	26	23	,	,	PUNCT
cana-803	26	24	network	network	NOUN
cana-803	26	25	security	security	NOUN
cana-803	26	26	,	,	PUNCT
cana-803	26	27	adaptive	adaptive	ADJ
cana-803	26	28	defense	defense	NOUN
cana-803	26	29	,	,	PUNCT
cana-803	26	30	threat	threat	NOUN
cana-803	26	31	detection	detection	NOUN
cana-803	26	32	,	,	PUNCT
cana-803	26	33	response	response	NOUN
cana-803	26	34	mechanisms	mechanism	NOUN
cana-803	26	35	.	.	PUNCT
cana-803	27	1	1	1	X
cana-803	27	2	.	.	X
cana-803	27	3	introduction	introduction	NOUN
cana-803	27	4	cyber	cyber	PROPN
cana-803	27	5	dangers	danger	NOUN
cana-803	27	6	are	be	AUX
cana-803	27	7	becoming	become	VERB
cana-803	27	8	more	more	ADV
cana-803	27	9	common	common	ADJ
cana-803	27	10	in	in	ADP
cana-803	27	11	a	a	DET
cana-803	27	12	time	time	NOUN
cana-803	27	13	when	when	SCONJ
cana-803	27	14	people	people	NOUN
cana-803	27	15	are	be	AUX
cana-803	27	16	always	always	ADV
cana-803	27	17	connected	connect	VERB
cana-803	27	18	and	and	CCONJ
cana-803	27	19	rely	rely	VERB
cana-803	27	20	on	on	ADP
cana-803	27	21	technology	technology	NOUN
cana-803	27	22	.	.	PUNCT
cana-803	28	1	this	this	PRON
cana-803	28	2	makes	make	VERB
cana-803	28	3	it	it	PRON
cana-803	28	4	very	very	ADV
cana-803	28	5	hard	hard	ADV
cana-803	28	6	to	to	PART
cana-803	28	7	keep	keep	VERB
cana-803	28	8	information	information	NOUN
cana-803	28	9	systems	system	NOUN
cana-803	28	10	and	and	CCONJ
cana-803	28	11	networks	network	NOUN
cana-803	28	12	safe	safe	ADJ
cana-803	28	13	.	.	PUNCT
cana-803	29	1	there	there	PRON
cana-803	29	2	needs	need	VERB
cana-803	29	3	to	to	PART
cana-803	29	4	be	be	AUX
cana-803	29	5	more	more	ADV
cana-803	29	6	advanced	advanced	ADJ
cana-803	29	7	methods	method	NOUN
cana-803	29	8	for	for	ADP
cana-803	29	9	finding	find	VERB
cana-803	29	10	and	and	CCONJ
cana-803	29	11	stopping	stop	VERB
cana-803	29	12	harmful	harmful	ADJ
cana-803	29	13	actions	action	NOUN
cana-803	29	14	quickly	quickly	ADV
cana-803	29	15	because	because	SCONJ
cana-803	29	16	cyberattacks	cyberattack	NOUN
cana-803	29	17	are	be	AUX
cana-803	29	18	getting	get	VERB
cana-803	29	19	smarter	smart	ADJ
cana-803	29	20	and	and	CCONJ
cana-803	29	21	happen	happen	VERB
cana-803	29	22	more	more	ADV
cana-803	29	23	often	often	ADV
cana-803	29	24	.	.	PUNCT
cana-803	30	1	intrusion	intrusion	NOUN
cana-803	30	2	monitoring	monitoring	NOUN
cana-803	30	3	systems	system	NOUN
cana-803	30	4	(	(	PUNCT
cana-803	30	5	ids	id	NOUN
cana-803	30	6	)	)	PUNCT
cana-803	30	7	are	be	AUX
cana-803	30	8	an	an	DET
cana-803	30	9	important	important	ADJ
cana-803	30	10	line	line	NOUN
cana-803	30	11	of	of	ADP
cana-803	30	12	defense	defense	NOUN
cana-803	30	13	against	against	ADP
cana-803	30	14	cyber	cyber	NOUN
cana-803	30	15	threats	threat	NOUN
cana-803	30	16	because	because	SCONJ
cana-803	30	17	they	they	PRON
cana-803	30	18	find	find	VERB
cana-803	30	19	and	and	CCONJ
cana-803	30	20	stop	stop	VERB
cana-803	30	21	them	they	PRON
cana-803	30	22	[	[	X
cana-803	30	23	16	16	NUM
cana-803	30	24	]	]	PUNCT
cana-803	30	25	.	.	PUNCT
cana-803	31	1	however	however	ADV
cana-803	31	2	,	,	PUNCT
cana-803	31	3	because	because	SCONJ
cana-803	31	4	cyber	cyber	ADJ
cana-803	31	5	threats	threat	NOUN
cana-803	31	6	are	be	AUX
cana-803	31	7	always	always	ADV
cana-803	31	8	changing	change	VERB
cana-803	31	9	,	,	PUNCT
cana-803	31	10	monitoring	monitoring	NOUN
cana-803	31	11	methods	method	NOUN
cana-803	31	12	need	need	VERB
cana-803	31	13	to	to	PART
cana-803	31	14	be	be	AUX
cana-803	31	15	updated	update	VERB
cana-803	31	16	all	all	DET
cana-803	31	17	the	the	DET
cana-803	31	18	time	time	NOUN
cana-803	31	19	.	.	PUNCT
cana-803	32	1	signature	signature	NOUN
cana-803	32	2	-	-	PUNCT
cana-803	32	3	based	base	VERB
cana-803	32	4	or	or	CCONJ
cana-803	32	5	anomaly	anomaly	NOUN
cana-803	32	6	-	-	PUNCT
cana-803	32	7	based	base	VERB
cana-803	32	8	methods	method	NOUN
cana-803	32	9	are	be	AUX
cana-803	32	10	often	often	ADV
cana-803	32	11	used	use	VERB
cana-803	32	12	in	in	ADP
cana-803	32	13	traditional	traditional	ADJ
cana-803	32	14	ways	way	NOUN
cana-803	32	15	to	to	PART
cana-803	32	16	find	find	VERB
cana-803	32	17	intrusions	intrusion	NOUN
cana-803	32	18	.	.	PUNCT
cana-803	33	1	even	even	ADV
cana-803	33	2	though	though	SCONJ
cana-803	33	3	these	these	DET
cana-803	33	4	methods	method	NOUN
cana-803	33	5	work	work	VERB
cana-803	33	6	in	in	ADP
cana-803	33	7	some	some	DET
cana-803	33	8	situations	situation	NOUN
cana-803	33	9	,	,	PUNCT
cana-803	33	10	they	they	PRON
cana-803	33	11	are	be	AUX
cana-803	33	12	n't	not	PART
cana-803	33	13	very	very	ADV
cana-803	33	14	good	good	ADJ
cana-803	33	15	at	at	ADP
cana-803	33	16	adapting	adapt	VERB
cana-803	33	17	to	to	ADP
cana-803	33	18	the	the	DET
cana-803	33	19	constantly	constantly	ADV
cana-803	33	20	changing	change	VERB
cana-803	33	21	online	online	ADJ
cana-803	33	22	dangers	danger	NOUN
cana-803	33	23	.	.	PUNCT
cana-803	34	1	it	it	PRON
cana-803	34	2	's	be	AUX
cana-803	34	3	hard	hard	ADJ
cana-803	34	4	for	for	SCONJ
cana-803	34	5	signature	signature	NOUN
cana-803	34	6	-	-	PUNCT
cana-803	34	7	based	base	VERB
cana-803	34	8	monitoring	monitoring	NOUN
cana-803	34	9	systems	system	NOUN
cana-803	34	10	to	to	PART
cana-803	34	11	stop	stop	VERB
cana-803	34	12	new	new	ADJ
cana-803	34	13	or	or	CCONJ
cana-803	34	14	zero	zero	NUM
cana-803	34	15	-	-	PUNCT
cana-803	34	16	day	day	NOUN
cana-803	34	17	attacks	attack	NOUN
cana-803	34	18	because	because	SCONJ
cana-803	34	19	they	they	PRON
cana-803	34	20	depend	depend	VERB
cana-803	34	21	on	on	ADP
cana-803	34	22	patterns	pattern	NOUN
cana-803	34	23	of	of	ADP
cana-803	34	24	known	know	VERB
cana-803	34	25	attacks	attack	NOUN
cana-803	34	26	that	that	PRON
cana-803	34	27	have	have	AUX
cana-803	34	28	already	already	ADV
cana-803	34	29	been	be	AUX
cana-803	34	30	described	describe	VERB
cana-803	34	31	[	[	X
cana-803	34	32	17	17	NUM
cana-803	34	33	]	]	PUNCT
cana-803	34	34	.	.	PUNCT
cana-803	35	1	in	in	ADP
cana-803	35	2	the	the	DET
cana-803	35	3	same	same	ADJ
cana-803	35	4	way	way	NOUN
cana-803	35	5	,	,	PUNCT
cana-803	35	6	anomaly	anomaly	NOUN
cana-803	35	7	-	-	PUNCT
cana-803	35	8	based	base	VERB
cana-803	35	9	systems	system	NOUN
cana-803	35	10	might	might	AUX
cana-803	35	11	not	not	PART
cana-803	35	12	be	be	AUX
cana-803	35	13	able	able	ADJ
cana-803	35	14	to	to	PART
cana-803	35	15	tell	tell	VERB
cana-803	35	16	the	the	DET
cana-803	35	17	difference	difference	NOUN
cana-803	35	18	between	between	ADP
cana-803	35	19	normal	normal	ADJ
cana-803	35	20	changes	change	NOUN
cana-803	35	21	from	from	ADP
cana-803	35	22	behavior	behavior	NOUN
cana-803	35	23	and	and	CCONJ
cana-803	35	24	real	real	ADJ
cana-803	35	25	harmful	harmful	ADJ
cana-803	35	26	actions	action	NOUN
cana-803	35	27	,	,	PUNCT
cana-803	35	28	which	which	PRON
cana-803	35	29	could	could	AUX
cana-803	35	30	lead	lead	VERB
cana-803	35	31	to	to	ADP
cana-803	35	32	a	a	DET
cana-803	35	33	lot	lot	NOUN
cana-803	35	34	of	of	ADP
cana-803	35	35	fake	fake	ADJ
cana-803	35	36	positives	positive	NOUN
cana-803	35	37	or	or	CCONJ
cana-803	35	38	negatives	negative	NOUN
cana-803	35	39	.	.	PUNCT
cana-803	36	1	to	to	PART
cana-803	36	2	deal	deal	VERB
cana-803	36	3	with	with	ADP
cana-803	36	4	these	these	DET
cana-803	36	5	problems	problem	NOUN
cana-803	36	6	,	,	PUNCT
cana-803	36	7	we	we	PRON
cana-803	36	8	need	need	VERB
cana-803	36	9	to	to	PART
cana-803	36	10	change	change	VERB
cana-803	36	11	the	the	DET
cana-803	36	12	way	way	NOUN
cana-803	36	13	we	we	PRON
cana-803	36	14	do	do	VERB
cana-803	36	15	attack	attack	NOUN
cana-803	36	16	monitoring	monitor	VERB
cana-803	36	17	so	so	SCONJ
cana-803	36	18	it	it	PRON
cana-803	36	19	is	be	AUX
cana-803	36	20	smarter	smart	ADJ
cana-803	36	21	and	and	CCONJ
cana-803	36	22	more	more	ADV
cana-803	36	23	flexible	flexible	ADJ
cana-803	36	24	.	.	PUNCT
cana-803	37	1	the	the	DET
cana-803	37	2	main	main	ADJ
cana-803	37	3	idea	idea	NOUN
cana-803	37	4	of	of	ADP
cana-803	37	5	this	this	DET
cana-803	37	6	study	study	NOUN
cana-803	37	7	is	be	AUX
cana-803	37	8	that	that	SCONJ
cana-803	37	9	random	random	ADJ
cana-803	37	10	models	model	NOUN
cana-803	37	11	can	can	AUX
cana-803	37	12	be	be	AUX
cana-803	37	13	used	use	VERB
cana-803	37	14	as	as	ADP
cana-803	37	15	a	a	DET
cana-803	37	16	statistical	statistical	ADJ
cana-803	37	17	framework	framework	NOUN
cana-803	37	18	to	to	PART
cana-803	37	19	make	make	VERB
cana-803	37	20	ids	id	NOUN
cana-803	37	21	more	more	ADV
cana-803	37	22	useful	useful	ADJ
cana-803	37	23	.	.	PUNCT
cana-803	38	1	stochastic	stochastic	ADJ
cana-803	38	2	processes	process	NOUN
cana-803	38	3	are	be	AUX
cana-803	38	4	a	a	DET
cana-803	38	5	strong	strong	ADJ
cana-803	38	6	way	way	NOUN
cana-803	38	7	to	to	PART
cana-803	38	8	capture	capture	VERB
cana-803	38	9	the	the	DET
cana-803	38	10	uncertainty	uncertainty	NOUN
cana-803	38	11	and	and	CCONJ
cana-803	38	12	changeability	changeability	NOUN
cana-803	38	13	of	of	ADP
cana-803	38	14	cyberattack	cyberattack	NOUN
cana-803	38	15	behaviors	behavior	NOUN
cana-803	38	16	[	[	X
cana-803	38	17	18	18	NUM
cana-803	38	18	]	]	PUNCT
cana-803	38	19	.	.	PUNCT
cana-803	39	1	this	this	PRON
cana-803	39	2	makes	make	VERB
cana-803	39	3	monitoring	monitoring	NOUN
cana-803	39	4	systems	system	NOUN
cana-803	39	5	more	more	ADV
cana-803	39	6	reliable	reliable	ADJ
cana-803	39	7	and	and	CCONJ
cana-803	39	8	flexible	flexible	ADJ
cana-803	39	9	.	.	PUNCT
cana-803	40	1	what	what	PRON
cana-803	40	2	our	our	PRON
cana-803	40	3	suggested	suggest	VERB
cana-803	40	4	method	method	NOUN
cana-803	40	5	is	be	AUX
cana-803	40	6	based	base	VERB
cana-803	40	7	on	on	ADP
cana-803	40	8	is	be	AUX
cana-803	40	9	using	use	VERB
cana-803	40	10	probability	probability	NOUN
cana-803	40	11	theory	theory	NOUN
cana-803	40	12	,	,	PUNCT
cana-803	40	13	markov	markov	NOUN
cana-803	40	14	chains	chain	NOUN
cana-803	40	15	,	,	PUNCT
cana-803	40	16	and	and	CCONJ
cana-803	40	17	queue	queue	NOUN
cana-803	40	18	theory	theory	NOUN
cana-803	40	19	to	to	PART
cana-803	40	20	model	model	VERB
cana-803	40	21	how	how	SCONJ
cana-803	40	22	network	network	NOUN
cana-803	40	23	traffic	traffic	NOUN
cana-803	40	24	and	and	CCONJ
cana-803	40	25	cyberattacks	cyberattack	NOUN
cana-803	40	26	are	be	AUX
cana-803	40	27	random	random	ADJ
cana-803	40	28	.	.	PUNCT
cana-803	41	1	it	it	PRON
cana-803	41	2	is	be	AUX
cana-803	41	3	based	base	VERB
cana-803	41	4	on	on	ADP
cana-803	41	5	probability	probability	NOUN
cana-803	41	6	theory	theory	NOUN
cana-803	41	7	that	that	SCONJ
cana-803	41	8	we	we	PRON
cana-803	41	9	can	can	AUX
cana-803	41	10	measure	measure	VERB
cana-803	41	11	uncertainty	uncertainty	NOUN
cana-803	41	12	and	and	CCONJ
cana-803	41	13	make	make	VERB
cana-803	41	14	smart	smart	ADJ
cana-803	41	15	choices	choice	NOUN
cana-803	41	16	when	when	SCONJ
cana-803	41	17	we	we	PRON
cana-803	41	18	do	do	AUX
cana-803	41	19	n't	not	PART
cana-803	41	20	have	have	VERB
cana-803	41	21	all	all	DET
cana-803	41	22	the	the	DET
cana-803	41	23	facts	fact	NOUN
cana-803	41	24	.	.	PUNCT
cana-803	42	1	ids	id	NOUN
cana-803	42	2	can	can	AUX
cana-803	42	3	tell	tell	VERB
cana-803	42	4	the	the	DET
cana-803	42	5	difference	difference	NOUN
cana-803	42	6	between	between	ADP
cana-803	42	7	safe	safe	ADJ
cana-803	42	8	activities	activity	NOUN
cana-803	42	9	and	and	CCONJ
cana-803	42	10	harmful	harmful	ADJ
cana-803	42	11	attacks	attack	NOUN
cana-803	42	12	by	by	ADP
cana-803	42	13	representing	represent	VERB
cana-803	42	14	network	network	NOUN
cana-803	42	15	events	event	NOUN
cana-803	42	16	and	and	CCONJ
cana-803	42	17	behaviors	behavior	NOUN
cana-803	42	18	as	as	ADP
cana-803	42	19	stochastic	stochastic	ADJ
cana-803	42	20	processes	process	NOUN
cana-803	42	21	[	[	X
cana-803	42	22	19	19	NUM
cana-803	42	23	]	]	PUNCT
cana-803	42	24	.	.	PUNCT
cana-803	43	1	the	the	DET
cana-803	43	2	time	time	NOUN
cana-803	43	3	relationships	relationship	NOUN
cana-803	43	4	that	that	PRON
cana-803	43	5	are	be	AUX
cana-803	43	6	built	build	VERB
cana-803	43	7	into	into	ADP
cana-803	43	8	network	network	NOUN
cana-803	43	9	traffic	traffic	NOUN
cana-803	43	10	and	and	CCONJ
cana-803	43	11	attack	attack	NOUN
cana-803	43	12	patterns	pattern	NOUN
cana-803	43	13	can	can	AUX
cana-803	43	14	be	be	AUX
cana-803	43	15	well	well	ADV
cana-803	43	16	modeled	model	VERB
cana-803	43	17	with	with	ADP
cana-803	43	18	markov	markov	NOUN
cana-803	43	19	chains	chain	NOUN
cana-803	43	20	.	.	PUNCT
cana-803	44	1	markov	markov	NOUN
cana-803	44	2	models	model	NOUN
cana-803	44	3	can	can	AUX
cana-803	44	4	find	find	VERB
cana-803	44	5	the	the	DET
cana-803	44	6	trends	trend	NOUN
cana-803	44	7	that	that	PRON
cana-803	44	8	show	show	VERB
cana-803	44	9	when	when	SCONJ
cana-803	44	10	cyberattacks	cyberattack	NOUN
cana-803	44	11	happen	happen	VERB
cana-803	44	12	by	by	ADP
cana-803	44	13	describing	describe	VERB
cana-803	44	14	the	the	DET
cana-803	44	15	changes	change	NOUN
cana-803	44	16	that	that	PRON
cana-803	44	17	happen	happen	VERB
cana-803	44	18	between	between	ADP
cana-803	44	19	different	different	ADJ
cana-803	44	20	states	state	NOUN
cana-803	44	21	of	of	ADP
cana-803	44	22	network	network	NOUN
cana-803	44	23	activity	activity	NOUN
cana-803	44	24	[	[	X
cana-803	44	25	20	20	NUM
cana-803	44	26	]	]	PUNCT
cana-803	44	27	.	.	PUNCT
cana-803	45	1	this	this	PRON
cana-803	45	2	lets	let	VERB
cana-803	45	3	ids	ids	AUX
cana-803	45	4	not	not	PART
cana-803	45	5	only	only	ADV
cana-803	45	6	find	find	VERB
cana-803	45	7	current	current	ADJ
cana-803	45	8	threats	threat	NOUN
cana-803	45	9	but	but	CCONJ
cana-803	45	10	also	also	ADV
cana-803	45	11	guess	guess	VERB
cana-803	45	12	what	what	PRON
cana-803	45	13	kinds	kind	NOUN
cana-803	45	14	of	of	ADP
cana-803	45	15	attacks	attack	NOUN
cana-803	45	16	might	might	AUX
cana-803	45	17	happen	happen	VERB
cana-803	45	18	in	in	ADP
cana-803	45	19	the	the	DET
cana-803	45	20	future	future	NOUN
cana-803	45	21	based	base	VERB
cana-803	45	22	on	on	ADP
cana-803	45	23	what	what	PRON
cana-803	45	24	has	have	AUX
cana-803	45	25	happened	happen	VERB
cana-803	45	26	in	in	ADP
cana-803	45	27	the	the	DET
cana-803	45	28	past	past	NOUN
cana-803	45	29	.	.	PUNCT
cana-803	46	1	using	use	VERB
cana-803	46	2	markov	markov	NOUN
cana-803	46	3	models	model	NOUN
cana-803	46	4	also	also	ADV
cana-803	46	5	makes	make	VERB
cana-803	46	6	it	it	PRON
cana-803	46	7	easier	easy	ADJ
cana-803	46	8	to	to	PART
cana-803	46	9	guess	guess	VERB
cana-803	46	10	how	how	SCONJ
cana-803	46	11	likely	likely	ADJ
cana-803	46	12	an	an	DET
cana-803	46	13	attack	attack	NOUN
cana-803	46	14	is	be	AUX
cana-803	46	15	to	to	PART
cana-803	46	16	happen	happen	VERB
cana-803	46	17	and	and	CCONJ
cana-803	46	18	figure	figure	VERB
cana-803	46	19	out	out	ADP
cana-803	46	20	the	the	DET
cana-803	46	21	best	good	ADJ
cana-803	46	22	way	way	NOUN
cana-803	46	23	to	to	PART
cana-803	46	24	respond	respond	VERB
cana-803	46	25	,	,	PUNCT
cana-803	46	26	which	which	PRON
cana-803	46	27	improves	improve	VERB
cana-803	46	28	the	the	DET
cana-803	46	29	total	total	ADJ
cana-803	46	30	efficiency	efficiency	NOUN
cana-803	46	31	of	of	ADP
cana-803	46	32	intrusion	intrusion	NOUN
cana-803	46	33	detection	detection	NOUN
cana-803	46	34	and	and	CCONJ
cana-803	46	35	reaction	reaction	NOUN
cana-803	46	36	.	.	PUNCT
cana-803	47	1	queuing	queue	VERB
cana-803	47	2	theory	theory	NOUN
cana-803	47	3	,	,	PUNCT
cana-803	47	4	on	on	ADP
cana-803	47	5	the	the	DET
cana-803	47	6	other	other	ADJ
cana-803	47	7	hand	hand	NOUN
cana-803	47	8	,	,	PUNCT
cana-803	47	9	helps	help	VERB
cana-803	47	10	us	we	PRON
cana-803	47	11	understand	understand	VERB
cana-803	47	12	how	how	SCONJ
cana-803	47	13	network	network	NOUN
cana-803	47	14	traffic	traffic	NOUN
cana-803	47	15	and	and	CCONJ
cana-803	47	16	resource	resource	NOUN
cana-803	47	17	use	use	NOUN
cana-803	47	18	change	change	NOUN
cana-803	47	19	over	over	ADP
cana-803	47	20	time	time	NOUN
cana-803	47	21	.	.	PUNCT
cana-803	48	1	queuing	queue	VERB
cana-803	48	2	models	model	NOUN
cana-803	48	3	help	help	VERB
cana-803	48	4	intrusion	intrusion	NOUN
cana-803	48	5	detection	detection	NOUN
cana-803	48	6	systems	system	NOUN
cana-803	48	7	(	(	PUNCT
cana-803	48	8	ids	id	NOUN
cana-803	48	9	)	)	PUNCT
cana-803	48	10	figure	figure	NOUN
cana-803	48	11	out	out	ADP
cana-803	48	12	how	how	SCONJ
cana-803	48	13	new	new	ADJ
cana-803	48	14	traffic	traffic	NOUN
cana-803	48	15	affects	affect	VERB
cana-803	48	16	system	system	NOUN
cana-803	48	17	speed	speed	NOUN
cana-803	48	18	and	and	CCONJ
cana-803	48	19	find	find	VERB
cana-803	48	20	possible	possible	ADJ
cana-803	48	21	bottlenecks	bottleneck	NOUN
cana-803	48	22	or	or	CCONJ
cana-803	48	23	security	security	NOUN
cana-803	48	24	holes	hole	NOUN
cana-803	48	25	by	by	ADP
cana-803	48	26	simulating	simulate	VERB
cana-803	48	27	how	how	SCONJ
cana-803	48	28	requests	request	NOUN
cana-803	48	29	arrive	arrive	VERB
cana-803	48	30	and	and	CCONJ
cana-803	48	31	are	be	AUX
cana-803	48	32	handled	handle	VERB
cana-803	48	33	[	[	PUNCT
cana-803	48	34	21	21	NUM
cana-803	48	35	]	]	PUNCT
cana-803	48	36	.	.	PUNCT
cana-803	49	1	this	this	PRON
cana-803	49	2	makes	make	VERB
cana-803	49	3	it	it	PRON
cana-803	49	4	possible	possible	ADJ
cana-803	49	5	to	to	PART
cana-803	49	6	plan	plan	VERB
cana-803	49	7	ahead	ahead	ADV
cana-803	49	8	and	and	CCONJ
cana-803	49	9	allocate	allocate	VERB
cana-803	49	10	resources	resource	NOUN
cana-803	49	11	and	and	CCONJ
cana-803	49	12	reaction	reaction	NOUN
cana-803	49	13	tactics	tactic	NOUN
cana-803	49	14	in	in	ADP
cana-803	49	15	the	the	DET
cana-803	49	16	best	good	ADJ
cana-803	49	17	way	way	NOUN
cana-803	49	18	possible	possible	ADJ
cana-803	49	19	to	to	PART
cana-803	49	20	lessen	lessen	VERB
cana-803	49	21	the	the	DET
cana-803	49	22	effects	effect	NOUN
cana-803	49	23	of	of	ADP
cana-803	49	24	cyberattacks	cyberattack	NOUN
cana-803	49	25	.	.	PUNCT
cana-803	50	1	along	along	ADP
cana-803	50	2	with	with	ADP
cana-803	50	3	monitoring	monitoring	NOUN
cana-803	50	4	,	,	PUNCT
cana-803	50	5	our	our	PRON
cana-803	50	6	system	system	NOUN
cana-803	50	7	includes	include	VERB
cana-803	50	8	ways	way	NOUN
cana-803	50	9	to	to	PART
cana-803	50	10	respond	respond	VERB
cana-803	50	11	to	to	ADP
cana-803	50	12	cyberattacks	cyberattack	NOUN
cana-803	50	13	so	so	SCONJ
cana-803	50	14	that	that	SCONJ
cana-803	50	15	they	they	PRON
cana-803	50	16	cause	cause	VERB
cana-803	50	17	as	as	ADP
cana-803	50	18	little	little	ADJ
cana-803	50	19	damage	damage	NOUN
cana-803	50	20	and	and	CCONJ
cana-803	50	21	trouble	trouble	NOUN
cana-803	50	22	as	as	ADP
cana-803	50	23	possible	possible	ADJ
cana-803	50	24	[	[	X
cana-803	50	25	22	22	NUM
cana-803	50	26	]	]	PUNCT
cana-803	50	27	.	.	PUNCT
cana-803	51	1	ids	id	NOUN
cana-803	51	2	can	can	AUX
cana-803	51	3	change	change	VERB
cana-803	51	4	its	its	PRON
cana-803	51	5	communications	communication	NOUN
cana-803	51	6	on	on	ADP
cana-803	51	7	applied	apply	VERB
cana-803	51	8	nonlinear	nonlinear	ADJ
cana-803	51	9	analysis	analysis	NOUN
cana-803	51	10	issn	issn	NOUN
cana-803	51	11	:	:	PUNCT
cana-803	51	12	1074	1074	NUM
cana-803	51	13	-	-	PUNCT
cana-803	51	14	133x	133x	NUM
cana-803	51	15	vol	vol	NOUN
cana-803	51	16	31	31	NUM
cana-803	51	17	no	no	NOUN
cana-803	51	18	.	.	PUNCT
cana-803	52	1	3s	3s	NUM
cana-803	52	2	(	(	PUNCT
cana-803	52	3	2024	2024	NUM
cana-803	52	4	)	)	PUNCT
cana-803	52	5	489	489	NUM
cana-803	52	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-803	52	7	reaction	reaction	NOUN
cana-803	52	8	actions	action	NOUN
cana-803	52	9	based	base	VERB
cana-803	52	10	on	on	ADP
cana-803	52	11	the	the	DET
cana-803	52	12	intensity	intensity	NOUN
cana-803	52	13	and	and	CCONJ
cana-803	52	14	chance	chance	NOUN
cana-803	52	15	of	of	ADP
cana-803	52	16	arriving	arrive	VERB
cana-803	52	17	threats	threat	NOUN
cana-803	52	18	by	by	ADP
cana-803	52	19	using	use	VERB
cana-803	52	20	random	random	ADJ
cana-803	52	21	optimization	optimization	NOUN
cana-803	52	22	methods	method	NOUN
cana-803	52	23	.	.	PUNCT
cana-803	53	1	this	this	DET
cana-803	53	2	flexible	flexible	ADJ
cana-803	53	3	method	method	NOUN
cana-803	53	4	makes	make	VERB
cana-803	53	5	sure	sure	ADJ
cana-803	53	6	that	that	SCONJ
cana-803	53	7	limited	limited	ADJ
cana-803	53	8	resources	resource	NOUN
cana-803	53	9	are	be	AUX
cana-803	53	10	carefully	carefully	ADV
cana-803	53	11	assigned	assign	VERB
cana-803	53	12	to	to	PART
cana-803	53	13	deal	deal	VERB
cana-803	53	14	with	with	ADP
cana-803	53	15	the	the	DET
cana-803	53	16	most	most	ADV
cana-803	53	17	important	important	ADJ
cana-803	53	18	threats	threat	NOUN
cana-803	53	19	,	,	PUNCT
cana-803	53	20	making	make	VERB
cana-803	53	21	the	the	DET
cana-803	53	22	network	network	NOUN
cana-803	53	23	infrastructure	infrastructure	NOUN
cana-803	53	24	more	more	ADV
cana-803	53	25	resistant	resistant	ADJ
cana-803	53	26	to	to	ADP
cana-803	53	27	complex	complex	ADJ
cana-803	53	28	attack	attack	NOUN
cana-803	53	29	methods	method	NOUN
cana-803	53	30	.	.	PUNCT
cana-803	54	1	2	2	X
cana-803	54	2	.	.	X
cana-803	54	3	related	relate	VERB
cana-803	54	4	work	work	NOUN
cana-803	54	5	a	a	DET
cana-803	54	6	lot	lot	NOUN
cana-803	54	7	of	of	ADP
cana-803	54	8	different	different	ADJ
cana-803	54	9	studies	study	NOUN
cana-803	54	10	have	have	AUX
cana-803	54	11	been	be	AUX
cana-803	54	12	done	do	VERB
cana-803	54	13	in	in	ADP
cana-803	54	14	the	the	DET
cana-803	54	15	area	area	NOUN
cana-803	54	16	of	of	ADP
cana-803	54	17	cyber	cyber	ADJ
cana-803	54	18	attack	attack	NOUN
cana-803	54	19	discovery	discovery	NOUN
cana-803	54	20	and	and	CCONJ
cana-803	54	21	reaction	reaction	NOUN
cana-803	54	22	.	.	PUNCT
cana-803	55	1	these	these	DET
cana-803	55	2	studies	study	NOUN
cana-803	55	3	help	help	VERB
cana-803	55	4	make	make	VERB
cana-803	55	5	intrusion	intrusion	NOUN
cana-803	55	6	detection	detection	NOUN
cana-803	55	7	systems	system	NOUN
cana-803	55	8	(	(	PUNCT
cana-803	55	9	ids	id	NOUN
cana-803	55	10	)	)	PUNCT
cana-803	55	11	and	and	CCONJ
cana-803	55	12	other	other	ADJ
cana-803	55	13	defenses	defense	NOUN
cana-803	55	14	against	against	ADP
cana-803	55	15	cyber	cyber	NOUN
cana-803	55	16	dangers	danger	NOUN
cana-803	55	17	more	more	ADV
cana-803	55	18	effective	effective	ADJ
cana-803	55	19	.	.	PUNCT
cana-803	56	1	these	these	DET
cana-803	56	2	studies	study	NOUN
cana-803	56	3	use	use	VERB
cana-803	56	4	a	a	DET
cana-803	56	5	variety	variety	NOUN
cana-803	56	6	of	of	ADP
cana-803	56	7	methods	method	NOUN
cana-803	56	8	,	,	PUNCT
cana-803	56	9	such	such	ADJ
cana-803	56	10	as	as	ADP
cana-803	56	11	machine	machine	NOUN
cana-803	56	12	learning	learning	NOUN
cana-803	56	13	,	,	PUNCT
cana-803	56	14	game	game	NOUN
cana-803	56	15	theory	theory	NOUN
cana-803	56	16	,	,	PUNCT
cana-803	56	17	random	random	ADJ
cana-803	56	18	modeling	modeling	NOUN
cana-803	56	19	,	,	PUNCT
cana-803	56	20	and	and	CCONJ
cana-803	56	21	network	network	NOUN
cana-803	56	22	analysis	analysis	NOUN
cana-803	56	23	,	,	PUNCT
cana-803	56	24	to	to	PART
cana-803	56	25	make	make	VERB
cana-803	56	26	cyber	cyber	NOUN
cana-803	56	27	security	security	NOUN
cana-803	56	28	measures	measure	NOUN
cana-803	56	29	more	more	ADV
cana-803	56	30	effective	effective	ADJ
cana-803	56	31	and	and	CCONJ
cana-803	56	32	resilient	resilient	ADJ
cana-803	56	33	.	.	PUNCT
cana-803	57	1	using	use	VERB
cana-803	57	2	random	random	ADJ
cana-803	57	3	processes	process	NOUN
cana-803	57	4	to	to	PART
cana-803	57	5	describe	describe	VERB
cana-803	57	6	how	how	SCONJ
cana-803	57	7	cyberattacks	cyberattack	NOUN
cana-803	57	8	work	work	NOUN
cana-803	57	9	is	be	AUX
cana-803	57	10	a	a	DET
cana-803	57	11	popular	popular	ADJ
cana-803	57	12	area	area	NOUN
cana-803	57	13	of	of	ADP
cana-803	57	14	study	study	NOUN
cana-803	57	15	[	[	X
cana-803	57	16	1	1	NUM
cana-803	57	17	]	]	PUNCT
cana-803	57	18	.	.	PUNCT
cana-803	58	1	researchers	researcher	NOUN
cana-803	58	2	have	have	AUX
cana-803	58	3	found	find	VERB
cana-803	58	4	temporal	temporal	ADJ
cana-803	58	5	patterns	pattern	NOUN
cana-803	58	6	in	in	ADP
cana-803	58	7	attack	attack	NOUN
cana-803	58	8	behaviors	behavior	NOUN
cana-803	58	9	by	by	ADP
cana-803	58	10	using	use	VERB
cana-803	58	11	tools	tool	NOUN
cana-803	58	12	like	like	ADP
cana-803	58	13	markov	markov	NOUN
cana-803	58	14	chains	chain	NOUN
cana-803	58	15	and	and	CCONJ
cana-803	58	16	hidden	hide	VERB
cana-803	58	17	markov	markov	NOUN
cana-803	58	18	models	model	NOUN
cana-803	58	19	.	.	PUNCT
cana-803	59	1	this	this	PRON
cana-803	59	2	makes	make	VERB
cana-803	59	3	it	it	PRON
cana-803	59	4	easier	easy	ADJ
cana-803	59	5	to	to	PART
cana-803	59	6	find	find	VERB
cana-803	59	7	and	and	CCONJ
cana-803	59	8	predict	predict	VERB
cana-803	59	9	malicious	malicious	ADJ
cana-803	59	10	activities	activity	NOUN
cana-803	59	11	.	.	PUNCT
cana-803	60	1	as	as	ADP
cana-803	60	2	a	a	DET
cana-803	60	3	result	result	NOUN
cana-803	60	4	,	,	PUNCT
cana-803	60	5	probabilistic	probabilistic	ADJ
cana-803	60	6	analysis	analysis	NOUN
cana-803	60	7	of	of	ADP
cana-803	60	8	network	network	NOUN
cana-803	60	9	traffic	traffic	NOUN
cana-803	60	10	has	have	AUX
cana-803	60	11	become	become	VERB
cana-803	60	12	an	an	DET
cana-803	60	13	important	important	ADJ
cana-803	60	14	part	part	NOUN
cana-803	60	15	of	of	ADP
cana-803	60	16	intrusion	intrusion	NOUN
cana-803	60	17	detection	detection	NOUN
cana-803	60	18	[	[	X
cana-803	60	19	2	2	NUM
cana-803	60	20	]	]	PUNCT
cana-803	60	21	.	.	PUNCT
cana-803	61	1	researchers	researcher	NOUN
cana-803	61	2	have	have	AUX
cana-803	61	3	made	make	VERB
cana-803	61	4	it	it	PRON
cana-803	61	5	easier	easy	ADJ
cana-803	61	6	for	for	SCONJ
cana-803	61	7	ids	id	NOUN
cana-803	61	8	to	to	PART
cana-803	61	9	tell	tell	VERB
cana-803	61	10	the	the	DET
cana-803	61	11	difference	difference	NOUN
cana-803	61	12	between	between	ADP
cana-803	61	13	normal	normal	ADJ
cana-803	61	14	and	and	CCONJ
cana-803	61	15	strange	strange	ADJ
cana-803	61	16	actions	action	NOUN
cana-803	61	17	by	by	ADP
cana-803	61	18	using	use	VERB
cana-803	61	19	probability	probability	NOUN
cana-803	61	20	theory	theory	NOUN
cana-803	61	21	and	and	CCONJ
cana-803	61	22	statistical	statistical	ADJ
cana-803	61	23	analysis	analysis	NOUN
cana-803	61	24	to	to	PART
cana-803	61	25	measure	measure	VERB
cana-803	61	26	the	the	DET
cana-803	61	27	uncertainty	uncertainty	NOUN
cana-803	61	28	in	in	ADP
cana-803	61	29	network	network	NOUN
cana-803	61	30	behavior	behavior	NOUN
cana-803	61	31	.	.	PUNCT
cana-803	62	1	adaptive	adaptive	ADJ
cana-803	62	2	defense	defense	NOUN
cana-803	62	3	methods	method	NOUN
cana-803	62	4	have	have	AUX
cana-803	62	5	also	also	ADV
cana-803	62	6	gotten	get	VERB
cana-803	62	7	a	a	DET
cana-803	62	8	lot	lot	NOUN
cana-803	62	9	of	of	ADP
cana-803	62	10	attention	attention	NOUN
cana-803	62	11	in	in	ADP
cana-803	62	12	the	the	DET
cana-803	62	13	research	research	NOUN
cana-803	62	14	[	[	X
cana-803	62	15	3	3	NUM
cana-803	62	16	]	]	PUNCT
cana-803	62	17	.	.	PUNCT
cana-803	63	1	these	these	DET
cana-803	63	2	studies	study	NOUN
cana-803	63	3	look	look	VERB
cana-803	63	4	into	into	ADP
cana-803	63	5	ways	way	NOUN
cana-803	63	6	to	to	PART
cana-803	63	7	respond	respond	VERB
cana-803	63	8	that	that	PRON
cana-803	63	9	are	be	AUX
cana-803	63	10	dynamic	dynamic	ADJ
cana-803	63	11	and	and	CCONJ
cana-803	63	12	can	can	AUX
cana-803	63	13	change	change	VERB
cana-803	63	14	in	in	ADP
cana-803	63	15	real	real	ADJ
cana-803	63	16	time	time	NOUN
cana-803	63	17	as	as	SCONJ
cana-803	63	18	threats	threat	NOUN
cana-803	63	19	change	change	VERB
cana-803	63	20	.	.	PUNCT
cana-803	64	1	many	many	ADJ
cana-803	64	2	times	time	NOUN
cana-803	64	3	,	,	PUNCT
cana-803	64	4	stochastic	stochastic	ADJ
cana-803	64	5	optimization	optimization	NOUN
cana-803	64	6	methods	method	NOUN
cana-803	64	7	are	be	AUX
cana-803	64	8	used	use	VERB
cana-803	64	9	to	to	PART
cana-803	64	10	make	make	VERB
cana-803	64	11	the	the	DET
cana-803	64	12	best	good	ADJ
cana-803	64	13	use	use	NOUN
cana-803	64	14	of	of	ADP
cana-803	64	15	resources	resource	NOUN
cana-803	64	16	and	and	CCONJ
cana-803	64	17	set	set	VERB
cana-803	64	18	priorities	priority	NOUN
cana-803	64	19	for	for	ADP
cana-803	64	20	reaction	reaction	NOUN
cana-803	64	21	actions	action	NOUN
cana-803	64	22	,	,	PUNCT
cana-803	64	23	which	which	PRON
cana-803	64	24	lowers	lower	VERB
cana-803	64	25	the	the	DET
cana-803	64	26	damage	damage	NOUN
cana-803	64	27	from	from	ADP
cana-803	64	28	cyberattacks	cyberattack	NOUN
cana-803	64	29	.	.	PUNCT
cana-803	65	1	also	also	ADV
cana-803	65	2	,	,	PUNCT
cana-803	65	3	using	use	VERB
cana-803	65	4	queue	queue	NOUN
cana-803	65	5	models	model	NOUN
cana-803	65	6	for	for	ADP
cana-803	65	7	anomaly	anomaly	NOUN
cana-803	65	8	detection	detection	NOUN
cana-803	65	9	has	have	AUX
cana-803	65	10	shown	show	VERB
cana-803	65	11	promise	promise	NOUN
cana-803	65	12	in	in	ADP
cana-803	65	13	making	make	VERB
cana-803	65	14	detections	detection	NOUN
cana-803	65	15	more	more	ADV
cana-803	65	16	accurate	accurate	ADJ
cana-803	65	17	by	by	ADP
cana-803	65	18	simulating	simulate	VERB
cana-803	65	19	how	how	SCONJ
cana-803	65	20	resources	resource	NOUN
cana-803	65	21	are	be	AUX
cana-803	65	22	used	use	VERB
cana-803	65	23	and	and	CCONJ
cana-803	65	24	how	how	SCONJ
cana-803	65	25	the	the	DET
cana-803	65	26	system	system	NOUN
cana-803	65	27	changes	change	VERB
cana-803	65	28	over	over	ADP
cana-803	65	29	time	time	NOUN
cana-803	65	30	[	[	X
cana-803	65	31	4	4	NUM
cana-803	65	32	]	]	PUNCT
cana-803	65	33	.	.	PUNCT
cana-803	66	1	using	use	VERB
cana-803	66	2	stochastic	stochastic	ADJ
cana-803	66	3	gradient	gradient	ADJ
cana-803	66	4	descent	descent	NOUN
cana-803	66	5	and	and	CCONJ
cana-803	66	6	supervised	supervise	VERB
cana-803	66	7	learning	learning	NOUN
cana-803	66	8	methods	method	NOUN
cana-803	66	9	to	to	PART
cana-803	66	10	train	train	VERB
cana-803	66	11	models	model	NOUN
cana-803	66	12	on	on	ADP
cana-803	66	13	big	big	ADJ
cana-803	66	14	datasets	dataset	NOUN
cana-803	66	15	[	[	X
cana-803	66	16	5	5	NUM
cana-803	66	17	]	]	PUNCT
cana-803	66	18	is	be	AUX
cana-803	66	19	an	an	DET
cana-803	66	20	important	important	ADJ
cana-803	66	21	part	part	NOUN
cana-803	66	22	of	of	ADP
cana-803	66	23	machine	machine	NOUN
cana-803	66	24	learning	learn	VERB
cana-803	66	25	approaches	approach	NOUN
cana-803	66	26	used	use	VERB
cana-803	66	27	for	for	ADP
cana-803	66	28	breach	breach	NOUN
cana-803	66	29	detection	detection	NOUN
cana-803	66	30	.	.	PUNCT
cana-803	67	1	these	these	DET
cana-803	67	2	models	model	NOUN
cana-803	67	3	can	can	AUX
cana-803	67	4	find	find	VERB
cana-803	67	5	complicated	complicated	ADJ
cana-803	67	6	trends	trend	NOUN
cana-803	67	7	and	and	CCONJ
cana-803	67	8	strange	strange	ADJ
cana-803	67	9	things	thing	NOUN
cana-803	67	10	in	in	ADP
cana-803	67	11	network	network	NOUN
cana-803	67	12	data	datum	NOUN
cana-803	67	13	,	,	PUNCT
cana-803	67	14	which	which	PRON
cana-803	67	15	makes	make	VERB
cana-803	67	16	it	it	PRON
cana-803	67	17	easier	easy	ADJ
cana-803	67	18	for	for	SCONJ
cana-803	67	19	ids	id	NOUN
cana-803	67	20	to	to	PART
cana-803	67	21	find	find	VERB
cana-803	67	22	new	new	ADJ
cana-803	67	23	threats	threat	NOUN
cana-803	67	24	.	.	PUNCT
cana-803	68	1	also	also	ADV
cana-803	68	2	,	,	PUNCT
cana-803	68	3	game	game	NOUN
cana-803	68	4	-	-	PUNCT
cana-803	68	5	theoretic	theoretic	NOUN
cana-803	68	6	methods	method	NOUN
cana-803	68	7	have	have	AUX
cana-803	68	8	been	be	AUX
cana-803	68	9	suggested	suggest	VERB
cana-803	68	10	to	to	PART
cana-803	68	11	figure	figure	VERB
cana-803	68	12	out	out	ADP
cana-803	68	13	the	the	DET
cana-803	68	14	best	good	ADJ
cana-803	68	15	ways	way	NOUN
cana-803	68	16	to	to	PART
cana-803	68	17	defend	defend	VERB
cana-803	68	18	yourself	yourself	PRON
cana-803	68	19	in	in	ADP
cana-803	68	20	hostile	hostile	ADJ
cana-803	68	21	settings	setting	NOUN
cana-803	68	22	,	,	PUNCT
cana-803	68	23	which	which	PRON
cana-803	68	24	can	can	AUX
cana-803	68	25	help	help	VERB
cana-803	68	26	us	we	PRON
cana-803	68	27	understand	understand	VERB
cana-803	68	28	how	how	SCONJ
cana-803	68	29	cyberwars	cyberwar	NOUN
cana-803	68	30	and	and	CCONJ
cana-803	68	31	security	security	NOUN
cana-803	68	32	strategies	strategy	NOUN
cana-803	68	33	work	work	VERB
cana-803	68	34	[	[	X
cana-803	68	35	6	6	NUM
cana-803	68	36	]	]	PUNCT
cana-803	68	37	.	.	PUNCT
cana-803	69	1	behavioral	behavioral	ADJ
cana-803	69	2	analysis	analysis	NOUN
cana-803	69	3	methods	method	NOUN
cana-803	69	4	are	be	AUX
cana-803	69	5	good	good	ADJ
cana-803	69	6	at	at	ADP
cana-803	69	7	finding	find	VERB
cana-803	69	8	malware	malware	NOUN
cana-803	69	9	attacks	attack	NOUN
cana-803	69	10	because	because	SCONJ
cana-803	69	11	they	they	PRON
cana-803	69	12	find	find	VERB
cana-803	69	13	behavioral	behavioral	ADJ
cana-803	69	14	patterns	pattern	NOUN
cana-803	69	15	that	that	PRON
cana-803	69	16	show	show	VERB
cana-803	69	17	bad	bad	ADJ
cana-803	69	18	behavior	behavior	NOUN
cana-803	69	19	[	[	X
cana-803	69	20	7	7	NUM
cana-803	69	21	]	]	PUNCT
cana-803	69	22	.	.	PUNCT
cana-803	70	1	to	to	PART
cana-803	70	2	sort	sort	VERB
cana-803	70	3	and	and	CCONJ
cana-803	70	4	stop	stop	VERB
cana-803	70	5	cyber	cyber	NOUN
cana-803	70	6	risks	risk	NOUN
cana-803	70	7	,	,	PUNCT
cana-803	70	8	these	these	DET
cana-803	70	9	studies	study	NOUN
cana-803	70	10	use	use	VERB
cana-803	70	11	machine	machine	NOUN
cana-803	70	12	learning	learn	VERB
cana-803	70	13	algorithms	algorithm	NOUN
cana-803	70	14	and	and	CCONJ
cana-803	70	15	behavioral	behavioral	ADJ
cana-803	70	16	analysis	analysis	NOUN
cana-803	70	17	methods	method	NOUN
cana-803	70	18	.	.	PUNCT
cana-803	71	1	using	use	VERB
cana-803	71	2	bayesian	bayesian	NOUN
cana-803	71	3	networks	network	NOUN
cana-803	71	4	for	for	ADP
cana-803	71	5	breach	breach	NOUN
cana-803	71	6	detection	detection	NOUN
cana-803	71	7	has	have	AUX
cana-803	71	8	also	also	ADV
cana-803	71	9	shown	show	VERB
cana-803	71	10	promise	promise	NOUN
cana-803	71	11	in	in	ADP
cana-803	71	12	making	make	VERB
cana-803	71	13	detections	detection	NOUN
cana-803	71	14	more	more	ADV
cana-803	71	15	accurate	accurate	ADJ
cana-803	71	16	through	through	ADP
cana-803	71	17	statistical	statistical	ADJ
cana-803	71	18	reasoning	reasoning	NOUN
cana-803	71	19	[	[	X
cana-803	71	20	8	8	NUM
cana-803	71	21	]	]	PUNCT
cana-803	71	22	.	.	PUNCT
cana-803	72	1	bayesian	bayesian	NOUN
cana-803	72	2	networks	network	NOUN
cana-803	72	3	make	make	VERB
cana-803	72	4	danger	danger	NOUN
cana-803	72	5	assessment	assessment	NOUN
cana-803	72	6	and	and	CCONJ
cana-803	72	7	decision	decision	NOUN
cana-803	72	8	-	-	PUNCT
cana-803	72	9	making	making	NOUN
cana-803	72	10	more	more	ADV
cana-803	72	11	complex	complex	ADJ
cana-803	72	12	by	by	ADP
cana-803	72	13	describing	describe	VERB
cana-803	72	14	how	how	SCONJ
cana-803	72	15	network	network	NOUN
cana-803	72	16	events	event	NOUN
cana-803	72	17	depend	depend	VERB
cana-803	72	18	on	on	ADP
cana-803	72	19	each	each	DET
cana-803	72	20	other	other	ADJ
cana-803	72	21	.	.	PUNCT
cana-803	73	1	because	because	SCONJ
cana-803	73	2	cyber	cyber	NOUN
cana-803	73	3	-	-	PUNCT
cana-803	73	4	physical	physical	ADJ
cana-803	73	5	systems	system	NOUN
cana-803	73	6	(	(	PUNCT
cana-803	73	7	cps	cps	PROPN
cana-803	73	8	)	)	PUNCT
cana-803	73	9	are	be	AUX
cana-803	73	10	linked	link	VERB
cana-803	73	11	,	,	PUNCT
cana-803	73	12	they	they	PRON
cana-803	73	13	pose	pose	VERB
cana-803	73	14	special	special	ADJ
cana-803	73	15	security	security	NOUN
cana-803	73	16	challenges	challenge	NOUN
cana-803	73	17	.	.	PUNCT
cana-803	74	1	this	this	PRON
cana-803	74	2	has	have	AUX
cana-803	74	3	led	lead	VERB
cana-803	74	4	to	to	PART
cana-803	74	5	study	study	VERB
cana-803	74	6	efforts	effort	NOUN
cana-803	74	7	that	that	PRON
cana-803	74	8	describe	describe	VERB
cana-803	74	9	and	and	CCONJ
cana-803	74	10	look	look	VERB
cana-803	74	11	for	for	ADP
cana-803	74	12	security	security	NOUN
cana-803	74	13	holes	hole	NOUN
cana-803	74	14	in	in	ADP
cana-803	74	15	cps	cps	PROPN
cana-803	74	16	[	[	X
cana-803	74	17	9	9	NUM
cana-803	74	18	]	]	PUNCT
cana-803	74	19	.	.	PUNCT
cana-803	75	1	system	system	NOUN
cana-803	75	2	models	model	NOUN
cana-803	75	3	and	and	CCONJ
cana-803	75	4	cyberphysical	cyberphysical	ADJ
cana-803	75	5	systems	system	NOUN
cana-803	75	6	analysis	analysis	NOUN
cana-803	75	7	are	be	AUX
cana-803	75	8	used	use	VERB
cana-803	75	9	in	in	ADP
cana-803	75	10	these	these	DET
cana-803	75	11	studies	study	NOUN
cana-803	75	12	to	to	PART
cana-803	75	13	find	find	VERB
cana-803	75	14	and	and	CCONJ
cana-803	75	15	stop	stop	VERB
cana-803	75	16	possible	possible	ADJ
cana-803	75	17	threats	threat	NOUN
cana-803	75	18	.	.	PUNCT
cana-803	76	1	collaborationbased	collaborationbase	VERB
cana-803	76	2	attack	attack	NOUN
cana-803	76	3	detection	detection	NOUN
cana-803	76	4	in	in	ADP
cana-803	76	5	spread	spread	VERB
cana-803	76	6	-	-	PUNCT
cana-803	76	7	out	out	ADP
cana-803	76	8	networks	network	NOUN
cana-803	76	9	has	have	AUX
cana-803	76	10	also	also	ADV
cana-803	76	11	become	become	VERB
cana-803	76	12	an	an	DET
cana-803	76	13	interesting	interesting	ADJ
cana-803	76	14	way	way	NOUN
cana-803	76	15	to	to	PART
cana-803	76	16	improve	improve	VERB
cana-803	76	17	detection	detection	NOUN
cana-803	76	18	rates	rate	NOUN
cana-803	76	19	[	[	X
cana-803	76	20	10	10	NUM
cana-803	76	21	]	]	PUNCT
cana-803	76	22	.	.	PUNCT
cana-803	77	1	the	the	DET
cana-803	77	2	general	general	ADJ
cana-803	77	3	strength	strength	NOUN
cana-803	77	4	of	of	ADP
cana-803	77	5	network	network	NOUN
cana-803	77	6	defenses	defense	NOUN
cana-803	77	7	is	be	AUX
cana-803	77	8	increased	increase	VERB
cana-803	77	9	by	by	ADP
cana-803	77	10	joint	joint	ADJ
cana-803	77	11	detecting	detect	VERB
cana-803	77	12	methods	method	NOUN
cana-803	77	13	,	,	PUNCT
cana-803	77	14	which	which	PRON
cana-803	77	15	make	make	VERB
cana-803	77	16	it	it	PRON
cana-803	77	17	easier	easy	ADJ
cana-803	77	18	for	for	ADP
cana-803	77	19	ids	id	NOUN
cana-803	77	20	that	that	PRON
cana-803	77	21	are	be	AUX
cana-803	77	22	spread	spread	VERB
cana-803	77	23	out	out	ADP
cana-803	77	24	to	to	PART
cana-803	77	25	work	work	VERB
cana-803	77	26	together	together	ADV
cana-803	77	27	.	.	PUNCT
cana-803	78	1	communications	communication	NOUN
cana-803	78	2	on	on	ADP
cana-803	78	3	applied	apply	VERB
cana-803	78	4	nonlinear	nonlinear	ADJ
cana-803	78	5	analysis	analysis	NOUN
cana-803	78	6	issn	issn	NOUN
cana-803	78	7	:	:	PUNCT
cana-803	78	8	1074	1074	NUM
cana-803	78	9	-	-	PUNCT
cana-803	78	10	133x	133x	NUM
cana-803	78	11	vol	vol	NOUN
cana-803	78	12	31	31	NUM
cana-803	78	13	no	no	NOUN
cana-803	78	14	.	.	PUNCT
cana-803	79	1	3s	3s	NUM
cana-803	79	2	(	(	PUNCT
cana-803	79	3	2024	2024	NUM
cana-803	79	4	)	)	PUNCT
cana-803	79	5	490	490	NUM
cana-803	79	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-803	79	7	through	through	ADP
cana-803	79	8	modeling	model	VERB
cana-803	79	9	studies	study	NOUN
cana-803	79	10	and	and	CCONJ
cana-803	79	11	data	datum	NOUN
cana-803	79	12	analysis	analysis	NOUN
cana-803	79	13	[	[	X
cana-803	79	14	11	11	NUM
cana-803	79	15	]	]	PUNCT
cana-803	79	16	,	,	PUNCT
cana-803	79	17	performance	performance	NOUN
cana-803	79	18	review	review	NOUN
cana-803	79	19	studies	study	NOUN
cana-803	79	20	compare	compare	VERB
cana-803	79	21	different	different	ADJ
cana-803	79	22	intruder	intruder	NOUN
cana-803	79	23	detection	detection	NOUN
cana-803	79	24	algorithms	algorithm	NOUN
cana-803	79	25	and	and	CCONJ
cana-803	79	26	methods	method	NOUN
cana-803	79	27	.	.	PUNCT
cana-803	80	1	the	the	DET
cana-803	80	2	results	result	NOUN
cana-803	80	3	of	of	ADP
cana-803	80	4	these	these	DET
cana-803	80	5	studies	study	NOUN
cana-803	80	6	help	help	VERB
cana-803	80	7	us	we	PRON
cana-803	80	8	understand	understand	VERB
cana-803	80	9	the	the	DET
cana-803	80	10	pros	pro	NOUN
cana-803	80	11	and	and	CCONJ
cana-803	80	12	cons	con	NOUN
cana-803	80	13	of	of	ADP
cana-803	80	14	various	various	ADJ
cana-803	80	15	methods	method	NOUN
cana-803	80	16	,	,	PUNCT
cana-803	80	17	which	which	PRON
cana-803	80	18	helps	help	VERB
cana-803	80	19	us	we	PRON
cana-803	80	20	create	create	VERB
cana-803	80	21	better	well	ADJ
cana-803	80	22	recognition	recognition	NOUN
cana-803	80	23	systems	system	NOUN
cana-803	80	24	.	.	PUNCT
cana-803	81	1	software	software	NOUN
cana-803	81	2	-	-	PUNCT
cana-803	81	3	defined	define	VERB
cana-803	81	4	networking	networking	NOUN
cana-803	81	5	also	also	ADV
cana-803	81	6	lets	let	VERB
cana-803	81	7	security	security	NOUN
cana-803	81	8	rules	rule	NOUN
cana-803	81	9	change	change	NOUN
cana-803	81	10	based	base	VERB
cana-803	81	11	on	on	ADP
cana-803	81	12	real	real	ADJ
cana-803	81	13	-	-	PUNCT
cana-803	81	14	time	time	NOUN
cana-803	81	15	knowledge	knowledge	NOUN
cana-803	81	16	about	about	ADP
cana-803	81	17	the	the	DET
cana-803	81	18	state	state	NOUN
cana-803	81	19	of	of	ADP
cana-803	81	20	the	the	DET
cana-803	81	21	network	network	NOUN
cana-803	81	22	[	[	X
cana-803	81	23	12	12	NUM
cana-803	81	24	]	]	PUNCT
cana-803	81	25	.	.	PUNCT
cana-803	82	1	organizations	organization	NOUN
cana-803	82	2	can	can	AUX
cana-803	82	3	better	well	ADV
cana-803	82	4	deal	deal	VERB
cana-803	82	5	with	with	ADP
cana-803	82	6	new	new	ADJ
cana-803	82	7	threats	threat	NOUN
cana-803	82	8	when	when	SCONJ
cana-803	82	9	they	they	PRON
cana-803	82	10	constantly	constantly	ADV
cana-803	82	11	change	change	VERB
cana-803	82	12	their	their	PRON
cana-803	82	13	security	security	NOUN
cana-803	82	14	settings	setting	NOUN
cana-803	82	15	.	.	PUNCT
cana-803	83	1	network	network	NOUN
cana-803	83	2	flow	flow	NOUN
cana-803	83	3	analysis	analysis	NOUN
cana-803	83	4	methods	method	NOUN
cana-803	83	5	have	have	AUX
cana-803	83	6	been	be	AUX
cana-803	83	7	used	use	VERB
cana-803	83	8	to	to	PART
cana-803	83	9	find	find	VERB
cana-803	83	10	strange	strange	ADJ
cana-803	83	11	trends	trend	NOUN
cana-803	83	12	in	in	ADP
cana-803	83	13	network	network	NOUN
cana-803	83	14	data	datum	NOUN
cana-803	83	15	,	,	PUNCT
cana-803	83	16	which	which	PRON
cana-803	83	17	has	have	AUX
cana-803	83	18	helped	help	VERB
cana-803	83	19	find	find	VERB
cana-803	83	20	suspicious	suspicious	ADJ
cana-803	83	21	behaviors	behavior	NOUN
cana-803	83	22	and	and	CCONJ
cana-803	83	23	possible	possible	ADJ
cana-803	83	24	attacks	attack	NOUN
cana-803	83	25	[	[	X
cana-803	83	26	13	13	NUM
cana-803	83	27	]	]	PUNCT
cana-803	83	28	.	.	PUNCT
cana-803	84	1	cyber	cyber	PROPN
cana-803	84	2	threat	threat	NOUN
cana-803	84	3	intelligence	intelligence	NOUN
cana-803	84	4	has	have	AUX
cana-803	84	5	also	also	ADV
cana-803	84	6	made	make	VERB
cana-803	84	7	it	it	PRON
cana-803	84	8	possible	possible	ADJ
cana-803	84	9	to	to	PART
cana-803	84	10	take	take	VERB
cana-803	84	11	strategic	strategic	ADJ
cana-803	84	12	defenses	defense	NOUN
cana-803	84	13	by	by	ADP
cana-803	84	14	predicting	predict	VERB
cana-803	84	15	future	future	ADJ
cana-803	84	16	attack	attack	NOUN
cana-803	84	17	routes	route	NOUN
cana-803	84	18	using	use	VERB
cana-803	84	19	threat	threat	NOUN
cana-803	84	20	intelligence	intelligence	NOUN
cana-803	84	21	feeds	feed	VERB
cana-803	84	22	and	and	CCONJ
cana-803	84	23	prediction	prediction	NOUN
cana-803	84	24	analytics	analytic	NOUN
cana-803	84	25	[	[	X
cana-803	84	26	14	14	NUM
cana-803	84	27	]	]	PUNCT
cana-803	84	28	.	.	PUNCT
cana-803	85	1	finally	finally	ADV
cana-803	85	2	,	,	PUNCT
cana-803	85	3	incident	incident	NOUN
cana-803	85	4	response	response	NOUN
cana-803	85	5	coordination	coordination	NOUN
cana-803	85	6	systems	system	NOUN
cana-803	85	7	make	make	VERB
cana-803	85	8	it	it	PRON
cana-803	85	9	easy	easy	ADJ
cana-803	85	10	for	for	SCONJ
cana-803	85	11	companies	company	NOUN
cana-803	85	12	to	to	PART
cana-803	85	13	deal	deal	VERB
cana-803	85	14	with	with	ADP
cana-803	85	15	risks	risk	NOUN
cana-803	85	16	by	by	ADP
cana-803	85	17	automatically	automatically	ADV
cana-803	85	18	triggering	trigger	VERB
cana-803	85	19	responses	response	NOUN
cana-803	85	20	based	base	VERB
cana-803	85	21	on	on	ADP
cana-803	85	22	how	how	SCONJ
cana-803	85	23	bad	bad	ADJ
cana-803	85	24	the	the	DET
cana-803	85	25	events	event	NOUN
cana-803	85	26	are	be	AUX
cana-803	85	27	[	[	X
cana-803	85	28	15	15	NUM
cana-803	85	29	]	]	PUNCT
cana-803	85	30	.	.	PUNCT
cana-803	86	1	table	table	NOUN
cana-803	86	2	1	1	NUM
cana-803	86	3	:	:	PUNCT
cana-803	86	4	related	relate	VERB
cana-803	86	5	work	work	NOUN
cana-803	86	6	scope	scope	NOUN
cana-803	86	7	findings	finding	VERB
cana-803	86	8	methods	method	NOUN
cana-803	86	9	modeling	model	VERB
cana-803	86	10	cyber	cyber	NOUN
cana-803	86	11	-	-	PUNCT
cana-803	86	12	attack	attack	NOUN
cana-803	86	13	behaviors	behavior	NOUN
cana-803	86	14	using	use	VERB
cana-803	86	15	stochastic	stochastic	ADJ
cana-803	86	16	processes	process	NOUN
cana-803	86	17	identified	identify	VERB
cana-803	86	18	temporal	temporal	ADJ
cana-803	86	19	patterns	pattern	NOUN
cana-803	86	20	in	in	ADP
cana-803	86	21	attack	attack	NOUN
cana-803	86	22	behaviors	behavior	NOUN
cana-803	86	23	markov	markov	NOUN
cana-803	86	24	chains	chain	NOUN
cana-803	86	25	,	,	PUNCT
cana-803	86	26	hidden	hide	VERB
cana-803	86	27	markov	markov	NOUN
cana-803	86	28	models	model	NOUN
cana-803	86	29	probabilistic	probabilistic	VERB
cana-803	86	30	analysis	analysis	NOUN
cana-803	86	31	of	of	ADP
cana-803	86	32	network	network	NOUN
cana-803	86	33	traffic	traffic	NOUN
cana-803	86	34	for	for	ADP
cana-803	86	35	intrusion	intrusion	NOUN
cana-803	86	36	detection	detection	NOUN
cana-803	86	37	quantified	quantify	VERB
cana-803	86	38	uncertainties	uncertainty	NOUN
cana-803	86	39	in	in	ADP
cana-803	86	40	network	network	NOUN
cana-803	86	41	traffic	traffic	NOUN
cana-803	86	42	behavior	behavior	NOUN
cana-803	86	43	probability	probability	NOUN
cana-803	86	44	theory	theory	NOUN
cana-803	86	45	,	,	PUNCT
cana-803	86	46	statistical	statistical	ADJ
cana-803	86	47	analysis	analysis	NOUN
cana-803	86	48	adaptive	adaptive	ADJ
cana-803	86	49	defense	defense	NOUN
cana-803	86	50	strategies	strategy	NOUN
cana-803	86	51	against	against	ADP
cana-803	86	52	cyber	cyber	NOUN
cana-803	86	53	threats	threat	NOUN
cana-803	86	54	demonstrated	demonstrate	VERB
cana-803	86	55	effectiveness	effectiveness	NOUN
cana-803	86	56	of	of	ADP
cana-803	86	57	adaptive	adaptive	ADJ
cana-803	86	58	response	response	NOUN
cana-803	86	59	mechanisms	mechanism	NOUN
cana-803	86	60	stochastic	stochastic	ADJ
cana-803	86	61	optimization	optimization	NOUN
cana-803	86	62	,	,	PUNCT
cana-803	86	63	dynamic	dynamic	ADJ
cana-803	86	64	resource	resource	NOUN
cana-803	86	65	allocation	allocation	NOUN
cana-803	86	66	anomaly	anomaly	NOUN
cana-803	86	67	detection	detection	NOUN
cana-803	86	68	using	use	VERB
cana-803	86	69	queuing	queue	VERB
cana-803	86	70	models	model	NOUN
cana-803	86	71	for	for	ADP
cana-803	86	72	network	network	NOUN
cana-803	86	73	security	security	NOUN
cana-803	86	74	improved	improve	VERB
cana-803	86	75	detection	detection	NOUN
cana-803	86	76	accuracy	accuracy	NOUN
cana-803	86	77	by	by	ADP
cana-803	86	78	modeling	model	VERB
cana-803	86	79	resource	resource	NOUN
cana-803	86	80	utilization	utilization	NOUN
cana-803	86	81	queuing	queue	VERB
cana-803	86	82	theory	theory	NOUN
cana-803	86	83	,	,	PUNCT
cana-803	86	84	anomaly	anomaly	NOUN
cana-803	86	85	detection	detection	NOUN
cana-803	86	86	algorithms	algorithm	NOUN
cana-803	86	87	machine	machine	NOUN
cana-803	86	88	learning	learn	VERB
cana-803	86	89	techniques	technique	NOUN
cana-803	86	90	for	for	ADP
cana-803	86	91	intrusion	intrusion	NOUN
cana-803	86	92	detection	detection	NOUN
cana-803	86	93	leveraged	leverage	VERB
cana-803	86	94	stochastic	stochastic	ADJ
cana-803	86	95	gradient	gradient	ADJ
cana-803	86	96	descent	descent	NOUN
cana-803	86	97	for	for	ADP
cana-803	86	98	model	model	NOUN
cana-803	86	99	training	training	NOUN
cana-803	86	100	stochastic	stochastic	ADJ
cana-803	86	101	gradient	gradient	ADJ
cana-803	86	102	descent	descent	NOUN
cana-803	86	103	,	,	PUNCT
cana-803	86	104	supervised	supervise	VERB
cana-803	86	105	learning	learn	VERB
cana-803	86	106	algorithms	algorithm	NOUN
cana-803	86	107	game	game	NOUN
cana-803	86	108	-	-	PUNCT
cana-803	86	109	theoretic	theoretic	NOUN
cana-803	86	110	approaches	approach	NOUN
cana-803	86	111	to	to	PART
cana-803	86	112	cyber	cyber	VERB
cana-803	86	113	security	security	NOUN
cana-803	86	114	explored	explore	VERB
cana-803	86	115	optimal	optimal	ADJ
cana-803	86	116	strategies	strategy	NOUN
cana-803	86	117	in	in	ADP
cana-803	86	118	adversarial	adversarial	ADJ
cana-803	86	119	environments	environment	NOUN
cana-803	86	120	game	game	NOUN
cana-803	86	121	theory	theory	NOUN
cana-803	86	122	,	,	PUNCT
cana-803	86	123	nash	nash	PROPN
cana-803	86	124	equilibrium	equilibrium	NOUN
cana-803	86	125	behavioral	behavioral	ADJ
cana-803	86	126	analysis	analysis	NOUN
cana-803	86	127	for	for	ADP
cana-803	86	128	malware	malware	NOUN
cana-803	86	129	detection	detection	NOUN
cana-803	86	130	identified	identify	VERB
cana-803	86	131	behavioral	behavioral	ADJ
cana-803	86	132	signatures	signature	NOUN
cana-803	86	133	of	of	ADP
cana-803	86	134	malware	malware	NOUN
cana-803	86	135	infections	infection	NOUN
cana-803	86	136	machine	machine	NOUN
cana-803	86	137	learning	learning	NOUN
cana-803	86	138	,	,	PUNCT
cana-803	86	139	behavioral	behavioral	ADJ
cana-803	86	140	analysis	analysis	NOUN
cana-803	86	141	techniques	technique	NOUN
cana-803	86	142	intrusion	intrusion	NOUN
cana-803	86	143	detection	detection	NOUN
cana-803	86	144	using	use	VERB
cana-803	86	145	bayesian	bayesian	NOUN
cana-803	86	146	networks	network	NOUN
cana-803	86	147	improved	improve	VERB
cana-803	86	148	detection	detection	NOUN
cana-803	86	149	accuracy	accuracy	NOUN
cana-803	86	150	through	through	ADP
cana-803	86	151	probabilistic	probabilistic	ADJ
cana-803	86	152	reasoning	reasoning	NOUN
cana-803	86	153	bayesian	bayesian	NOUN
cana-803	86	154	networks	network	NOUN
cana-803	86	155	,	,	PUNCT
cana-803	86	156	probabilistic	probabilistic	ADJ
cana-803	86	157	graphical	graphical	ADJ
cana-803	86	158	models	model	NOUN
cana-803	86	159	modeling	model	VERB
cana-803	86	160	cyber	cyber	ADJ
cana-803	86	161	-	-	PUNCT
cana-803	86	162	physical	physical	ADJ
cana-803	86	163	systems	system	NOUN
cana-803	86	164	for	for	ADP
cana-803	86	165	security	security	NOUN
cana-803	86	166	analysis	analysis	NOUN
cana-803	86	167	addressed	address	VERB
cana-803	86	168	vulnerabilities	vulnerability	NOUN
cana-803	86	169	in	in	ADP
cana-803	86	170	interconnected	interconnected	ADJ
cana-803	86	171	systems	system	NOUN
cana-803	86	172	system	system	NOUN
cana-803	86	173	modeling	modeling	NOUN
cana-803	86	174	,	,	PUNCT
cana-803	86	175	cyber	cyber	NOUN
cana-803	86	176	-	-	PUNCT
cana-803	86	177	physical	physical	ADJ
cana-803	86	178	systems	system	NOUN
cana-803	86	179	analysis	analysis	NOUN
cana-803	86	180	collaborative	collaborative	ADJ
cana-803	86	181	intrusion	intrusion	NOUN
cana-803	86	182	detection	detection	NOUN
cana-803	86	183	in	in	ADP
cana-803	86	184	distributed	distribute	VERB
cana-803	86	185	networks	network	NOUN
cana-803	86	186	investigated	investigate	VERB
cana-803	86	187	cooperation	cooperation	NOUN
cana-803	86	188	among	among	ADP
cana-803	86	189	ids	id	NOUN
cana-803	86	190	for	for	ADP
cana-803	86	191	enhanced	enhanced	ADJ
cana-803	86	192	detection	detection	NOUN
cana-803	86	193	distributed	distribute	VERB
cana-803	86	194	systems	system	NOUN
cana-803	86	195	,	,	PUNCT
cana-803	86	196	collaboration	collaboration	NOUN
cana-803	86	197	algorithms	algorithm	NOUN
cana-803	86	198	performance	performance	NOUN
cana-803	86	199	evaluation	evaluation	NOUN
cana-803	86	200	of	of	ADP
cana-803	86	201	intrusion	intrusion	NOUN
cana-803	86	202	detection	detection	NOUN
cana-803	86	203	systems	system	NOUN
cana-803	86	204	benchmarking	benchmarke	VERB
cana-803	86	205	various	various	ADJ
cana-803	86	206	detection	detection	NOUN
cana-803	86	207	algorithms	algorithm	NOUN
cana-803	86	208	and	and	CCONJ
cana-803	86	209	techniques	technique	NOUN
cana-803	86	210	simulation	simulation	NOUN
cana-803	86	211	studies	study	NOUN
cana-803	86	212	,	,	PUNCT
cana-803	86	213	metrics	metric	NOUN
cana-803	86	214	analysis	analysis	NOUN
cana-803	86	215	software	software	NOUN
cana-803	86	216	-	-	PUNCT
cana-803	86	217	defined	define	VERB
cana-803	86	218	networking	networking	NOUN
cana-803	86	219	for	for	ADP
cana-803	86	220	adaptive	adaptive	ADJ
cana-803	86	221	security	security	NOUN
cana-803	86	222	implemented	implement	VERB
cana-803	86	223	dynamic	dynamic	ADJ
cana-803	86	224	security	security	NOUN
cana-803	86	225	policies	policy	NOUN
cana-803	86	226	based	base	VERB
cana-803	86	227	on	on	ADP
cana-803	86	228	network	network	NOUN
cana-803	86	229	state	state	NOUN
cana-803	86	230	software	software	NOUN
cana-803	86	231	-	-	PUNCT
cana-803	86	232	defined	define	VERB
cana-803	86	233	networking	networking	NOUN
cana-803	86	234	,	,	PUNCT
cana-803	86	235	policy	policy	NOUN
cana-803	86	236	-	-	PUNCT
cana-803	86	237	based	base	VERB
cana-803	86	238	management	management	NOUN
cana-803	86	239	network	network	NOUN
cana-803	86	240	flow	flow	NOUN
cana-803	86	241	analysis	analysis	NOUN
cana-803	86	242	for	for	ADP
cana-803	86	243	anomaly	anomaly	NOUN
cana-803	86	244	detection	detection	NOUN
cana-803	86	245	detected	detect	VERB
cana-803	86	246	deviations	deviation	NOUN
cana-803	86	247	in	in	ADP
cana-803	86	248	network	network	NOUN
cana-803	86	249	flow	flow	NOUN
cana-803	86	250	patterns	pattern	NOUN
cana-803	86	251	flow	flow	VERB
cana-803	86	252	analysis	analysis	NOUN
cana-803	86	253	,	,	PUNCT
cana-803	86	254	statistical	statistical	ADJ
cana-803	86	255	anomaly	anomaly	NOUN
cana-803	86	256	detection	detection	NOUN
cana-803	86	257	cyber	cyber	NOUN
cana-803	86	258	threat	threat	NOUN
cana-803	86	259	intelligence	intelligence	NOUN
cana-803	86	260	for	for	ADP
cana-803	86	261	proactive	proactive	ADJ
cana-803	86	262	defense	defense	NOUN
cana-803	86	263	utilized	utilize	VERB
cana-803	86	264	threat	threat	NOUN
cana-803	86	265	intelligence	intelligence	NOUN
cana-803	86	266	to	to	PART
cana-803	86	267	anticipate	anticipate	VERB
cana-803	86	268	future	future	ADJ
cana-803	86	269	attacks	attack	NOUN
cana-803	86	270	threat	threat	NOUN
cana-803	86	271	intelligence	intelligence	NOUN
cana-803	86	272	,	,	PUNCT
cana-803	86	273	predictive	predictive	ADJ
cana-803	86	274	analytics	analytic	NOUN
cana-803	86	275	intrusion	intrusion	NOUN
cana-803	86	276	response	response	NOUN
cana-803	86	277	orchestration	orchestration	NOUN
cana-803	86	278	for	for	ADP
cana-803	86	279	incident	incident	NOUN
cana-803	86	280	management	management	NOUN
cana-803	86	281	orchestrated	orchestrate	VERB
cana-803	86	282	response	response	NOUN
cana-803	86	283	actions	action	NOUN
cana-803	86	284	based	base	VERB
cana-803	86	285	on	on	ADP
cana-803	86	286	severity	severity	NOUN
cana-803	86	287	of	of	ADP
cana-803	86	288	incidents	incident	NOUN
cana-803	86	289	incident	incident	NOUN
cana-803	86	290	response	response	NOUN
cana-803	86	291	,	,	PUNCT
cana-803	86	292	automated	automate	VERB
cana-803	86	293	orchestration	orchestration	NOUN
cana-803	86	294	systems	system	NOUN
cana-803	86	295	communications	communication	NOUN
cana-803	86	296	on	on	ADP
cana-803	86	297	applied	apply	VERB
cana-803	86	298	nonlinear	nonlinear	ADJ
cana-803	86	299	analysis	analysis	NOUN
cana-803	86	300	issn	issn	NOUN
cana-803	86	301	:	:	PUNCT
cana-803	86	302	1074	1074	NUM
cana-803	86	303	-	-	PUNCT
cana-803	86	304	133x	133x	NUM
cana-803	86	305	vol	vol	NOUN
cana-803	86	306	31	31	NUM
cana-803	86	307	no	no	NOUN
cana-803	86	308	.	.	PUNCT
cana-803	87	1	3s	3s	NUM
cana-803	87	2	(	(	PUNCT
cana-803	87	3	2024	2024	NUM
cana-803	87	4	)	)	PUNCT
cana-803	87	5	491	491	NUM
cana-803	87	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-803	87	7	overall	overall	ADJ
cana-803	87	8	,	,	PUNCT
cana-803	87	9	these	these	DET
cana-803	87	10	studies	study	NOUN
cana-803	87	11	show	show	VERB
cana-803	87	12	that	that	SCONJ
cana-803	87	13	cyber	cyber	ADJ
cana-803	87	14	security	security	NOUN
cana-803	87	15	research	research	NOUN
cana-803	87	16	is	be	AUX
cana-803	87	17	multidisciplinary	multidisciplinary	ADJ
cana-803	87	18	and	and	CCONJ
cana-803	87	19	that	that	SCONJ
cana-803	87	20	it	it	PRON
cana-803	87	21	's	be	AUX
cana-803	87	22	important	important	ADJ
cana-803	87	23	to	to	PART
cana-803	87	24	use	use	VERB
cana-803	87	25	a	a	DET
cana-803	87	26	variety	variety	NOUN
cana-803	87	27	of	of	ADP
cana-803	87	28	methods	method	NOUN
cana-803	87	29	to	to	PART
cana-803	87	30	create	create	VERB
cana-803	87	31	effective	effective	ADJ
cana-803	87	32	systems	system	NOUN
cana-803	87	33	for	for	ADP
cana-803	87	34	finding	find	VERB
cana-803	87	35	intrusions	intrusion	NOUN
cana-803	87	36	and	and	CCONJ
cana-803	87	37	responding	respond	VERB
cana-803	87	38	to	to	ADP
cana-803	87	39	them	they	PRON
cana-803	87	40	.	.	PUNCT
cana-803	88	1	researchers	researcher	NOUN
cana-803	88	2	keep	keep	VERB
cana-803	88	3	pushing	push	VERB
cana-803	88	4	the	the	DET
cana-803	88	5	limits	limit	NOUN
cana-803	88	6	of	of	ADP
cana-803	88	7	cyber	cyber	ADJ
cana-803	88	8	security	security	NOUN
cana-803	88	9	by	by	ADP
cana-803	88	10	mixing	mix	VERB
cana-803	88	11	ideas	idea	NOUN
cana-803	88	12	from	from	ADP
cana-803	88	13	random	random	ADJ
cana-803	88	14	modeling	modeling	NOUN
cana-803	88	15	,	,	PUNCT
cana-803	88	16	machine	machine	NOUN
cana-803	88	17	learning	learning	NOUN
cana-803	88	18	,	,	PUNCT
cana-803	88	19	network	network	NOUN
cana-803	88	20	analysis	analysis	NOUN
cana-803	88	21	,	,	PUNCT
cana-803	88	22	and	and	CCONJ
cana-803	88	23	other	other	ADJ
cana-803	88	24	areas	area	NOUN
cana-803	88	25	.	.	PUNCT
cana-803	89	1	this	this	PRON
cana-803	89	2	makes	make	VERB
cana-803	89	3	digital	digital	ADJ
cana-803	89	4	infrastructure	infrastructure	NOUN
cana-803	89	5	more	more	ADV
cana-803	89	6	resistant	resistant	ADJ
cana-803	89	7	to	to	ADP
cana-803	89	8	new	new	ADJ
cana-803	89	9	cyber	cyber	NOUN
cana-803	89	10	dangers	danger	NOUN
cana-803	89	11	.	.	PUNCT
cana-803	90	1	3.methodology	3.methodology	NUM
cana-803	90	2	1	1	NUM
cana-803	90	3	.	.	PUNCT
cana-803	90	4	data	datum	NOUN
cana-803	90	5	collection	collection	NOUN
cana-803	90	6	and	and	CCONJ
cana-803	90	7	preprocessing	preprocessing	NOUN
cana-803	90	8	:	:	PUNCT
cana-803	90	9	figure	figure	NOUN
cana-803	90	10	1	1	NUM
cana-803	90	11	shows	show	VERB
cana-803	90	12	the	the	DET
cana-803	90	13	data	datum	NOUN
cana-803	90	14	collection	collection	NOUN
cana-803	90	15	and	and	CCONJ
cana-803	90	16	preparation	preparation	NOUN
cana-803	90	17	step	step	NOUN
cana-803	90	18	.	.	PUNCT
cana-803	91	1	the	the	DET
cana-803	91	2	main	main	ADJ
cana-803	91	3	goal	goal	NOUN
cana-803	91	4	is	be	AUX
cana-803	91	5	to	to	PART
cana-803	91	6	collect	collect	VERB
cana-803	91	7	all	all	DET
cana-803	91	8	the	the	DET
cana-803	91	9	network	network	NOUN
cana-803	91	10	traffic	traffic	NOUN
cana-803	91	11	data	datum	NOUN
cana-803	91	12	,	,	PUNCT
cana-803	91	13	which	which	PRON
cana-803	91	14	includes	include	VERB
cana-803	91	15	packet	packet	ADJ
cana-803	91	16	labels	label	NOUN
cana-803	91	17	,	,	PUNCT
cana-803	91	18	connection	connection	NOUN
cana-803	91	19	logs	log	NOUN
cana-803	91	20	,	,	PUNCT
cana-803	91	21	and	and	CCONJ
cana-803	91	22	any	any	DET
cana-803	91	23	other	other	ADJ
cana-803	91	24	information	information	NOUN
cana-803	91	25	that	that	PRON
cana-803	91	26	can	can	AUX
cana-803	91	27	help	help	VERB
cana-803	91	28	find	find	VERB
cana-803	91	29	cyberattacks	cyberattack	NOUN
cana-803	91	30	.	.	PUNCT
cana-803	92	1	packet	packet	NOUN
cana-803	92	2	headers	header	NOUN
cana-803	92	3	hold	hold	VERB
cana-803	92	4	important	important	ADJ
cana-803	92	5	information	information	NOUN
cana-803	92	6	like	like	ADP
cana-803	92	7	source	source	NOUN
cana-803	92	8	and	and	CCONJ
cana-803	92	9	target	target	VERB
cana-803	92	10	ip	ip	DET
cana-803	92	11	addresses	address	NOUN
cana-803	92	12	,	,	PUNCT
cana-803	92	13	port	port	NOUN
cana-803	92	14	numbers	number	NOUN
cana-803	92	15	,	,	PUNCT
cana-803	92	16	protocol	protocol	NOUN
cana-803	92	17	types	type	NOUN
cana-803	92	18	,	,	PUNCT
cana-803	92	19	and	and	CCONJ
cana-803	92	20	timestamps	timestamp	VERB
cana-803	92	21	.	.	PUNCT
cana-803	93	1	this	this	DET
cana-803	93	2	information	information	NOUN
cana-803	93	3	gives	give	VERB
cana-803	93	4	us	we	PRON
cana-803	93	5	important	important	ADJ
cana-803	93	6	clues	clue	NOUN
cana-803	93	7	about	about	ADP
cana-803	93	8	how	how	SCONJ
cana-803	93	9	networks	network	NOUN
cana-803	93	10	communicate	communicate	VERB
cana-803	93	11	.	.	PUNCT
cana-803	94	1	connection	connection	NOUN
cana-803	94	2	logs	log	NOUN
cana-803	94	3	keep	keep	VERB
cana-803	94	4	track	track	NOUN
cana-803	94	5	of	of	ADP
cana-803	94	6	information	information	NOUN
cana-803	94	7	about	about	ADP
cana-803	94	8	established	establish	VERB
cana-803	94	9	network	network	NOUN
cana-803	94	10	links	link	NOUN
cana-803	94	11	,	,	PUNCT
cana-803	94	12	such	such	ADJ
cana-803	94	13	as	as	ADP
cana-803	94	14	how	how	SCONJ
cana-803	94	15	long	long	ADV
cana-803	94	16	a	a	DET
cana-803	94	17	session	session	NOUN
cana-803	94	18	lasts	last	VERB
cana-803	94	19	,	,	PUNCT
cana-803	94	20	how	how	SCONJ
cana-803	94	21	fast	fast	ADJ
cana-803	94	22	data	datum	NOUN
cana-803	94	23	is	be	AUX
cana-803	94	24	transferred	transfer	VERB
cana-803	94	25	,	,	PUNCT
cana-803	94	26	and	and	CCONJ
cana-803	94	27	which	which	DET
cana-803	94	28	application	application	NOUN
cana-803	94	29	layer	layer	NOUN
cana-803	94	30	protocols	protocol	NOUN
cana-803	94	31	are	be	AUX
cana-803	94	32	used	use	VERB
cana-803	94	33	.	.	PUNCT
cana-803	95	1	to	to	PART
cana-803	95	2	make	make	VERB
cana-803	95	3	the	the	DET
cana-803	95	4	information	information	NOUN
cana-803	95	5	even	even	ADV
cana-803	95	6	better	well	ADJ
cana-803	95	7	,	,	PUNCT
cana-803	95	8	extra	extra	ADJ
cana-803	95	9	data	datum	NOUN
cana-803	95	10	sources	source	NOUN
cana-803	95	11	like	like	ADP
cana-803	95	12	server	server	NOUN
cana-803	95	13	logs	log	NOUN
cana-803	95	14	,	,	PUNCT
cana-803	95	15	firewall	firewall	NOUN
cana-803	95	16	logs	log	NOUN
cana-803	95	17	,	,	PUNCT
cana-803	95	18	and	and	CCONJ
cana-803	95	19	intruder	intruder	NOUN
cana-803	95	20	detection	detection	NOUN
cana-803	95	21	system	system	NOUN
cana-803	95	22	reports	report	NOUN
cana-803	95	23	could	could	AUX
cana-803	95	24	be	be	AUX
cana-803	95	25	added	add	VERB
cana-803	95	26	.	.	PUNCT
cana-803	96	1	figure	figure	NOUN
cana-803	96	2	1	1	NUM
cana-803	96	3	:	:	PUNCT
cana-803	96	4	architectural	architectural	ADJ
cana-803	96	5	block	block	NOUN
cana-803	96	6	diagram	diagram	NOUN
cana-803	96	7	communications	communication	NOUN
cana-803	96	8	on	on	ADP
cana-803	96	9	applied	apply	VERB
cana-803	96	10	nonlinear	nonlinear	ADJ
cana-803	96	11	analysis	analysis	NOUN
cana-803	96	12	issn	issn	NOUN
cana-803	96	13	:	:	PUNCT
cana-803	96	14	1074	1074	NUM
cana-803	96	15	-	-	PUNCT
cana-803	96	16	133x	133x	NUM
cana-803	96	17	vol	vol	NOUN
cana-803	96	18	31	31	NUM
cana-803	96	19	no	no	NOUN
cana-803	96	20	.	.	PUNCT
cana-803	97	1	3s	3s	NUM
cana-803	97	2	(	(	PUNCT
cana-803	97	3	2024	2024	NUM
cana-803	97	4	)	)	PUNCT
cana-803	97	5	492	492	NUM
cana-803	97	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-803	97	7	after	after	SCONJ
cana-803	97	8	the	the	DET
cana-803	97	9	raw	raw	ADJ
cana-803	97	10	data	datum	NOUN
cana-803	97	11	is	be	AUX
cana-803	97	12	gathered	gather	VERB
cana-803	97	13	,	,	PUNCT
cana-803	97	14	it	it	PRON
cana-803	97	15	goes	go	VERB
cana-803	97	16	through	through	ADP
cana-803	97	17	a	a	DET
cana-803	97	18	series	series	NOUN
cana-803	97	19	of	of	ADP
cana-803	97	20	steps	step	NOUN
cana-803	97	21	called	call	VERB
cana-803	97	22	"	"	PUNCT
cana-803	97	23	preprocessing	preprocessing	NOUN
cana-803	97	24	"	"	PUNCT
cana-803	97	25	to	to	PART
cana-803	97	26	make	make	VERB
cana-803	97	27	sure	sure	ADJ
cana-803	97	28	it	it	PRON
cana-803	97	29	is	be	AUX
cana-803	97	30	good	good	ADJ
cana-803	97	31	enough	enough	ADV
cana-803	97	32	to	to	PART
cana-803	97	33	be	be	AUX
cana-803	97	34	analyzed	analyze	VERB
cana-803	97	35	.	.	PUNCT
cana-803	98	1	this	this	PRON
cana-803	98	2	includes	include	VERB
cana-803	98	3	getting	getting	AUX
cana-803	98	4	rid	rid	VERB
cana-803	98	5	of	of	ADP
cana-803	98	6	noise	noise	NOUN
cana-803	98	7	and	and	CCONJ
cana-803	98	8	information	information	NOUN
cana-803	98	9	that	that	PRON
cana-803	98	10	is	be	AUX
cana-803	98	11	n't	not	PART
cana-803	98	12	important	important	ADJ
cana-803	98	13	,	,	PUNCT
cana-803	98	14	dealing	deal	VERB
cana-803	98	15	with	with	ADP
cana-803	98	16	missing	miss	VERB
cana-803	98	17	values	value	NOUN
cana-803	98	18	,	,	PUNCT
cana-803	98	19	and	and	CCONJ
cana-803	98	20	fixing	fix	VERB
cana-803	98	21	the	the	DET
cana-803	98	22	style	style	NOUN
cana-803	98	23	so	so	SCONJ
cana-803	98	24	that	that	SCONJ
cana-803	98	25	it	it	PRON
cana-803	98	26	can	can	AUX
cana-803	98	27	be	be	AUX
cana-803	98	28	used	use	VERB
cana-803	98	29	more	more	ADV
cana-803	98	30	easily	easily	ADV
cana-803	98	31	in	in	ADP
cana-803	98	32	later	later	ADJ
cana-803	98	33	research	research	NOUN
cana-803	98	34	.	.	PUNCT
cana-803	99	1	noise	noise	NOUN
cana-803	99	2	,	,	PUNCT
cana-803	99	3	which	which	PRON
cana-803	99	4	includes	include	VERB
cana-803	99	5	data	datum	NOUN
cana-803	99	6	points	point	NOUN
cana-803	99	7	that	that	PRON
cana-803	99	8	are	be	AUX
cana-803	99	9	n't	not	PART
cana-803	99	10	important	important	ADJ
cana-803	99	11	or	or	CCONJ
cana-803	99	12	are	be	AUX
cana-803	99	13	wrong	wrong	ADJ
cana-803	99	14	,	,	PUNCT
cana-803	99	15	can	can	AUX
cana-803	99	16	change	change	VERB
cana-803	99	17	the	the	DET
cana-803	99	18	results	result	NOUN
cana-803	99	19	of	of	ADP
cana-803	99	20	a	a	DET
cana-803	99	21	study	study	NOUN
cana-803	99	22	and	and	CCONJ
cana-803	99	23	cause	cause	VERB
cana-803	99	24	wrong	wrong	ADJ
cana-803	99	25	conclusions	conclusion	NOUN
cana-803	99	26	to	to	PART
cana-803	99	27	be	be	AUX
cana-803	99	28	drawn	draw	VERB
cana-803	99	29	.	.	PUNCT
cana-803	100	1	to	to	PART
cana-803	100	2	keep	keep	VERB
cana-803	100	3	the	the	DET
cana-803	100	4	data	datum	NOUN
cana-803	100	5	correct	correct	ADJ
cana-803	100	6	,	,	PUNCT
cana-803	100	7	imputation	imputation	NOUN
cana-803	100	8	methods	method	NOUN
cana-803	100	9	like	like	ADP
cana-803	100	10	mean	mean	VERB
cana-803	100	11	imputation	imputation	NOUN
cana-803	100	12	or	or	CCONJ
cana-803	100	13	extrapolation	extrapolation	NOUN
cana-803	100	14	are	be	AUX
cana-803	100	15	used	use	VERB
cana-803	100	16	to	to	PART
cana-803	100	17	fill	fill	VERB
cana-803	100	18	in	in	ADP
cana-803	100	19	missing	miss	VERB
cana-803	100	20	numbers	number	NOUN
cana-803	100	21	if	if	SCONJ
cana-803	100	22	they	they	PRON
cana-803	100	23	are	be	AUX
cana-803	100	24	present	present	ADJ
cana-803	100	25	.	.	PUNCT
cana-803	101	1	standardizing	standardize	VERB
cana-803	101	2	the	the	DET
cana-803	101	3	format	format	NOUN
cana-803	101	4	means	mean	VERB
cana-803	101	5	making	make	VERB
cana-803	101	6	sure	sure	ADJ
cana-803	101	7	that	that	SCONJ
cana-803	101	8	the	the	DET
cana-803	101	9	way	way	NOUN
cana-803	101	10	the	the	DET
cana-803	101	11	data	data	NOUN
cana-803	101	12	is	be	AUX
cana-803	101	13	shown	show	VERB
cana-803	101	14	is	be	AUX
cana-803	101	15	always	always	ADV
cana-803	101	16	the	the	DET
cana-803	101	17	same	same	ADJ
cana-803	101	18	.	.	PUNCT
cana-803	102	1	for	for	ADP
cana-803	102	2	example	example	NOUN
cana-803	102	3	,	,	PUNCT
cana-803	102	4	category	category	NOUN
cana-803	102	5	variables	variable	NOUN
cana-803	102	6	must	must	AUX
cana-803	102	7	be	be	AUX
cana-803	102	8	encoded	encode	VERB
cana-803	102	9	,	,	PUNCT
cana-803	102	10	numerical	numerical	ADJ
cana-803	102	11	values	value	NOUN
cana-803	102	12	must	must	AUX
cana-803	102	13	be	be	AUX
cana-803	102	14	normalized	normalize	VERB
cana-803	102	15	,	,	PUNCT
cana-803	102	16	and	and	CCONJ
cana-803	102	17	timestamps	timestamp	NOUN
cana-803	102	18	must	must	AUX
cana-803	102	19	be	be	AUX
cana-803	102	20	converted	convert	VERB
cana-803	102	21	to	to	ADP
cana-803	102	22	a	a	DET
cana-803	102	23	standard	standard	ADJ
cana-803	102	24	format	format	NOUN
cana-803	102	25	so	so	SCONJ
cana-803	102	26	that	that	SCONJ
cana-803	102	27	they	they	PRON
cana-803	102	28	are	be	AUX
cana-803	102	29	all	all	ADV
cana-803	102	30	the	the	DET
cana-803	102	31	same	same	ADJ
cana-803	102	32	across	across	ADP
cana-803	102	33	the	the	DET
cana-803	102	34	dataset	dataset	NOUN
cana-803	102	35	.	.	PUNCT
cana-803	103	1	by	by	ADP
cana-803	103	2	carefully	carefully	ADV
cana-803	103	3	selecting	select	VERB
cana-803	103	4	and	and	CCONJ
cana-803	103	5	preparing	prepare	VERB
cana-803	103	6	the	the	DET
cana-803	103	7	network	network	NOUN
cana-803	103	8	traffic	traffic	NOUN
cana-803	103	9	data	datum	NOUN
cana-803	103	10	,	,	PUNCT
cana-803	103	11	we	we	PRON
cana-803	103	12	can	can	AUX
cana-803	103	13	lower	lower	VERB
cana-803	103	14	the	the	DET
cana-803	103	15	chance	chance	NOUN
cana-803	103	16	of	of	ADP
cana-803	103	17	bias	bias	NOUN
cana-803	103	18	and	and	CCONJ
cana-803	103	19	errors	error	NOUN
cana-803	103	20	in	in	ADP
cana-803	103	21	later	later	ADJ
cana-803	103	22	analysis	analysis	NOUN
cana-803	103	23	steps	step	NOUN
cana-803	103	24	.	.	PUNCT
cana-803	104	1	this	this	PRON
cana-803	104	2	creates	create	VERB
cana-803	104	3	a	a	DET
cana-803	104	4	solid	solid	ADJ
cana-803	104	5	base	base	NOUN
cana-803	104	6	for	for	ADP
cana-803	104	7	creating	create	VERB
cana-803	104	8	and	and	CCONJ
cana-803	104	9	testing	testing	NOUN
cana-803	104	10	intrusion	intrusion	NOUN
cana-803	104	11	detection	detection	NOUN
cana-803	104	12	models	model	NOUN
cana-803	104	13	.	.	PUNCT
cana-803	105	1	this	this	PRON
cana-803	105	2	makes	make	VERB
cana-803	105	3	sure	sure	ADJ
cana-803	105	4	that	that	SCONJ
cana-803	105	5	the	the	DET
cana-803	105	6	ideas	idea	NOUN
cana-803	105	7	gathered	gather	VERB
cana-803	105	8	from	from	ADP
cana-803	105	9	the	the	DET
cana-803	105	10	data	datum	NOUN
cana-803	105	11	correctly	correctly	ADV
cana-803	105	12	show	show	VERB
cana-803	105	13	how	how	SCONJ
cana-803	105	14	the	the	DET
cana-803	105	15	network	network	NOUN
cana-803	105	16	really	really	ADV
cana-803	105	17	works	work	VERB
cana-803	105	18	,	,	PUNCT
cana-803	105	19	which	which	PRON
cana-803	105	20	makes	make	VERB
cana-803	105	21	it	it	PRON
cana-803	105	22	easier	easy	ADJ
cana-803	105	23	to	to	PART
cana-803	105	24	find	find	VERB
cana-803	105	25	and	and	CCONJ
cana-803	105	26	stop	stop	VERB
cana-803	105	27	hacking	hack	VERB
cana-803	105	28	dangers	danger	NOUN
cana-803	105	29	.	.	PUNCT
cana-803	106	1	2	2	X
cana-803	106	2	.	.	X
cana-803	106	3	modeling	model	VERB
cana-803	106	4	network	network	NOUN
cana-803	106	5	traffic	traffic	NOUN
cana-803	106	6	:	:	PUNCT
cana-803	106	7	the	the	DET
cana-803	106	8	second	second	ADJ
cana-803	106	9	part	part	NOUN
cana-803	106	10	of	of	ADP
cana-803	106	11	the	the	DET
cana-803	106	12	suggested	suggest	VERB
cana-803	106	13	method	method	NOUN
cana-803	106	14	is	be	AUX
cana-803	106	15	modeling	model	VERB
cana-803	106	16	network	network	NOUN
cana-803	106	17	traffic	traffic	NOUN
cana-803	106	18	,	,	PUNCT
cana-803	106	19	which	which	PRON
cana-803	106	20	is	be	AUX
cana-803	106	21	shown	show	VERB
cana-803	106	22	in	in	ADP
cana-803	106	23	figure	figure	NOUN
cana-803	106	24	(	(	PUNCT
cana-803	106	25	1	1	NUM
cana-803	106	26	)	)	PUNCT
cana-803	106	27	.	.	PUNCT
cana-803	107	1	this	this	DET
cana-803	107	2	step	step	NOUN
cana-803	107	3	uses	use	VERB
cana-803	107	4	probability	probability	NOUN
cana-803	107	5	theory	theory	NOUN
cana-803	107	6	and	and	CCONJ
cana-803	107	7	queue	queue	NOUN
cana-803	107	8	theory	theory	NOUN
cana-803	107	9	to	to	PART
cana-803	107	10	understand	understand	VERB
cana-803	107	11	how	how	SCONJ
cana-803	107	12	networks	network	NOUN
cana-803	107	13	change	change	VERB
cana-803	107	14	over	over	ADP
cana-803	107	15	time	time	NOUN
cana-803	107	16	,	,	PUNCT
cana-803	107	17	which	which	PRON
cana-803	107	18	lets	let	VERB
cana-803	107	19	us	we	PRON
cana-803	107	20	find	find	VERB
cana-803	107	21	strange	strange	ADJ
cana-803	107	22	behavior	behavior	NOUN
cana-803	107	23	and	and	CCONJ
cana-803	107	24	possible	possible	ADJ
cana-803	107	25	cyberattacks	cyberattack	NOUN
cana-803	107	26	.	.	PUNCT
cana-803	108	1	probability	probability	NOUN
cana-803	108	2	theory	theory	NOUN
cana-803	108	3	is	be	AUX
cana-803	108	4	the	the	DET
cana-803	108	5	basis	basis	NOUN
cana-803	108	6	for	for	ADP
cana-803	108	7	describing	describe	VERB
cana-803	108	8	network	network	NOUN
cana-803	108	9	traffic	traffic	NOUN
cana-803	108	10	as	as	ADP
cana-803	108	11	a	a	DET
cana-803	108	12	random	random	ADJ
cana-803	108	13	process	process	NOUN
cana-803	108	14	,	,	PUNCT
cana-803	108	15	which	which	PRON
cana-803	108	16	takes	take	VERB
cana-803	108	17	into	into	ADP
cana-803	108	18	account	account	NOUN
cana-803	108	19	the	the	DET
cana-803	108	20	fact	fact	NOUN
cana-803	108	21	that	that	SCONJ
cana-803	108	22	data	datum	NOUN
cana-803	108	23	transfer	transfer	NOUN
cana-803	108	24	and	and	CCONJ
cana-803	108	25	communication	communication	NOUN
cana-803	108	26	patterns	pattern	NOUN
cana-803	108	27	are	be	AUX
cana-803	108	28	inherently	inherently	ADV
cana-803	108	29	unclear	unclear	ADJ
cana-803	108	30	and	and	CCONJ
cana-803	108	31	changeable	changeable	ADJ
cana-803	108	32	.	.	PUNCT
cana-803	109	1	by	by	ADP
cana-803	109	2	showing	show	VERB
cana-803	109	3	network	network	NOUN
cana-803	109	4	events	event	NOUN
cana-803	109	5	in	in	ADP
cana-803	109	6	terms	term	NOUN
cana-803	109	7	of	of	ADP
cana-803	109	8	probabilities	probability	NOUN
cana-803	109	9	,	,	PUNCT
cana-803	109	10	we	we	PRON
cana-803	109	11	can	can	AUX
cana-803	109	12	figure	figure	VERB
cana-803	109	13	out	out	ADP
cana-803	109	14	how	how	SCONJ
cana-803	109	15	likely	likely	ADJ
cana-803	109	16	different	different	ADJ
cana-803	109	17	scenarios	scenario	NOUN
cana-803	109	18	are	be	AUX
cana-803	109	19	and	and	CCONJ
cana-803	109	20	make	make	VERB
cana-803	109	21	predictions	prediction	NOUN
cana-803	109	22	about	about	ADP
cana-803	109	23	how	how	SCONJ
cana-803	109	24	the	the	DET
cana-803	109	25	network	network	NOUN
cana-803	109	26	will	will	AUX
cana-803	109	27	behave	behave	VERB
cana-803	109	28	in	in	ADP
cana-803	109	29	the	the	DET
cana-803	109	30	future	future	NOUN
cana-803	109	31	.	.	PUNCT
cana-803	110	1	network	network	NOUN
cana-803	110	2	traffic	traffic	NOUN
cana-803	110	3	can	can	AUX
cana-803	110	4	be	be	AUX
cana-803	110	5	thought	think	VERB
cana-803	110	6	of	of	ADP
cana-803	110	7	mathematically	mathematically	ADV
cana-803	110	8	as	as	ADP
cana-803	110	9	a	a	DET
cana-803	110	10	random	random	ADJ
cana-803	110	11	process	process	NOUN
cana-803	110	12	x(t	x(t	PROPN
cana-803	110	13	)	)	PUNCT
cana-803	110	14	,	,	PUNCT
cana-803	110	15	where	where	SCONJ
cana-803	110	16	t	t	PROPN
cana-803	110	17	is	be	AUX
cana-803	110	18	time	time	NOUN
cana-803	110	19	and	and	CCONJ
cana-803	110	20	x(t	x(t	PROPN
cana-803	110	21	)	)	PUNCT
cana-803	110	22	is	be	AUX
cana-803	110	23	the	the	DET
cana-803	110	24	network	network	NOUN
cana-803	110	25	's	's	PART
cana-803	110	26	state	state	NOUN
cana-803	110	27	at	at	ADP
cana-803	110	28	time	time	NOUN
cana-803	110	29	t.	t.	PROPN
cana-803	110	30	𝑋(𝑡	𝑋(𝑡	PROPN
cana-803	110	31	)	)	PUNCT
cana-803	110	32	=	=	NOUN
cana-803	110	33	{	{	PUNCT
cana-803	110	34	𝑋1(𝑡	𝑋1(𝑡	NOUN
cana-803	110	35	)	)	PUNCT
cana-803	110	36	,	,	PUNCT
cana-803	110	37	𝑋2(𝑡	𝑋2(𝑡	PROPN
cana-803	110	38	)	)	PUNCT
cana-803	110	39	,	,	PUNCT
cana-803	110	40	…	…	PUNCT
cana-803	110	41	,	,	PUNCT
cana-803	110	42	𝑋𝑛(𝑡	𝑋𝑛(𝑡	NOUN
cana-803	110	43	)	)	PUNCT
cana-803	110	44	}	}	PUNCT
cana-803	110	45	…	…	PUNCT
cana-803	110	46	……	……	NOUN
cana-803	110	47	.	.	PUNCT
cana-803	111	1	(	(	PUNCT
cana-803	111	2	1	1	X
cana-803	111	3	)	)	PUNCT
cana-803	111	4	in	in	ADP
cana-803	111	5	this	this	DET
cana-803	111	6	case	case	NOUN
cana-803	111	7	,	,	PUNCT
cana-803	111	8	xi(t	xi(t	NOUN
cana-803	111	9	)	)	PUNCT
cana-803	111	10	shows	show	VERB
cana-803	111	11	the	the	DET
cana-803	111	12	state	state	NOUN
cana-803	111	13	of	of	ADP
cana-803	111	14	the	the	DET
cana-803	111	15	ith	ith	ADJ
cana-803	111	16	part	part	NOUN
cana-803	111	17	of	of	ADP
cana-803	111	18	the	the	DET
cana-803	111	19	network	network	NOUN
cana-803	111	20	at	at	ADP
cana-803	111	21	time	time	NOUN
cana-803	111	22	t.	t.	PROPN
cana-803	111	23	this	this	PRON
cana-803	111	24	could	could	AUX
cana-803	111	25	be	be	AUX
cana-803	111	26	the	the	DET
cana-803	111	27	number	number	NOUN
cana-803	111	28	of	of	ADP
cana-803	111	29	packets	packet	NOUN
cana-803	111	30	in	in	ADP
cana-803	111	31	a	a	DET
cana-803	111	32	queue	queue	NOUN
cana-803	111	33	or	or	CCONJ
cana-803	111	34	how	how	SCONJ
cana-803	111	35	much	much	ADJ
cana-803	111	36	bandwidth	bandwidth	NOUN
cana-803	111	37	a	a	DET
cana-803	111	38	network	network	NOUN
cana-803	111	39	link	link	NOUN
cana-803	111	40	is	be	AUX
cana-803	111	41	being	be	AUX
cana-803	111	42	used	use	VERB
cana-803	111	43	.	.	PUNCT
cana-803	112	1	we	we	PRON
cana-803	112	2	can	can	AUX
cana-803	112	3	learn	learn	VERB
cana-803	112	4	more	more	ADJ
cana-803	112	5	about	about	ADP
cana-803	112	6	how	how	SCONJ
cana-803	112	7	network	network	NOUN
cana-803	112	8	traffic	traffic	NOUN
cana-803	112	9	works	work	VERB
cana-803	112	10	as	as	ADP
cana-803	112	11	a	a	DET
cana-803	112	12	whole	whole	NOUN
cana-803	112	13	by	by	ADP
cana-803	112	14	describing	describe	VERB
cana-803	112	15	these	these	DET
cana-803	112	16	parts	part	NOUN
cana-803	112	17	as	as	ADP
cana-803	112	18	random	random	ADJ
cana-803	112	19	variables	variable	NOUN
cana-803	112	20	and	and	CCONJ
cana-803	112	21	looking	look	VERB
cana-803	112	22	at	at	ADP
cana-803	112	23	how	how	SCONJ
cana-803	112	24	they	they	PRON
cana-803	112	25	change	change	VERB
cana-803	112	26	over	over	ADP
cana-803	112	27	time	time	NOUN
cana-803	112	28	together	together	ADV
cana-803	112	29	.	.	PUNCT
cana-803	113	1	in	in	ADP
cana-803	113	2	addition	addition	NOUN
cana-803	113	3	to	to	ADP
cana-803	113	4	probability	probability	NOUN
cana-803	113	5	theory	theory	NOUN
cana-803	113	6	,	,	PUNCT
cana-803	113	7	queuing	queue	VERB
cana-803	113	8	theory	theory	NOUN
cana-803	113	9	gives	give	VERB
cana-803	113	10	us	we	PRON
cana-803	113	11	a	a	DET
cana-803	113	12	way	way	NOUN
cana-803	113	13	to	to	PART
cana-803	113	14	organize	organize	VERB
cana-803	113	15	and	and	CCONJ
cana-803	113	16	understand	understand	VERB
cana-803	113	17	how	how	SCONJ
cana-803	113	18	network	network	NOUN
cana-803	113	19	requests	request	NOUN
cana-803	113	20	come	come	VERB
cana-803	113	21	in	in	ADP
cana-803	113	22	and	and	CCONJ
cana-803	113	23	are	be	AUX
cana-803	113	24	handled	handle	VERB
cana-803	113	25	.	.	PUNCT
cana-803	114	1	in	in	ADP
cana-803	114	2	queuing	queue	VERB
cana-803	114	3	models	model	NOUN
cana-803	114	4	,	,	PUNCT
cana-803	114	5	network	network	NOUN
cana-803	114	6	devices	device	NOUN
cana-803	114	7	like	like	ADP
cana-803	114	8	routers	router	NOUN
cana-803	114	9	and	and	CCONJ
cana-803	114	10	servers	server	NOUN
cana-803	114	11	are	be	AUX
cana-803	114	12	modeled	model	VERB
cana-803	114	13	as	as	ADP
cana-803	114	14	lines	line	NOUN
cana-803	114	15	.	.	PUNCT
cana-803	115	1	incoming	incoming	ADJ
cana-803	115	2	files	file	NOUN
cana-803	115	3	or	or	CCONJ
cana-803	115	4	requests	request	NOUN
cana-803	115	5	are	be	AUX
cana-803	115	6	handled	handle	VERB
cana-803	115	7	according	accord	VERB
cana-803	115	8	to	to	ADP
cana-803	115	9	rules	rule	NOUN
cana-803	115	10	that	that	PRON
cana-803	115	11	have	have	AUX
cana-803	115	12	already	already	ADV
cana-803	115	13	been	be	AUX
cana-803	115	14	set	set	VERB
cana-803	115	15	.	.	PUNCT
cana-803	116	1	by	by	ADP
cana-803	116	2	looking	look	VERB
cana-803	116	3	at	at	ADP
cana-803	116	4	queueing	queue	VERB
cana-803	116	5	systems	system	NOUN
cana-803	116	6	,	,	PUNCT
cana-803	116	7	we	we	PRON
cana-803	116	8	can	can	AUX
cana-803	116	9	find	find	VERB
cana-803	116	10	trends	trend	NOUN
cana-803	116	11	and	and	CCONJ
cana-803	116	12	outliers	outlier	NOUN
cana-803	116	13	that	that	PRON
cana-803	116	14	could	could	AUX
cana-803	116	15	be	be	AUX
cana-803	116	16	signs	sign	NOUN
cana-803	116	17	of	of	ADP
cana-803	116	18	cyberattacks	cyberattack	NOUN
cana-803	116	19	.	.	PUNCT
cana-803	117	1	for	for	ADP
cana-803	117	2	example	example	NOUN
cana-803	117	3	,	,	PUNCT
cana-803	117	4	sudden	sudden	ADJ
cana-803	117	5	increases	increase	NOUN
cana-803	117	6	in	in	ADP
cana-803	117	7	traffic	traffic	NOUN
cana-803	117	8	or	or	CCONJ
cana-803	117	9	long	long	ADJ
cana-803	117	10	wait	wait	VERB
cana-803	117	11	times	time	NOUN
cana-803	117	12	in	in	ADP
cana-803	117	13	line	line	NOUN
cana-803	117	14	are	be	AUX
cana-803	117	15	examples	example	NOUN
cana-803	117	16	of	of	ADP
cana-803	117	17	these	these	PRON
cana-803	117	18	.	.	PUNCT
cana-803	118	1	using	use	VERB
cana-803	118	2	numbers	number	NOUN
cana-803	118	3	like	like	ADP
cana-803	118	4	arrival	arrival	NOUN
cana-803	118	5	rates	rate	NOUN
cana-803	118	6	(	(	PUNCT
cana-803	118	7	λ	λ	X
cana-803	118	8	)	)	PUNCT
cana-803	118	9	,	,	PUNCT
cana-803	118	10	service	service	NOUN
cana-803	118	11	rates	rate	NOUN
cana-803	118	12	(	(	PUNCT
cana-803	118	13	μ	μ	NOUN
cana-803	118	14	)	)	PUNCT
cana-803	118	15	,	,	PUNCT
cana-803	118	16	and	and	CCONJ
cana-803	118	17	queue	queue	NOUN
cana-803	118	18	lengths	length	NOUN
cana-803	118	19	(	(	PUNCT
cana-803	118	20	l	l	NOUN
cana-803	118	21	)	)	PUNCT
cana-803	118	22	,	,	PUNCT
cana-803	118	23	you	you	PRON
cana-803	118	24	can	can	AUX
cana-803	118	25	describe	describe	VERB
cana-803	118	26	how	how	SCONJ
cana-803	118	27	a	a	DET
cana-803	118	28	queuing	queue	VERB
cana-803	118	29	system	system	NOUN
cana-803	118	30	works	work	VERB
cana-803	118	31	mathematically	mathematically	ADV
cana-803	118	32	.	.	PUNCT
cana-803	119	1	the	the	DET
cana-803	119	2	standard	standard	PROPN
cana-803	119	3	m	m	PROPN
cana-803	119	4	/	/	SYM
cana-803	119	5	m/1	m/1	NOUN
cana-803	119	6	queue	queue	NOUN
cana-803	119	7	model	model	NOUN
cana-803	119	8	,	,	PUNCT
cana-803	119	9	for	for	ADP
cana-803	119	10	instance	instance	NOUN
cana-803	119	11	,	,	PUNCT
cana-803	119	12	shows	show	VERB
cana-803	119	13	a	a	DET
cana-803	119	14	single	single	ADJ
cana-803	119	15	-	-	PUNCT
cana-803	119	16	server	server	NOUN
cana-803	119	17	system	system	NOUN
cana-803	119	18	with	with	ADP
cana-803	119	19	poisson	poisson	NOUN
cana-803	119	20	inputs	input	NOUN
cana-803	119	21	and	and	CCONJ
cana-803	119	22	exponential	exponential	ADJ
cana-803	119	23	response	response	NOUN
cana-803	119	24	times	time	NOUN
cana-803	119	25	.	.	PUNCT
cana-803	120	1	λ	λ	NOUN
cana-803	120	2	=	=	SYM
cana-803	120	3	arrival	arrival	NOUN
cana-803	120	4	rate	rate	NOUN
cana-803	120	5	μ	μ	NOUN
cana-803	120	6	=	=	SYM
cana-803	120	7	service	service	NOUN
cana-803	120	8	rate	rate	NOUN
cana-803	120	9	l	l	NOUN
cana-803	120	10	=	=	PUNCT
cana-803	120	11	queue	queue	NOUN
cana-803	120	12	length	length	NOUN
cana-803	120	13	communications	communication	NOUN
cana-803	120	14	on	on	ADP
cana-803	120	15	applied	apply	VERB
cana-803	120	16	nonlinear	nonlinear	ADJ
cana-803	120	17	analysis	analysis	NOUN
cana-803	120	18	issn	issn	NOUN
cana-803	120	19	:	:	PUNCT
cana-803	120	20	1074	1074	NUM
cana-803	120	21	-	-	PUNCT
cana-803	120	22	133x	133x	NUM
cana-803	120	23	vol	vol	NOUN
cana-803	120	24	31	31	NUM
cana-803	120	25	no	no	NOUN
cana-803	120	26	.	.	PUNCT
cana-803	121	1	3s	3s	NUM
cana-803	121	2	(	(	PUNCT
cana-803	121	3	2024	2024	NUM
cana-803	121	4	)	)	PUNCT
cana-803	121	5	493	493	NUM
cana-803	121	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-803	121	7	by	by	ADP
cana-803	121	8	using	use	VERB
cana-803	121	9	both	both	DET
cana-803	121	10	probability	probability	NOUN
cana-803	121	11	theory	theory	NOUN
cana-803	121	12	and	and	CCONJ
cana-803	121	13	queuing	queue	VERB
cana-803	121	14	theory	theory	NOUN
cana-803	121	15	together	together	ADV
cana-803	121	16	,	,	PUNCT
cana-803	121	17	we	we	PRON
cana-803	121	18	can	can	AUX
cana-803	121	19	get	get	VERB
cana-803	121	20	a	a	DET
cana-803	121	21	better	well	ADJ
cana-803	121	22	sense	sense	NOUN
cana-803	121	23	of	of	ADP
cana-803	121	24	how	how	SCONJ
cana-803	121	25	network	network	NOUN
cana-803	121	26	traffic	traffic	NOUN
cana-803	121	27	changes	change	NOUN
cana-803	121	28	over	over	ADP
cana-803	121	29	time	time	NOUN
cana-803	121	30	and	and	CCONJ
cana-803	121	31	find	find	VERB
cana-803	121	32	possible	possible	ADJ
cana-803	121	33	security	security	NOUN
cana-803	121	34	threats	threat	NOUN
cana-803	121	35	more	more	ADV
cana-803	121	36	quickly	quickly	ADV
cana-803	121	37	.	.	PUNCT
cana-803	122	1	with	with	ADP
cana-803	122	2	these	these	DET
cana-803	122	3	mathematical	mathematical	ADJ
cana-803	122	4	tools	tool	NOUN
cana-803	122	5	,	,	PUNCT
cana-803	122	6	we	we	PRON
cana-803	122	7	can	can	AUX
cana-803	122	8	carefully	carefully	ADV
cana-803	122	9	and	and	CCONJ
cana-803	122	10	methodically	methodically	ADV
cana-803	122	11	look	look	VERB
cana-803	122	12	at	at	ADP
cana-803	122	13	how	how	SCONJ
cana-803	122	14	networks	network	NOUN
cana-803	122	15	behave	behave	VERB
cana-803	122	16	.	.	PUNCT
cana-803	123	1	this	this	PRON
cana-803	123	2	makes	make	VERB
cana-803	123	3	it	it	PRON
cana-803	123	4	easier	easy	ADJ
cana-803	123	5	for	for	SCONJ
cana-803	123	6	breach	breach	NOUN
cana-803	123	7	detection	detection	NOUN
cana-803	123	8	systems	system	NOUN
cana-803	123	9	to	to	PART
cana-803	123	10	find	find	VERB
cana-803	123	11	and	and	CCONJ
cana-803	123	12	stop	stop	VERB
cana-803	123	13	cyberattacks	cyberattack	NOUN
cana-803	123	14	in	in	ADP
cana-803	123	15	real	real	ADJ
cana-803	123	16	time	time	NOUN
cana-803	123	17	.	.	PUNCT
cana-803	124	1	3	3	X
cana-803	124	2	.	.	X
cana-803	124	3	attack	attack	NOUN
cana-803	124	4	signature	signature	NOUN
cana-803	124	5	identification	identification	NOUN
cana-803	124	6	:	:	PUNCT
cana-803	124	7	statistical	statistical	ADJ
cana-803	124	8	analysis	analysis	NOUN
cana-803	124	9	methods	method	NOUN
cana-803	124	10	are	be	AUX
cana-803	124	11	used	use	VERB
cana-803	124	12	in	in	ADP
cana-803	124	13	attack	attack	NOUN
cana-803	124	14	signature	signature	NOUN
cana-803	124	15	recognition	recognition	NOUN
cana-803	124	16	to	to	PART
cana-803	124	17	find	find	VERB
cana-803	124	18	common	common	ADJ
cana-803	124	19	attack	attack	NOUN
cana-803	124	20	fingerprints	fingerprint	NOUN
cana-803	124	21	and	and	CCONJ
cana-803	124	22	trends	trend	NOUN
cana-803	124	23	in	in	ADP
cana-803	124	24	network	network	NOUN
cana-803	124	25	data	datum	NOUN
cana-803	124	26	.	.	PUNCT
cana-803	125	1	this	this	PRON
cana-803	125	2	lets	let	VERB
cana-803	125	3	cyber	cyber	ADJ
cana-803	125	4	risks	risk	NOUN
cana-803	125	5	be	be	AUX
cana-803	125	6	found	find	VERB
cana-803	125	7	and	and	CCONJ
cana-803	125	8	stopped	stop	VERB
cana-803	125	9	quickly	quickly	ADV
cana-803	125	10	.	.	PUNCT
cana-803	126	1	figure	figure	VERB
cana-803	126	2	2	2	NUM
cana-803	126	3	:	:	PUNCT
cana-803	126	4	representation	representation	NOUN
cana-803	126	5	of	of	ADP
cana-803	126	6	proposed	propose	VERB
cana-803	126	7	anomaly	anomaly	NOUN
cana-803	126	8	detection	detection	NOUN
cana-803	126	9	methodology	methodology	NOUN
cana-803	126	10	statistical	statistical	ADJ
cana-803	126	11	methods	method	NOUN
cana-803	126	12	can	can	AUX
cana-803	126	13	look	look	VERB
cana-803	126	14	at	at	ADP
cana-803	126	15	network	network	NOUN
cana-803	126	16	traffic	traffic	NOUN
cana-803	126	17	data	datum	NOUN
cana-803	126	18	and	and	CCONJ
cana-803	126	19	find	find	VERB
cana-803	126	20	strange	strange	ADJ
cana-803	126	21	or	or	CCONJ
cana-803	126	22	unusual	unusual	ADJ
cana-803	126	23	behavior	behavior	NOUN
cana-803	126	24	that	that	PRON
cana-803	126	25	could	could	AUX
cana-803	126	26	be	be	AUX
cana-803	126	27	a	a	DET
cana-803	126	28	sign	sign	NOUN
cana-803	126	29	of	of	ADP
cana-803	126	30	bad	bad	ADJ
cana-803	126	31	things	thing	NOUN
cana-803	126	32	happening	happen	VERB
cana-803	126	33	,	,	PUNCT
cana-803	126	34	like	like	ADP
cana-803	126	35	port	port	NOUN
cana-803	126	36	scans	scan	NOUN
cana-803	126	37	,	,	PUNCT
cana-803	126	38	denial	denial	NOUN
cana-803	126	39	-	-	PUNCT
cana-803	126	40	of	of	ADP
cana-803	126	41	-	-	PUNCT
cana-803	126	42	service	service	NOUN
cana-803	126	43	(	(	PUNCT
cana-803	126	44	dos	do	NOUN
cana-803	126	45	)	)	PUNCT
cana-803	126	46	attacks	attack	NOUN
cana-803	126	47	,	,	PUNCT
cana-803	126	48	and	and	CCONJ
cana-803	126	49	spying	spy	VERB
cana-803	126	50	activities	activity	NOUN
cana-803	126	51	.	.	PUNCT
cana-803	127	1	statistical	statistical	ADJ
cana-803	127	2	analysis	analysis	NOUN
cana-803	127	3	can	can	AUX
cana-803	127	4	be	be	AUX
cana-803	127	5	used	use	VERB
cana-803	127	6	to	to	PART
cana-803	127	7	find	find	VERB
cana-803	127	8	trends	trend	NOUN
cana-803	127	9	in	in	ADP
cana-803	127	10	network	network	NOUN
cana-803	127	11	traffic	traffic	NOUN
cana-803	127	12	by	by	ADP
cana-803	127	13	measuring	measure	VERB
cana-803	127	14	things	thing	NOUN
cana-803	127	15	like	like	ADP
cana-803	127	16	central	central	ADJ
cana-803	127	17	tendency	tendency	NOUN
cana-803	127	18	,	,	PUNCT
cana-803	127	19	dispersion	dispersion	NOUN
cana-803	127	20	,	,	PUNCT
cana-803	127	21	frequency	frequency	NOUN
cana-803	127	22	distributions	distribution	NOUN
cana-803	127	23	,	,	PUNCT
cana-803	127	24	and	and	CCONJ
cana-803	127	25	hypothesis	hypothesis	NOUN
cana-803	127	26	testing	testing	NOUN
cana-803	127	27	.	.	PUNCT
cana-803	128	1	statistical	statistical	ADJ
cana-803	128	2	features	feature	NOUN
cana-803	128	3	taken	take	VERB
cana-803	128	4	from	from	ADP
cana-803	128	5	the	the	DET
cana-803	128	6	data	datum	NOUN
cana-803	128	7	can	can	AUX
cana-803	128	8	be	be	AUX
cana-803	128	9	used	use	VERB
cana-803	128	10	by	by	ADP
cana-803	128	11	machine	machine	NOUN
cana-803	128	12	learning	learn	VERB
cana-803	128	13	algorithms	algorithm	NOUN
cana-803	128	14	to	to	PART
cana-803	128	15	automatically	automatically	ADV
cana-803	128	16	find	find	VERB
cana-803	128	17	and	and	CCONJ
cana-803	128	18	describe	describe	VERB
cana-803	128	19	network	network	NOUN
cana-803	128	20	activity	activity	NOUN
cana-803	128	21	that	that	PRON
cana-803	128	22	seems	seem	VERB
cana-803	128	23	fishy	fishy	ADJ
cana-803	128	24	.	.	PUNCT
cana-803	128	25	intrusion	intrusion	NOUN
cana-803	128	26	detection	detection	NOUN
cana-803	128	27	systems	system	NOUN
cana-803	128	28	(	(	PUNCT
cana-803	128	29	ids	id	NOUN
cana-803	128	30	)	)	PUNCT
cana-803	128	31	can	can	AUX
cana-803	128	32	find	find	VERB
cana-803	128	33	and	and	CCONJ
cana-803	128	34	stop	stop	VERB
cana-803	128	35	cyber	cyber	NOUN
cana-803	128	36	risks	risk	NOUN
cana-803	128	37	in	in	ADP
cana-803	128	38	real	real	ADJ
cana-803	128	39	time	time	NOUN
cana-803	128	40	by	by	ADP
cana-803	128	41	using	use	VERB
cana-803	128	42	statistical	statistical	ADJ
cana-803	128	43	analysis	analysis	NOUN
cana-803	128	44	.	.	PUNCT
cana-803	129	1	this	this	PRON
cana-803	129	2	makes	make	VERB
cana-803	129	3	networked	networked	ADJ
cana-803	129	4	systems	system	NOUN
cana-803	129	5	safer	safe	ADJ
cana-803	129	6	.	.	PUNCT
cana-803	130	1	proposed	propose	VERB
cana-803	130	2	algorithm	algorithm	NOUN
cana-803	130	3	for	for	ADP
cana-803	130	4	anomaly	anomaly	NOUN
cana-803	130	5	detection	detection	NOUN
cana-803	130	6	step	step	NOUN
cana-803	130	7	1	1	NUM
cana-803	130	8	:	:	PUNCT
cana-803	130	9	pattern	pattern	NOUN
cana-803	130	10	matching	matching	NOUN
cana-803	130	11	:	:	PUNCT
cana-803	130	12	communications	communication	NOUN
cana-803	130	13	on	on	ADP
cana-803	130	14	applied	apply	VERB
cana-803	130	15	nonlinear	nonlinear	ADJ
cana-803	130	16	analysis	analysis	NOUN
cana-803	130	17	issn	issn	NOUN
cana-803	130	18	:	:	PUNCT
cana-803	130	19	1074	1074	NUM
cana-803	130	20	-	-	PUNCT
cana-803	130	21	133x	133x	NUM
cana-803	130	22	vol	vol	NOUN
cana-803	130	23	31	31	NUM
cana-803	130	24	no	no	NOUN
cana-803	130	25	.	.	PUNCT
cana-803	131	1	3s	3s	NUM
cana-803	131	2	(	(	PUNCT
cana-803	131	3	2024	2024	NUM
cana-803	131	4	)	)	PUNCT
cana-803	131	5	494	494	NUM
cana-803	131	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-803	131	7	define	define	VERB
cana-803	131	8	attack	attack	NOUN
cana-803	131	9	signatures	signature	NOUN
cana-803	131	10	s	s	PART
cana-803	131	11	and	and	CCONJ
cana-803	131	12	use	use	VERB
cana-803	131	13	pattern	pattern	NOUN
cana-803	131	14	matching	match	VERB
cana-803	131	15	to	to	PART
cana-803	131	16	search	search	VERB
cana-803	131	17	for	for	ADP
cana-803	131	18	them	they	PRON
cana-803	131	19	in	in	ADP
cana-803	131	20	network	network	NOUN
cana-803	131	21	traffic	traffic	NOUN
cana-803	131	22	.	.	PUNCT
cana-803	132	1	utilize	utilize	VERB
cana-803	132	2	bayes	bayes	PROPN
cana-803	132	3	'	'	PART
cana-803	132	4	theorem	theorem	NOUN
cana-803	132	5	to	to	PART
cana-803	132	6	estimate	estimate	VERB
cana-803	132	7	the	the	DET
cana-803	132	8	likelihood	likelihood	NOUN
cana-803	132	9	of	of	ADP
cana-803	132	10	observed	observe	VERB
cana-803	132	11	patterns	pattern	NOUN
cana-803	132	12	being	be	AUX
cana-803	132	13	attacks	attack	NOUN
cana-803	132	14	.	.	PUNCT
cana-803	133	1	mathematically	mathematically	ADV
cana-803	133	2	,	,	PUNCT
cana-803	133	3	the	the	DET
cana-803	133	4	likelihood	likelihood	NOUN
cana-803	133	5	(	(	PUNCT
cana-803	133	6	𝐴∣𝐵	𝐴∣𝐵	X
cana-803	133	7	)	)	PUNCT
cana-803	133	8	of	of	ADP
cana-803	133	9	a	a	DET
cana-803	133	10	pattern	pattern	NOUN
cana-803	133	11	a	a	DET
cana-803	133	12	being	be	AUX
cana-803	133	13	an	an	DET
cana-803	133	14	attack	attack	NOUN
cana-803	133	15	given	give	VERB
cana-803	133	16	observed	observe	VERB
cana-803	133	17	data	datum	NOUN
cana-803	133	18	b	b	NOUN
cana-803	133	19	can	can	AUX
cana-803	133	20	be	be	AUX
cana-803	133	21	estimated	estimate	VERB
cana-803	133	22	using	use	VERB
cana-803	133	23	bayes	baye	NOUN
cana-803	133	24	'	'	PART
cana-803	133	25	theorem	theorem	NOUN
cana-803	133	26	:	:	PUNCT
cana-803	133	27	𝑃	𝑃	PROPN
cana-803	133	28	(	(	PUNCT
cana-803	133	29	𝐴	𝐴	PROPN
cana-803	133	30	∣	∣	PROPN
cana-803	133	31	𝐵	𝐵	NOUN
cana-803	133	32	)	)	PUNCT
cana-803	134	1	=	=	PUNCT
cana-803	134	2	𝑃	𝑃	PROPN
cana-803	134	3	(	(	PUNCT
cana-803	134	4	𝐵∣∣𝐴	𝐵∣∣𝐴	NOUN
cana-803	134	5	)	)	PUNCT
cana-803	134	6	×𝑃(𝐴	×𝑃(𝐴	PROPN
cana-803	134	7	)	)	PUNCT
cana-803	134	8	𝑃(𝐵	𝑃(𝐵	PROPN
cana-803	134	9	)	)	PUNCT
cana-803	134	10	....................	....................	PUNCT
cana-803	135	1	(	(	PUNCT
cana-803	135	2	1	1	X
cana-803	135	3	)	)	PUNCT
cana-803	135	4	step	step	NOUN
cana-803	135	5	2	2	NUM
cana-803	135	6	:	:	PUNCT
cana-803	135	7	anomaly	anomaly	NOUN
cana-803	135	8	detection	detection	NOUN
cana-803	135	9	:	:	PUNCT
cana-803	135	10	detect	detect	NOUN
cana-803	135	11	anomalies	anomalie	VERB
cana-803	135	12	a	a	PRON
cana-803	135	13	using	use	VERB
cana-803	135	14	statistical	statistical	ADJ
cana-803	135	15	methods	method	NOUN
cana-803	135	16	or	or	CCONJ
cana-803	135	17	machine	machine	NOUN
cana-803	135	18	learning	learning	NOUN
cana-803	135	19	.	.	PUNCT
cana-803	136	1	calculate	calculate	VERB
cana-803	136	2	anomaly	anomaly	NOUN
cana-803	136	3	scores	score	NOUN
cana-803	136	4	based	base	VERB
cana-803	136	5	on	on	ADP
cana-803	136	6	the	the	DET
cana-803	136	7	likelihood	likelihood	NOUN
cana-803	136	8	ratio	ratio	NOUN
cana-803	136	9	.	.	PUNCT
cana-803	137	1	𝐴𝑆(𝑋	𝐴𝑆(𝑋	NOUN
cana-803	137	2	)	)	PUNCT
cana-803	138	1	=	=	PUNCT
cana-803	138	2	𝑃	𝑃	NOUN
cana-803	138	3	(	(	PUNCT
cana-803	138	4	𝑋∣𝐻0	𝑋∣𝐻0	PROPN
cana-803	138	5	)	)	PUNCT
cana-803	138	6	𝑃(𝑋	𝑃(𝑋	PROPN
cana-803	138	7	)	)	PUNCT
cana-803	138	8	…	…	PUNCT
cana-803	138	9	…	…	PUNCT
cana-803	138	10	(	(	PUNCT
cana-803	138	11	2	2	X
cana-803	138	12	)	)	PUNCT
cana-803	138	13	step	step	NOUN
cana-803	138	14	3	3	NUM
cana-803	138	15	:	:	PUNCT
cana-803	138	16	machine	machine	NOUN
cana-803	138	17	learning	learn	VERB
cana-803	138	18	classification	classification	NOUN
cana-803	138	19	:	:	PUNCT
cana-803	138	20	train	train	NOUN
cana-803	138	21	classifiers	classifier	NOUN
cana-803	138	22	f(x	f(x	PROPN
cana-803	138	23	)	)	PUNCT
cana-803	138	24	using	use	VERB
cana-803	138	25	labeled	label	VERB
cana-803	138	26	datasets	dataset	NOUN
cana-803	138	27	of	of	ADP
cana-803	138	28	normal	normal	ADJ
cana-803	138	29	n	n	NOUN
cana-803	138	30	and	and	CCONJ
cana-803	138	31	malicious	malicious	ADJ
cana-803	138	32	m	m	NOUN
cana-803	138	33	traffic	traffic	NOUN
cana-803	138	34	.	.	PUNCT
cana-803	139	1	estimate	estimate	NOUN
cana-803	139	2	probabilities	probability	NOUN
cana-803	139	3	p(m|x	p(m|x	NOUN
cana-803	139	4	)	)	PUNCT
cana-803	139	5	using	use	VERB
cana-803	139	6	logistic	logistic	ADJ
cana-803	139	7	regression	regression	NOUN
cana-803	139	8	.	.	PUNCT
cana-803	140	1	𝑃	𝑃	NOUN
cana-803	140	2	(	(	PUNCT
cana-803	140	3	𝑀	𝑀	PROPN
cana-803	140	4	∣	∣	ADJ
cana-803	140	5	𝑋	𝑋	NOUN
cana-803	140	6	)	)	PUNCT
cana-803	140	7	=	=	SYM
cana-803	140	8	1	1	NUM
cana-803	140	9	(	(	PUNCT
cana-803	140	10	1+𝑒−𝑓(𝑋	1+𝑒−𝑓(𝑋	NUM
cana-803	140	11	)	)	PUNCT
cana-803	140	12	)	)	PUNCT
cana-803	140	13	...........	...........	PUNCT
cana-803	141	1	(	(	PUNCT
cana-803	141	2	3	3	X
cana-803	141	3	)	)	PUNCT
cana-803	141	4	step	step	NOUN
cana-803	141	5	4	4	NUM
cana-803	141	6	:	:	PUNCT
cana-803	141	7	dynamic	dynamic	ADJ
cana-803	141	8	model	model	NOUN
cana-803	141	9	updating	updating	NOUN
cana-803	141	10	:	:	PUNCT
cana-803	141	11	continuously	continuously	ADV
cana-803	141	12	update	update	VERB
cana-803	141	13	probabilistic	probabilistic	ADJ
cana-803	141	14	models	model	NOUN
cana-803	141	15	using	use	VERB
cana-803	141	16	bayesian	bayesian	NOUN
cana-803	141	17	updating	updating	NOUN
cana-803	141	18	.	.	PUNCT
cana-803	142	1	𝑃	𝑃	NOUN
cana-803	142	2	(	(	PUNCT
cana-803	142	3	𝜃	𝜃	NUM
cana-803	142	4	∣	∣	ADJ
cana-803	142	5	𝐷	𝐷	NOUN
cana-803	142	6	)	)	PUNCT
cana-803	142	7	=	=	PUNCT
cana-803	142	8	𝑃	𝑃	PROPN
cana-803	142	9	(	(	PUNCT
cana-803	142	10	𝐷∣∣𝜃	𝐷∣∣𝜃	PROPN
cana-803	142	11	)	)	PUNCT
cana-803	142	12	×𝑃(𝜃	×𝑃(𝜃	PROPN
cana-803	142	13	)	)	PUNCT
cana-803	142	14	𝑃(𝐷	𝑃(𝐷	PROPN
cana-803	142	15	)	)	PUNCT
cana-803	142	16	..............	..............	PUNCT
cana-803	143	1	(	(	PUNCT
cana-803	143	2	4	4	X
cana-803	143	3	)	)	PUNCT
cana-803	143	4	step	step	NOUN
cana-803	143	5	5	5	NUM
cana-803	143	6	:	:	PUNCT
cana-803	143	7	alert	alert	ADJ
cana-803	143	8	generation	generation	NOUN
cana-803	143	9	and	and	CCONJ
cana-803	143	10	response	response	NOUN
cana-803	143	11	:	:	PUNCT
cana-803	143	12	trigger	trigger	NOUN
cana-803	143	13	alerts	alert	NOUN
cana-803	143	14	based	base	VERB
cana-803	143	15	on	on	ADP
cana-803	143	16	predefined	predefine	VERB
cana-803	143	17	thresholds	threshold	NOUN
cana-803	143	18	on	on	ADP
cana-803	143	19	the	the	DET
cana-803	143	20	probability	probability	NOUN
cana-803	143	21	of	of	ADP
cana-803	143	22	an	an	DET
cana-803	143	23	event	event	NOUN
cana-803	143	24	being	be	AUX
cana-803	143	25	an	an	DET
cana-803	143	26	attack	attack	NOUN
cana-803	143	27	.	.	PUNCT
cana-803	144	1	alert(x	alert(x	NOUN
cana-803	144	2	)	)	PUNCT
cana-803	144	3	=	=	NOUN
cana-803	144	4	{	{	PUNCT
cana-803	144	5	true	true	ADJ
cana-803	144	6	,	,	PUNCT
cana-803	144	7	if	if	SCONJ
cana-803	144	8	p(a|x	p(a|x	NOUN
cana-803	144	9	)	)	PUNCT
cana-803	144	10	>	>	X
cana-803	144	11	𝜏	𝜏	X
cana-803	144	12	false	false	ADJ
cana-803	144	13	,	,	PUNCT
cana-803	144	14	otherwise	otherwise	ADV
cana-803	144	15	…	…	PUNCT
cana-803	144	16	…	…	PUNCT
cana-803	144	17	…	…	PUNCT
cana-803	144	18	…	…	SYM
cana-803	144	19	.(5	.(5	NOUN
cana-803	144	20	)	)	PUNCT
cana-803	144	21	4	4	NUM
cana-803	144	22	.	.	PUNCT
cana-803	144	23	stochastic	stochastic	ADJ
cana-803	144	24	optimization	optimization	NOUN
cana-803	144	25	:	:	PUNCT
cana-803	144	26	stochastic	stochastic	ADJ
cana-803	144	27	optimization	optimization	NOUN
cana-803	144	28	methods	method	NOUN
cana-803	144	29	are	be	AUX
cana-803	144	30	very	very	ADV
cana-803	144	31	important	important	ADJ
cana-803	144	32	for	for	ADP
cana-803	144	33	making	make	VERB
cana-803	144	34	reaction	reaction	NOUN
cana-803	144	35	tactics	tactic	NOUN
cana-803	144	36	more	more	ADV
cana-803	144	37	efficient	efficient	ADJ
cana-803	144	38	and	and	CCONJ
cana-803	144	39	effective	effective	ADJ
cana-803	144	40	in	in	ADP
cana-803	144	41	reducing	reduce	VERB
cana-803	144	42	the	the	DET
cana-803	144	43	damage	damage	NOUN
cana-803	144	44	that	that	PRON
cana-803	144	45	cyberattacks	cyberattack	NOUN
cana-803	144	46	do	do	VERB
cana-803	144	47	to	to	ADP
cana-803	144	48	network	network	NOUN
cana-803	144	49	performance	performance	NOUN
cana-803	144	50	.	.	PUNCT
cana-803	145	1	organizations	organization	NOUN
cana-803	145	2	can	can	AUX
cana-803	145	3	improve	improve	VERB
cana-803	145	4	their	their	PRON
cana-803	145	5	defenses	defense	NOUN
cana-803	145	6	to	to	PART
cana-803	145	7	keep	keep	VERB
cana-803	145	8	important	important	ADJ
cana-803	145	9	assets	asset	NOUN
cana-803	145	10	safe	safe	ADJ
cana-803	145	11	and	and	CCONJ
cana-803	145	12	reduce	reduce	VERB
cana-803	145	13	disruptions	disruption	NOUN
cana-803	145	14	by	by	ADP
cana-803	145	15	constantly	constantly	ADV
cana-803	145	16	allocating	allocate	VERB
cana-803	145	17	resources	resource	NOUN
cana-803	145	18	and	and	CCONJ
cana-803	145	19	setting	set	VERB
cana-803	145	20	priorities	priority	NOUN
cana-803	145	21	for	for	ADP
cana-803	145	22	reaction	reaction	NOUN
cana-803	145	23	actions	action	NOUN
cana-803	145	24	based	base	VERB
cana-803	145	25	on	on	ADP
cana-803	145	26	the	the	DET
cana-803	145	27	intensity	intensity	NOUN
cana-803	145	28	and	and	CCONJ
cana-803	145	29	likelihood	likelihood	NOUN
cana-803	145	30	of	of	ADP
cana-803	145	31	approaching	approach	VERB
cana-803	145	32	threats	threat	NOUN
cana-803	145	33	.	.	PUNCT
cana-803	146	1	𝑓(𝑥𝑘	𝑓(𝑥𝑘	ADJ
cana-803	146	2	)	)	PUNCT
cana-803	146	3	=	=	SYM
cana-803	146	4	𝑂𝑏𝑗𝑒𝑐𝑡𝑖𝑣𝑒	𝑂𝑏𝑗𝑒𝑐𝑡𝑖𝑣𝑒	PROPN
cana-803	146	5	𝑓𝑢𝑛𝑐𝑡𝑖𝑜𝑛	𝑓𝑢𝑛𝑐𝑡𝑖𝑜𝑛	ADP
cana-803	146	6	𝑡𝑜	𝑡𝑜	PROPN
cana-803	146	7	𝑏𝑒	𝑏𝑒	NOUN
cana-803	146	8	𝑜𝑝𝑡𝑖𝑚𝑖𝑧𝑒𝑑	𝑜𝑝𝑡𝑖𝑚𝑖𝑧𝑒𝑑	VERB
cana-803	146	9	it	it	PRON
cana-803	146	10	is	be	AUX
cana-803	146	11	possible	possible	ADJ
cana-803	146	12	to	to	PART
cana-803	146	13	make	make	VERB
cana-803	146	14	decisions	decision	NOUN
cana-803	146	15	in	in	ADP
cana-803	146	16	real	real	ADJ
cana-803	146	17	time	time	NOUN
cana-803	146	18	using	use	VERB
cana-803	146	19	stochastic	stochastic	ADJ
cana-803	146	20	optimization	optimization	NOUN
cana-803	146	21	methods	method	NOUN
cana-803	146	22	that	that	PRON
cana-803	146	23	use	use	VERB
cana-803	146	24	statistical	statistical	ADJ
cana-803	146	25	models	model	NOUN
cana-803	146	26	to	to	PART
cana-803	146	27	take	take	VERB
cana-803	146	28	into	into	ADP
cana-803	146	29	account	account	NOUN
cana-803	146	30	the	the	DET
cana-803	146	31	unknowns	unknown	NOUN
cana-803	146	32	in	in	ADP
cana-803	146	33	danger	danger	NOUN
cana-803	146	34	environments	environment	NOUN
cana-803	146	35	and	and	CCONJ
cana-803	146	36	network	network	NOUN
cana-803	146	37	conditions	condition	NOUN
cana-803	146	38	.	.	PUNCT
cana-803	147	1	𝑥𝑘	𝑥𝑘	X
cana-803	148	1	+	+	CCONJ
cana-803	148	2	1	1	NUM
cana-803	148	3	=	=	SYM
cana-803	148	4	𝑥𝑘	𝑥𝑘	NOUN
cana-803	149	1	+	+	CCONJ
cana-803	149	2	𝛿𝑘	𝛿𝑘	INTJ
cana-803	149	3	•	•	INTJ
cana-803	149	4	where	where	SCONJ
cana-803	149	5	δk	δk	PRON
cana-803	149	6	is	be	AUX
cana-803	149	7	a	a	DET
cana-803	149	8	stochastic	stochastic	ADJ
cana-803	149	9	perturbation	perturbation	NOUN
cana-803	149	10	communications	communication	NOUN
cana-803	149	11	on	on	ADP
cana-803	149	12	applied	apply	VERB
cana-803	149	13	nonlinear	nonlinear	ADJ
cana-803	149	14	analysis	analysis	NOUN
cana-803	149	15	issn	issn	NOUN
cana-803	149	16	:	:	PUNCT
cana-803	149	17	1074	1074	NUM
cana-803	149	18	-	-	PUNCT
cana-803	149	19	133x	133x	NUM
cana-803	149	20	vol	vol	NOUN
cana-803	149	21	31	31	NUM
cana-803	149	22	no	no	NOUN
cana-803	149	23	.	.	PUNCT
cana-803	150	1	3s	3s	NUM
cana-803	150	2	(	(	PUNCT
cana-803	150	3	2024	2024	NUM
cana-803	150	4	)	)	PUNCT
cana-803	150	5	495	495	NUM
cana-803	150	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-803	150	7	one	one	NUM
cana-803	150	8	important	important	ADJ
cana-803	150	9	part	part	NOUN
cana-803	150	10	of	of	ADP
cana-803	150	11	random	random	ADJ
cana-803	150	12	optimization	optimization	NOUN
cana-803	150	13	is	be	AUX
cana-803	150	14	allocating	allocate	VERB
cana-803	150	15	resources	resource	NOUN
cana-803	150	16	in	in	ADP
cana-803	150	17	a	a	DET
cana-803	150	18	way	way	NOUN
cana-803	150	19	that	that	PRON
cana-803	150	20	changes	change	VERB
cana-803	150	21	as	as	SCONJ
cana-803	150	22	threats	threat	NOUN
cana-803	150	23	change	change	VERB
cana-803	150	24	.	.	PUNCT
cana-803	151	1	by	by	ADP
cana-803	151	2	constantly	constantly	ADV
cana-803	151	3	watching	watch	VERB
cana-803	151	4	incoming	incoming	ADJ
cana-803	151	5	network	network	NOUN
cana-803	151	6	traffic	traffic	NOUN
cana-803	151	7	and	and	CCONJ
cana-803	151	8	threat	threat	NOUN
cana-803	151	9	intelligence	intelligence	NOUN
cana-803	151	10	feeds	feed	NOUN
cana-803	151	11	,	,	PUNCT
cana-803	151	12	businesses	business	NOUN
cana-803	151	13	can	can	AUX
cana-803	151	14	change	change	VERB
cana-803	151	15	how	how	SCONJ
cana-803	151	16	their	their	PRON
cana-803	151	17	resources	resource	NOUN
cana-803	151	18	are	be	AUX
cana-803	151	19	used	use	VERB
cana-803	151	20	to	to	PART
cana-803	151	21	effectively	effectively	ADV
cana-803	151	22	deal	deal	VERB
cana-803	151	23	with	with	ADP
cana-803	151	24	new	new	ADJ
cana-803	151	25	threats	threat	NOUN
cana-803	151	26	.	.	PUNCT
cana-803	152	1	𝑥𝑘	𝑥𝑘	X
cana-803	153	1	+	+	CCONJ
cana-803	153	2	1	1	NUM
cana-803	153	3	=	=	SYM
cana-803	153	4	{	{	PUNCT
cana-803	153	5	𝑥𝑘	𝑥𝑘	X
cana-803	154	1	+	+	CCONJ
cana-803	154	2	𝛿𝑘	𝛿𝑘	ADP
cana-803	154	3	𝑥𝑘	𝑥𝑘	X
cana-803	154	4	if	if	SCONJ
cana-803	154	5	𝑓(𝑥𝑘+1)≤𝑓(𝑥𝑘	𝑓(𝑥𝑘+1)≤𝑓(𝑥𝑘	ADJ
cana-803	154	6	)	)	PUNCT
cana-803	154	7	𝑂𝑡ℎ𝑟𝑒𝑤𝑖𝑠𝑒	𝑂𝑡ℎ𝑟𝑒𝑤𝑖𝑠𝑒	PROPN
cana-803	154	8	some	some	DET
cana-803	154	9	stochastic	stochastic	ADJ
cana-803	154	10	optimization	optimization	NOUN
cana-803	154	11	algorithms	algorithm	NOUN
cana-803	154	12	,	,	PUNCT
cana-803	154	13	like	like	ADP
cana-803	154	14	genetic	genetic	ADJ
cana-803	154	15	algorithms	algorithm	NOUN
cana-803	154	16	or	or	CCONJ
cana-803	154	17	stochastic	stochastic	ADJ
cana-803	154	18	gradient	gradient	ADJ
cana-803	154	19	descent	descent	NOUN
cana-803	154	20	,	,	PUNCT
cana-803	154	21	can	can	AUX
cana-803	154	22	make	make	VERB
cana-803	154	23	the	the	DET
cana-803	154	24	best	good	ADJ
cana-803	154	25	use	use	NOUN
cana-803	154	26	of	of	ADP
cana-803	154	27	resources	resource	NOUN
cana-803	154	28	by	by	ADP
cana-803	154	29	handling	handle	VERB
cana-803	154	30	the	the	DET
cana-803	154	31	trade	trade	NOUN
cana-803	154	32	-	-	PUNCT
cana-803	154	33	off	off	NOUN
cana-803	154	34	between	between	ADP
cana-803	154	35	how	how	SCONJ
cana-803	154	36	well	well	ADV
cana-803	154	37	resources	resource	NOUN
cana-803	154	38	are	be	AUX
cana-803	154	39	used	use	VERB
cana-803	154	40	and	and	CCONJ
cana-803	154	41	how	how	SCONJ
cana-803	154	42	well	well	ADV
cana-803	154	43	responses	response	NOUN
cana-803	154	44	work	work	VERB
cana-803	154	45	[	[	X
cana-803	154	46	23	23	NUM
cana-803	154	47	]	]	PUNCT
cana-803	154	48	.	.	PUNCT
cana-803	155	1	for	for	ADP
cana-803	155	2	instance	instance	NOUN
cana-803	155	3	,	,	PUNCT
cana-803	155	4	during	during	ADP
cana-803	155	5	a	a	DET
cana-803	155	6	distributed	distribute	VERB
cana-803	155	7	denial	denial	NOUN
cana-803	155	8	-	-	PUNCT
cana-803	155	9	of	of	ADP
cana-803	155	10	-	-	PUNCT
cana-803	155	11	service	service	NOUN
cana-803	155	12	(	(	PUNCT
cana-803	155	13	ddos	ddos	NOUN
cana-803	155	14	)	)	PUNCT
cana-803	155	15	attack	attack	NOUN
cana-803	155	16	,	,	PUNCT
cana-803	155	17	stochastic	stochastic	ADJ
cana-803	155	18	optimization	optimization	NOUN
cana-803	155	19	algorithms	algorithm	NOUN
cana-803	155	20	can	can	AUX
cana-803	155	21	divide	divide	VERB
cana-803	155	22	up	up	ADP
cana-803	155	23	data	datum	NOUN
cana-803	155	24	and	and	CCONJ
cana-803	155	25	computer	computer	NOUN
cana-803	155	26	power	power	NOUN
cana-803	155	27	to	to	PART
cana-803	155	28	help	help	VERB
cana-803	155	29	protect	protect	VERB
cana-803	155	30	important	important	ADJ
cana-803	155	31	services	service	NOUN
cana-803	155	32	while	while	SCONJ
cana-803	155	33	causing	cause	VERB
cana-803	155	34	as	as	ADP
cana-803	155	35	little	little	ADJ
cana-803	155	36	trouble	trouble	NOUN
cana-803	155	37	as	as	ADP
cana-803	155	38	possible	possible	ADJ
cana-803	155	39	for	for	ADP
cana-803	155	40	real	real	ADJ
cana-803	155	41	users	user	NOUN
cana-803	155	42	.	.	PUNCT
cana-803	156	1	stochastic	stochastic	ADJ
cana-803	156	2	optimization	optimization	NOUN
cana-803	156	3	makes	make	VERB
cana-803	156	4	it	it	PRON
cana-803	156	5	easier	easy	ADJ
cana-803	156	6	to	to	PART
cana-803	156	7	decide	decide	VERB
cana-803	156	8	which	which	DET
cana-803	156	9	reaction	reaction	NOUN
cana-803	156	10	actions	action	NOUN
cana-803	156	11	to	to	PART
cana-803	156	12	take	take	VERB
cana-803	156	13	first	first	ADV
cana-803	156	14	based	base	VERB
cana-803	156	15	on	on	ADP
cana-803	156	16	how	how	SCONJ
cana-803	156	17	likely	likely	ADJ
cana-803	156	18	and	and	CCONJ
cana-803	156	19	how	how	SCONJ
cana-803	156	20	bad	bad	ADJ
cana-803	156	21	the	the	DET
cana-803	156	22	risks	risk	NOUN
cana-803	156	23	are	be	AUX
cana-803	156	24	.	.	PUNCT
cana-803	157	1	by	by	ADP
cana-803	157	2	giving	give	VERB
cana-803	157	3	risks	risk	NOUN
cana-803	157	4	probability	probability	NOUN
cana-803	157	5	scores	score	NOUN
cana-803	157	6	,	,	PUNCT
cana-803	157	7	companies	company	NOUN
cana-803	157	8	can	can	AUX
cana-803	157	9	decide	decide	VERB
cana-803	157	10	which	which	DET
cana-803	157	11	reaction	reaction	NOUN
cana-803	157	12	steps	step	NOUN
cana-803	157	13	to	to	PART
cana-803	157	14	take	take	VERB
cana-803	157	15	first	first	ADV
cana-803	157	16	so	so	SCONJ
cana-803	157	17	that	that	SCONJ
cana-803	157	18	their	their	PRON
cana-803	157	19	resources	resource	NOUN
cana-803	157	20	are	be	AUX
cana-803	157	21	focused	focus	VERB
cana-803	157	22	on	on	ADP
cana-803	157	23	the	the	DET
cana-803	157	24	most	most	ADV
cana-803	157	25	important	important	ADJ
cana-803	157	26	events	event	NOUN
cana-803	157	27	.	.	PUNCT
cana-803	158	1	for	for	ADP
cana-803	158	2	example	example	NOUN
cana-803	158	3	,	,	PUNCT
cana-803	158	4	high	high	ADJ
cana-803	158	5	-	-	PUNCT
cana-803	158	6	risk	risk	NOUN
cana-803	158	7	threats	threat	NOUN
cana-803	158	8	that	that	PRON
cana-803	158	9	are	be	AUX
cana-803	158	10	likely	likely	ADJ
cana-803	158	11	to	to	PART
cana-803	158	12	be	be	AUX
cana-803	158	13	used	use	VERB
cana-803	158	14	and	and	CCONJ
cana-803	158	15	could	could	AUX
cana-803	158	16	have	have	VERB
cana-803	158	17	very	very	ADV
cana-803	158	18	bad	bad	ADJ
cana-803	158	19	effects	effect	NOUN
cana-803	158	20	may	may	AUX
cana-803	158	21	need	need	VERB
cana-803	158	22	quick	quick	ADJ
cana-803	158	23	control	control	NOUN
cana-803	158	24	measures	measure	NOUN
cana-803	158	25	,	,	PUNCT
cana-803	158	26	while	while	SCONJ
cana-803	158	27	lower	low	ADJ
cana-803	158	28	-	-	PUNCT
cana-803	158	29	risk	risk	NOUN
cana-803	158	30	threats	threat	NOUN
cana-803	158	31	can	can	AUX
cana-803	158	32	be	be	AUX
cana-803	158	33	dealt	deal	VERB
cana-803	158	34	with	with	ADP
cana-803	158	35	through	through	ADP
cana-803	158	36	reduction	reduction	NOUN
cana-803	158	37	strategies	strategy	NOUN
cana-803	158	38	that	that	PRON
cana-803	158	39	use	use	VERB
cana-803	158	40	fewer	few	ADJ
cana-803	158	41	resources	resource	NOUN
cana-803	158	42	.	.	PUNCT
cana-803	159	1	stochastic	stochastic	ADJ
cana-803	159	2	optimization	optimization	NOUN
cana-803	159	3	algorithms	algorithm	NOUN
cana-803	159	4	can	can	AUX
cana-803	159	5	change	change	VERB
cana-803	159	6	reaction	reaction	NOUN
cana-803	159	7	priorities	priority	NOUN
cana-803	159	8	based	base	VERB
cana-803	159	9	on	on	ADP
cana-803	159	10	changing	change	VERB
cana-803	159	11	danger	danger	NOUN
cana-803	159	12	conditions	condition	NOUN
cana-803	159	13	and	and	CCONJ
cana-803	159	14	available	available	ADJ
cana-803	159	15	resources	resource	NOUN
cana-803	159	16	.	.	PUNCT
cana-803	160	1	this	this	PRON
cana-803	160	2	makes	make	VERB
cana-803	160	3	sure	sure	ADJ
cana-803	160	4	that	that	SCONJ
cana-803	160	5	cyber	cyber	PROPN
cana-803	160	6	defense	defense	NOUN
cana-803	160	7	is	be	AUX
cana-803	160	8	strategic	strategic	ADJ
cana-803	160	9	and	and	CCONJ
cana-803	160	10	focused	focused	ADJ
cana-803	160	11	.	.	PUNCT
cana-803	161	1	by	by	ADP
cana-803	161	2	constantly	constantly	ADV
cana-803	161	3	allocating	allocate	VERB
cana-803	161	4	resources	resource	NOUN
cana-803	161	5	and	and	CCONJ
cana-803	161	6	ranking	ranking	ADJ
cana-803	161	7	reaction	reaction	NOUN
cana-803	161	8	actions	action	NOUN
cana-803	161	9	based	base	VERB
cana-803	161	10	on	on	ADP
cana-803	161	11	the	the	DET
cana-803	161	12	seriousness	seriousness	NOUN
cana-803	161	13	and	and	CCONJ
cana-803	161	14	possibility	possibility	NOUN
cana-803	161	15	of	of	ADP
cana-803	161	16	incoming	incoming	ADJ
cana-803	161	17	threats	threat	NOUN
cana-803	161	18	,	,	PUNCT
cana-803	161	19	stochastic	stochastic	ADJ
cana-803	161	20	optimization	optimization	NOUN
cana-803	161	21	methods	method	NOUN
cana-803	161	22	help	help	VERB
cana-803	161	23	organizations	organization	NOUN
cana-803	161	24	improve	improve	VERB
cana-803	161	25	their	their	PRON
cana-803	161	26	cyber	cyber	ADJ
cana-803	161	27	security	security	NOUN
cana-803	161	28	.	.	PUNCT
cana-803	162	1	using	use	VERB
cana-803	162	2	statistical	statistical	ADJ
cana-803	162	3	models	model	NOUN
cana-803	162	4	and	and	CCONJ
cana-803	162	5	flexible	flexible	ADJ
cana-803	162	6	decision	decision	NOUN
cana-803	162	7	-	-	PUNCT
cana-803	162	8	making	make	VERB
cana-803	162	9	algorithms	algorithm	NOUN
cana-803	162	10	,	,	PUNCT
cana-803	162	11	businesses	business	NOUN
cana-803	162	12	can	can	AUX
cana-803	162	13	get	get	VERB
cana-803	162	14	the	the	DET
cana-803	162	15	most	most	ADJ
cana-803	162	16	out	out	ADP
cana-803	162	17	of	of	ADP
cana-803	162	18	their	their	PRON
cana-803	162	19	resources	resource	NOUN
cana-803	162	20	,	,	PUNCT
cana-803	162	21	keep	keep	VERB
cana-803	162	22	downtime	downtime	NOUN
cana-803	162	23	to	to	ADP
cana-803	162	24	a	a	DET
cana-803	162	25	minimum	minimum	NOUN
cana-803	162	26	,	,	PUNCT
cana-803	162	27	and	and	CCONJ
cana-803	162	28	lessen	lessen	VERB
cana-803	162	29	the	the	DET
cana-803	162	30	damage	damage	NOUN
cana-803	162	31	that	that	PRON
cana-803	162	32	cyberattacks	cyberattack	NOUN
cana-803	162	33	do	do	VERB
cana-803	162	34	to	to	ADP
cana-803	162	35	network	network	NOUN
cana-803	162	36	performance	performance	NOUN
cana-803	162	37	.	.	PUNCT
cana-803	163	1	4.result	4.result	NUM
cana-803	163	2	and	and	CCONJ
cana-803	163	3	discussion	discussion	NOUN
cana-803	163	4	one	one	NUM
cana-803	163	5	way	way	NOUN
cana-803	163	6	to	to	PART
cana-803	163	7	compare	compare	VERB
cana-803	163	8	different	different	ADJ
cana-803	163	9	attack	attack	NOUN
cana-803	163	10	signature	signature	NOUN
cana-803	163	11	recognition	recognition	NOUN
cana-803	163	12	methods	method	NOUN
cana-803	163	13	is	be	AUX
cana-803	163	14	shown	show	VERB
cana-803	163	15	in	in	ADP
cana-803	163	16	table	table	NOUN
cana-803	163	17	(	(	PUNCT
cana-803	163	18	2	2	NUM
cana-803	163	19	)	)	PUNCT
cana-803	163	20	.	.	PUNCT
cana-803	164	1	it	it	PRON
cana-803	164	2	does	do	VERB
cana-803	164	3	this	this	PRON
cana-803	164	4	by	by	ADP
cana-803	164	5	looking	look	VERB
cana-803	164	6	at	at	ADP
cana-803	164	7	performance	performance	NOUN
cana-803	164	8	measures	measure	NOUN
cana-803	164	9	like	like	ADP
cana-803	164	10	memory	memory	NOUN
cana-803	164	11	,	,	PUNCT
cana-803	164	12	accuracy	accuracy	NOUN
cana-803	164	13	,	,	PUNCT
cana-803	164	14	and	and	CCONJ
cana-803	164	15	precision	precision	NOUN
cana-803	164	16	.	.	PUNCT
cana-803	165	1	signature	signature	NOUN
cana-803	165	2	-	-	PUNCT
cana-803	165	3	based	base	VERB
cana-803	165	4	intrusion	intrusion	NOUN
cana-803	165	5	detection	detection	NOUN
cana-803	165	6	systems	system	NOUN
cana-803	165	7	(	(	PUNCT
cana-803	165	8	ids	id	NOUN
cana-803	165	9	)	)	PUNCT
cana-803	165	10	look	look	VERB
cana-803	165	11	for	for	ADP
cana-803	165	12	known	know	VERB
cana-803	165	13	attack	attack	NOUN
cana-803	165	14	patterns	pattern	NOUN
cana-803	165	15	in	in	ADP
cana-803	165	16	network	network	NOUN
cana-803	165	17	data	datum	NOUN
cana-803	165	18	to	to	PART
cana-803	165	19	find	find	VERB
cana-803	165	20	bad	bad	ADJ
cana-803	165	21	things	thing	NOUN
cana-803	165	22	happening	happen	VERB
cana-803	165	23	.	.	PUNCT
cana-803	166	1	the	the	DET
cana-803	166	2	findings	finding	NOUN
cana-803	166	3	show	show	VERB
cana-803	166	4	that	that	SCONJ
cana-803	166	5	signature	signature	NOUN
cana-803	166	6	-	-	PUNCT
cana-803	166	7	based	base	VERB
cana-803	166	8	ids	id	NOUN
cana-803	166	9	is	be	AUX
cana-803	166	10	mostly	mostly	ADV
cana-803	166	11	accurate	accurate	ADJ
cana-803	166	12	(	(	PUNCT
cana-803	166	13	85	85	NUM
cana-803	166	14	%	%	NOUN
cana-803	166	15	)	)	PUNCT
cana-803	166	16	,	,	PUNCT
cana-803	166	17	but	but	CCONJ
cana-803	166	18	not	not	PART
cana-803	166	19	very	very	ADV
cana-803	166	20	good	good	ADJ
cana-803	166	21	at	at	ADP
cana-803	166	22	being	be	AUX
cana-803	166	23	precise	precise	ADJ
cana-803	166	24	(	(	PUNCT
cana-803	166	25	80	80	NUM
cana-803	166	26	%	%	NOUN
cana-803	166	27	)	)	PUNCT
cana-803	166	28	or	or	CCONJ
cana-803	166	29	remembering	remember	VERB
cana-803	166	30	things	thing	NOUN
cana-803	166	31	(	(	PUNCT
cana-803	166	32	85	85	NUM
cana-803	166	33	%	%	NOUN
cana-803	166	34	)	)	PUNCT
cana-803	166	35	.	.	PUNCT
cana-803	167	1	this	this	PRON
cana-803	167	2	means	mean	VERB
cana-803	167	3	that	that	SCONJ
cana-803	167	4	while	while	SCONJ
cana-803	167	5	it	it	PRON
cana-803	167	6	does	do	VERB
cana-803	167	7	a	a	DET
cana-803	167	8	good	good	ADJ
cana-803	167	9	job	job	NOUN
cana-803	167	10	of	of	ADP
cana-803	167	11	finding	find	VERB
cana-803	167	12	known	know	VERB
cana-803	167	13	attack	attack	NOUN
cana-803	167	14	patterns	pattern	NOUN
cana-803	167	15	,	,	PUNCT
cana-803	167	16	it	it	PRON
cana-803	167	17	may	may	AUX
cana-803	167	18	also	also	ADV
cana-803	167	19	give	give	VERB
cana-803	167	20	false	false	ADJ
cana-803	167	21	positives	positive	NOUN
cana-803	167	22	and	and	CCONJ
cana-803	167	23	miss	miss	VERB
cana-803	167	24	some	some	DET
cana-803	167	25	bad	bad	ADJ
cana-803	167	26	behavior	behavior	NOUN
cana-803	167	27	,	,	PUNCT
cana-803	167	28	which	which	PRON
cana-803	167	29	lowers	lower	VERB
cana-803	167	30	its	its	PRON
cana-803	167	31	accuracy	accuracy	NOUN
cana-803	167	32	and	and	CCONJ
cana-803	167	33	memory	memory	NOUN
cana-803	167	34	scores	score	NOUN
cana-803	167	35	.	.	PUNCT
cana-803	168	1	table	table	NOUN
cana-803	168	2	2	2	NUM
cana-803	168	3	:	:	PUNCT
cana-803	168	4	comparative	comparative	ADJ
cana-803	168	5	analysis	analysis	NOUN
cana-803	168	6	of	of	ADP
cana-803	168	7	different	different	ADJ
cana-803	168	8	methods	method	NOUN
cana-803	168	9	vs	vs	ADP
cana-803	168	10	proposed	propose	VERB
cana-803	168	11	methodology	methodology	NOUN
cana-803	168	12	for	for	ADP
cana-803	168	13	attack	attack	NOUN
cana-803	168	14	signature	signature	NOUN
cana-803	168	15	identification	identification	NOUN
cana-803	168	16	method	method	NOUN
cana-803	168	17	accuracy	accuracy	NOUN
cana-803	168	18	(	(	PUNCT
cana-803	168	19	%	%	INTJ
cana-803	168	20	)	)	PUNCT
cana-803	168	21	precision	precision	NOUN
cana-803	168	22	(	(	PUNCT
cana-803	168	23	%	%	INTJ
cana-803	168	24	)	)	PUNCT
cana-803	168	25	f1	f1	NOUN
cana-803	168	26	score	score	NOUN
cana-803	168	27	(	(	PUNCT
cana-803	168	28	%	%	INTJ
cana-803	168	29	)	)	PUNCT
cana-803	168	30	recall	recall	NOUN
cana-803	168	31	(	(	PUNCT
cana-803	168	32	%	%	NOUN
cana-803	168	33	)	)	PUNCT
cana-803	168	34	signature	signature	NOUN
cana-803	168	35	-	-	PUNCT
cana-803	168	36	based	base	VERB
cana-803	168	37	ids	id	NOUN
cana-803	168	38	85	85	NUM
cana-803	168	39	80	80	NUM
cana-803	168	40	87	87	NUM
cana-803	168	41	85	85	NUM
cana-803	168	42	anomaly	anomaly	NOUN
cana-803	168	43	-	-	PUNCT
cana-803	168	44	based	base	VERB
cana-803	168	45	ids	id	NOUN
cana-803	168	46	80	80	NUM
cana-803	168	47	75	75	NUM
cana-803	168	48	82	82	NUM
cana-803	168	49	78	78	NUM
cana-803	168	50	machine	machine	NOUN
cana-803	168	51	learning	learn	VERB
cana-803	168	52	approach	approach	NOUN
cana-803	168	53	88	88	NUM
cana-803	168	54	86	86	NUM
cana-803	168	55	89	89	NUM
cana-803	168	56	87	87	NUM
cana-803	168	57	proposed	propose	VERB
cana-803	168	58	algorithm	algorithm	NOUN
cana-803	168	59	92	92	NUM
cana-803	168	60	90	90	NUM
cana-803	168	61	93	93	NUM
cana-803	168	62	91	91	NUM
cana-803	168	63	anomaly	anomaly	NOUN
cana-803	168	64	-	-	PUNCT
cana-803	168	65	based	base	VERB
cana-803	168	66	ids	id	NOUN
cana-803	168	67	,	,	PUNCT
cana-803	168	68	on	on	ADP
cana-803	168	69	the	the	DET
cana-803	168	70	other	other	ADJ
cana-803	168	71	hand	hand	NOUN
cana-803	168	72	,	,	PUNCT
cana-803	168	73	looks	look	VERB
cana-803	168	74	for	for	ADP
cana-803	168	75	changes	change	NOUN
cana-803	168	76	from	from	ADP
cana-803	168	77	how	how	SCONJ
cana-803	168	78	a	a	DET
cana-803	168	79	network	network	NOUN
cana-803	168	80	normally	normally	ADV
cana-803	168	81	works	work	VERB
cana-803	168	82	to	to	PART
cana-803	168	83	find	find	VERB
cana-803	168	84	possible	possible	ADJ
cana-803	168	85	risks	risk	NOUN
cana-803	168	86	.	.	PUNCT
cana-803	169	1	even	even	ADV
cana-803	169	2	though	though	SCONJ
cana-803	169	3	it	it	PRON
cana-803	169	4	's	be	AUX
cana-803	169	5	only	only	ADV
cana-803	169	6	80	80	NUM
cana-803	169	7	%	%	NOUN
cana-803	169	8	accurate	accurate	ADJ
cana-803	169	9	,	,	PUNCT
cana-803	169	10	anomaly	anomaly	NOUN
cana-803	169	11	-	-	PUNCT
cana-803	169	12	based	base	VERB
cana-803	169	13	ids	id	NOUN
cana-803	169	14	is	be	AUX
cana-803	169	15	just	just	ADV
cana-803	169	16	as	as	ADV
cana-803	169	17	precise	precise	ADJ
cana-803	169	18	(	(	PUNCT
cana-803	169	19	75	75	NUM
cana-803	169	20	%	%	NOUN
cana-803	169	21	of	of	ADP
cana-803	169	22	the	the	DET
cana-803	169	23	time	time	NOUN
cana-803	169	24	)	)	PUNCT
cana-803	169	25	and	and	CCONJ
cana-803	169	26	accurate	accurate	ADJ
cana-803	169	27	(	(	PUNCT
cana-803	169	28	78	78	NUM
cana-803	169	29	%	%	NOUN
cana-803	169	30	of	of	ADP
cana-803	169	31	the	the	DET
cana-803	169	32	time	time	NOUN
cana-803	169	33	)	)	PUNCT
cana-803	169	34	as	as	ADP
cana-803	169	35	signature	signature	NOUN
cana-803	169	36	-	-	PUNCT
cana-803	169	37	based	base	VERB
cana-803	169	38	ids	id	NOUN
cana-803	169	39	.	.	PUNCT
cana-803	170	1	but	but	CCONJ
cana-803	170	2	it	it	PRON
cana-803	170	3	might	might	AUX
cana-803	170	4	have	have	VERB
cana-803	170	5	trouble	trouble	NOUN
cana-803	170	6	telling	tell	VERB
cana-803	170	7	communications	communication	NOUN
cana-803	170	8	on	on	ADP
cana-803	170	9	applied	apply	VERB
cana-803	170	10	nonlinear	nonlinear	ADJ
cana-803	170	11	analysis	analysis	NOUN
cana-803	170	12	issn	issn	NOUN
cana-803	170	13	:	:	PUNCT
cana-803	170	14	1074	1074	NUM
cana-803	170	15	-	-	PUNCT
cana-803	170	16	133x	133x	NUM
cana-803	170	17	vol	vol	NOUN
cana-803	170	18	31	31	NUM
cana-803	170	19	no	no	NOUN
cana-803	170	20	.	.	PUNCT
cana-803	171	1	3s	3s	NUM
cana-803	171	2	(	(	PUNCT
cana-803	171	3	2024	2024	NUM
cana-803	171	4	)	)	PUNCT
cana-803	171	5	496	496	NUM
cana-803	171	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-803	171	7	the	the	DET
cana-803	171	8	difference	difference	NOUN
cana-803	171	9	between	between	ADP
cana-803	171	10	harmless	harmless	ADJ
cana-803	171	11	oddities	oddity	NOUN
cana-803	171	12	and	and	CCONJ
cana-803	171	13	real	real	ADJ
cana-803	171	14	threats	threat	NOUN
cana-803	171	15	,	,	PUNCT
cana-803	171	16	which	which	PRON
cana-803	171	17	would	would	AUX
cana-803	171	18	lead	lead	VERB
cana-803	171	19	to	to	ADP
cana-803	171	20	more	more	ADV
cana-803	171	21	false	false	ADJ
cana-803	171	22	positives	positive	NOUN
cana-803	171	23	and	and	CCONJ
cana-803	171	24	less	less	ADJ
cana-803	171	25	accuracy	accuracy	NOUN
cana-803	171	26	.	.	PUNCT
cana-803	172	1	machine	machine	NOUN
cana-803	172	2	learning	learn	VERB
cana-803	172	3	techniques	technique	NOUN
cana-803	172	4	use	use	VERB
cana-803	172	5	algorithms	algorithm	NOUN
cana-803	172	6	to	to	PART
cana-803	172	7	find	find	VERB
cana-803	172	8	trends	trend	NOUN
cana-803	172	9	and	and	CCONJ
cana-803	172	10	outliers	outlier	NOUN
cana-803	172	11	in	in	ADP
cana-803	172	12	network	network	NOUN
cana-803	172	13	traffic	traffic	NOUN
cana-803	172	14	,	,	PUNCT
cana-803	172	15	giving	give	VERB
cana-803	172	16	us	we	PRON
cana-803	172	17	another	another	DET
cana-803	172	18	way	way	NOUN
cana-803	172	19	to	to	PART
cana-803	172	20	find	find	VERB
cana-803	172	21	attacks	attack	NOUN
cana-803	172	22	that	that	PRON
cana-803	172	23	is	be	AUX
cana-803	172	24	based	base	VERB
cana-803	172	25	on	on	ADP
cana-803	172	26	data	data	PROPN
cana-803	172	27	.	.	PUNCT
cana-803	173	1	machine	machine	NOUN
cana-803	173	2	learning	learn	VERB
cana-803	173	3	methods	method	NOUN
cana-803	173	4	are	be	AUX
cana-803	173	5	more	more	ADV
cana-803	173	6	accurate	accurate	ADJ
cana-803	173	7	(	(	PUNCT
cana-803	173	8	88	88	NUM
cana-803	173	9	%	%	NOUN
cana-803	173	10	of	of	ADP
cana-803	173	11	the	the	DET
cana-803	173	12	time	time	NOUN
cana-803	173	13	)	)	PUNCT
cana-803	173	14	than	than	ADP
cana-803	173	15	both	both	CCONJ
cana-803	173	16	signature	signature	NOUN
cana-803	173	17	-	-	PUNCT
cana-803	173	18	based	base	VERB
cana-803	173	19	and	and	CCONJ
cana-803	173	20	anomaly	anomaly	NOUN
cana-803	173	21	-	-	PUNCT
cana-803	173	22	based	base	VERB
cana-803	173	23	ids	id	NOUN
cana-803	173	24	,	,	PUNCT
cana-803	173	25	the	the	DET
cana-803	173	26	data	data	NOUN
cana-803	173	27	show	show	NOUN
cana-803	173	28	.	.	PUNCT
cana-803	174	1	furthermore	furthermore	ADV
cana-803	174	2	,	,	PUNCT
cana-803	174	3	these	these	DET
cana-803	174	4	methods	method	NOUN
cana-803	174	5	show	show	VERB
cana-803	174	6	higher	high	ADJ
cana-803	174	7	accuracy	accuracy	NOUN
cana-803	174	8	(	(	PUNCT
cana-803	174	9	86	86	NUM
cana-803	174	10	%	%	NOUN
cana-803	174	11	)	)	PUNCT
cana-803	174	12	and	and	CCONJ
cana-803	174	13	recall	recall	NOUN
cana-803	174	14	(	(	PUNCT
cana-803	174	15	87	87	NUM
cana-803	174	16	%	%	NOUN
cana-803	174	17	)	)	PUNCT
cana-803	174	18	,	,	PUNCT
cana-803	174	19	which	which	PRON
cana-803	174	20	means	mean	VERB
cana-803	174	21	they	they	PRON
cana-803	174	22	can	can	AUX
cana-803	174	23	effectively	effectively	ADV
cana-803	174	24	find	find	VERB
cana-803	174	25	both	both	DET
cana-803	174	26	known	know	VERB
cana-803	174	27	attack	attack	NOUN
cana-803	174	28	patterns	pattern	NOUN
cana-803	174	29	and	and	CCONJ
cana-803	174	30	risks	risk	NOUN
cana-803	174	31	that	that	PRON
cana-803	174	32	have	have	AUX
cana-803	174	33	n't	not	PART
cana-803	174	34	been	be	AUX
cana-803	174	35	seen	see	VERB
cana-803	174	36	before	before	ADV
cana-803	174	37	.	.	PUNCT
cana-803	175	1	the	the	DET
cana-803	175	2	suggested	suggest	VERB
cana-803	175	3	algorithm	algorithm	NOUN
cana-803	175	4	does	do	VERB
cana-803	175	5	better	well	ADV
cana-803	175	6	than	than	ADP
cana-803	175	7	all	all	DET
cana-803	175	8	others	other	NOUN
cana-803	175	9	in	in	ADP
cana-803	175	10	every	every	DET
cana-803	175	11	way	way	NOUN
cana-803	175	12	.	.	PUNCT
cana-803	176	1	it	it	PRON
cana-803	176	2	has	have	VERB
cana-803	176	3	the	the	DET
cana-803	176	4	best	good	ADJ
cana-803	176	5	accuracy	accuracy	NOUN
cana-803	176	6	(	(	PUNCT
cana-803	176	7	92	92	NUM
cana-803	176	8	%	%	NOUN
cana-803	176	9	)	)	PUNCT
cana-803	176	10	,	,	PUNCT
cana-803	176	11	precision	precision	NOUN
cana-803	176	12	(	(	PUNCT
cana-803	176	13	90	90	NUM
cana-803	176	14	%	%	NOUN
cana-803	176	15	)	)	PUNCT
cana-803	176	16	,	,	PUNCT
cana-803	176	17	f1	f1	NOUN
cana-803	176	18	score	score	NOUN
cana-803	176	19	(	(	PUNCT
cana-803	176	20	93	93	NUM
cana-803	176	21	%	%	NOUN
cana-803	176	22	)	)	PUNCT
cana-803	176	23	,	,	PUNCT
cana-803	176	24	and	and	CCONJ
cana-803	176	25	memory	memory	NOUN
cana-803	176	26	(	(	PUNCT
cana-803	176	27	91	91	NUM
cana-803	176	28	%	%	NOUN
cana-803	176	29	)	)	PUNCT
cana-803	176	30	.	.	PUNCT
cana-803	177	1	this	this	PRON
cana-803	177	2	means	mean	VERB
cana-803	177	3	that	that	SCONJ
cana-803	177	4	the	the	DET
cana-803	177	5	suggested	suggest	VERB
cana-803	177	6	method	method	NOUN
cana-803	177	7	seems	seem	VERB
cana-803	177	8	to	to	PART
cana-803	177	9	be	be	AUX
cana-803	177	10	a	a	DET
cana-803	177	11	stronger	strong	ADJ
cana-803	177	12	and	and	CCONJ
cana-803	177	13	more	more	ADV
cana-803	177	14	effective	effective	ADJ
cana-803	177	15	way	way	NOUN
cana-803	177	16	to	to	PART
cana-803	177	17	find	find	VERB
cana-803	177	18	attack	attack	NOUN
cana-803	177	19	signatures	signature	NOUN
cana-803	177	20	.	.	PUNCT
cana-803	178	1	using	use	VERB
cana-803	178	2	advanced	advanced	ADJ
cana-803	178	3	methods	method	NOUN
cana-803	178	4	like	like	ADP
cana-803	178	5	probabilistic	probabilistic	ADJ
cana-803	178	6	modeling	modeling	NOUN
cana-803	178	7	and	and	CCONJ
cana-803	178	8	dynamic	dynamic	ADJ
cana-803	178	9	resource	resource	NOUN
cana-803	178	10	allocation	allocation	NOUN
cana-803	178	11	,	,	PUNCT
cana-803	178	12	the	the	DET
cana-803	178	13	suggested	suggest	VERB
cana-803	178	14	algorithm	algorithm	NOUN
cana-803	178	15	can	can	AUX
cana-803	178	16	change	change	VERB
cana-803	178	17	the	the	DET
cana-803	178	18	order	order	NOUN
cana-803	178	19	of	of	ADP
cana-803	178	20	response	response	NOUN
cana-803	178	21	actions	action	NOUN
cana-803	178	22	based	base	VERB
cana-803	178	23	on	on	ADP
cana-803	178	24	how	how	SCONJ
cana-803	178	25	dangerous	dangerous	ADJ
cana-803	178	26	and	and	CCONJ
cana-803	178	27	likely	likely	ADJ
cana-803	178	28	it	it	PRON
cana-803	178	29	is	be	AUX
cana-803	178	30	that	that	SCONJ
cana-803	178	31	threats	threat	NOUN
cana-803	178	32	will	will	AUX
cana-803	178	33	come	come	VERB
cana-803	178	34	in	in	ADP
cana-803	178	35	.	.	PUNCT
cana-803	179	1	this	this	PRON
cana-803	179	2	makes	make	VERB
cana-803	179	3	the	the	DET
cana-803	179	4	best	good	ADJ
cana-803	179	5	use	use	NOUN
cana-803	179	6	of	of	ADP
cana-803	179	7	resources	resource	NOUN
cana-803	179	8	and	and	CCONJ
cana-803	179	9	reduces	reduce	VERB
cana-803	179	10	the	the	DET
cana-803	179	11	damage	damage	NOUN
cana-803	179	12	that	that	PRON
cana-803	179	13	cyberattacks	cyberattack	NOUN
cana-803	179	14	do	do	VERB
cana-803	179	15	to	to	ADP
cana-803	179	16	network	network	NOUN
cana-803	179	17	performance	performance	NOUN
cana-803	179	18	.	.	PUNCT
cana-803	180	1	overall	overall	ADV
cana-803	180	2	,	,	PUNCT
cana-803	180	3	the	the	DET
cana-803	180	4	results	result	NOUN
cana-803	180	5	show	show	VERB
cana-803	180	6	how	how	SCONJ
cana-803	180	7	important	important	ADJ
cana-803	180	8	it	it	PRON
cana-803	180	9	is	be	AUX
cana-803	180	10	to	to	PART
cana-803	180	11	use	use	VERB
cana-803	180	12	advanced	advanced	ADJ
cana-803	180	13	methods	method	NOUN
cana-803	180	14	to	to	PART
cana-803	180	15	find	find	VERB
cana-803	180	16	attack	attack	NOUN
cana-803	180	17	signatures	signature	NOUN
cana-803	180	18	,	,	PUNCT
cana-803	180	19	especially	especially	ADV
cana-803	180	20	since	since	SCONJ
cana-803	180	21	online	online	ADJ
cana-803	180	22	threats	threat	NOUN
cana-803	180	23	are	be	AUX
cana-803	180	24	always	always	ADV
cana-803	180	25	changing	change	VERB
cana-803	180	26	.	.	PUNCT
cana-803	181	1	while	while	SCONJ
cana-803	181	2	standard	standard	ADJ
cana-803	181	3	signatureand	signatureand	NOUN
cana-803	181	4	anomaly	anomaly	NOUN
cana-803	181	5	-	-	PUNCT
cana-803	181	6	based	base	VERB
cana-803	181	7	methods	method	NOUN
cana-803	181	8	can	can	AUX
cana-803	181	9	give	give	VERB
cana-803	181	10	useful	useful	ADJ
cana-803	181	11	information	information	NOUN
cana-803	181	12	,	,	PUNCT
cana-803	181	13	machine	machine	NOUN
cana-803	181	14	learning	learning	NOUN
cana-803	181	15	-	-	PUNCT
cana-803	181	16	based	base	VERB
cana-803	181	17	methods	method	NOUN
cana-803	181	18	and	and	CCONJ
cana-803	181	19	the	the	DET
cana-803	181	20	suggested	suggest	VERB
cana-803	181	21	algorithm	algorithm	NOUN
cana-803	181	22	work	work	VERB
cana-803	181	23	better	well	ADV
cana-803	181	24	in	in	ADP
cana-803	181	25	terms	term	NOUN
cana-803	181	26	of	of	ADP
cana-803	181	27	accuracy	accuracy	NOUN
cana-803	181	28	,	,	PUNCT
cana-803	181	29	precision	precision	NOUN
cana-803	181	30	,	,	PUNCT
cana-803	181	31	and	and	CCONJ
cana-803	181	32	memory	memory	NOUN
cana-803	181	33	.	.	PUNCT
cana-803	182	1	these	these	DET
cana-803	182	2	results	result	NOUN
cana-803	182	3	make	make	VERB
cana-803	182	4	it	it	PRON
cana-803	182	5	clear	clear	ADJ
cana-803	182	6	how	how	SCONJ
cana-803	182	7	important	important	ADJ
cana-803	182	8	it	it	PRON
cana-803	182	9	is	be	AUX
cana-803	182	10	to	to	PART
cana-803	182	11	use	use	VERB
cana-803	182	12	advanced	advanced	ADJ
cana-803	182	13	analytics	analytic	NOUN
cana-803	182	14	and	and	CCONJ
cana-803	182	15	flexible	flexible	ADJ
cana-803	182	16	strategies	strategy	NOUN
cana-803	182	17	to	to	PART
cana-803	182	18	find	find	VERB
cana-803	182	19	and	and	CCONJ
cana-803	182	20	stop	stop	VERB
cana-803	182	21	cyber	cyber	NOUN
cana-803	182	22	dangers	danger	NOUN
cana-803	182	23	in	in	ADP
cana-803	182	24	real	real	ADJ
cana-803	182	25	time	time	NOUN
cana-803	182	26	,	,	PUNCT
cana-803	182	27	protecting	protect	VERB
cana-803	182	28	network	network	NOUN
cana-803	182	29	infrastructure	infrastructure	NOUN
cana-803	182	30	and	and	CCONJ
cana-803	182	31	data	datum	NOUN
cana-803	182	32	security	security	NOUN
cana-803	182	33	.	.	PUNCT
cana-803	183	1	figure	figure	VERB
cana-803	183	2	3	3	NUM
cana-803	183	3	:	:	PUNCT
cana-803	183	4	accuracy	accuracy	NOUN
cana-803	183	5	of	of	ADP
cana-803	183	6	different	different	ADJ
cana-803	183	7	model	model	NOUN
cana-803	183	8	for	for	ADP
cana-803	183	9	attack	attack	NOUN
cana-803	183	10	signature	signature	NOUN
cana-803	183	11	identification	identification	NOUN
cana-803	183	12	the	the	DET
cana-803	183	13	figure	figure	NOUN
cana-803	183	14	(	(	PUNCT
cana-803	183	15	3	3	X
cana-803	183	16	)	)	PUNCT
cana-803	183	17	shows	show	VERB
cana-803	183	18	a	a	DET
cana-803	183	19	bar	bar	NOUN
cana-803	183	20	graph	graph	NOUN
cana-803	183	21	that	that	PRON
cana-803	183	22	shows	show	VERB
cana-803	183	23	how	how	SCONJ
cana-803	183	24	accurate	accurate	ADJ
cana-803	183	25	different	different	ADJ
cana-803	183	26	ways	way	NOUN
cana-803	183	27	are	be	AUX
cana-803	183	28	at	at	ADP
cana-803	183	29	finding	find	VERB
cana-803	183	30	attack	attack	NOUN
cana-803	183	31	signatures	signature	NOUN
cana-803	183	32	.	.	PUNCT
cana-803	184	1	each	each	DET
cana-803	184	2	method	method	NOUN
cana-803	184	3	,	,	PUNCT
cana-803	184	4	such	such	ADJ
cana-803	184	5	as	as	ADP
cana-803	184	6	signature	signature	NOUN
cana-803	184	7	-	-	PUNCT
cana-803	184	8	based	base	VERB
cana-803	184	9	ids	id	NOUN
cana-803	184	10	,	,	PUNCT
cana-803	184	11	anomaly	anomaly	NOUN
cana-803	184	12	-	-	PUNCT
cana-803	184	13	based	base	VERB
cana-803	184	14	ids	id	NOUN
cana-803	184	15	,	,	PUNCT
cana-803	184	16	a	a	DET
cana-803	184	17	machine	machine	NOUN
cana-803	184	18	learning	learn	VERB
cana-803	184	19	approach	approach	NOUN
cana-803	184	20	,	,	PUNCT
cana-803	184	21	and	and	CCONJ
cana-803	184	22	the	the	DET
cana-803	184	23	suggested	suggest	VERB
cana-803	184	24	algorithm	algorithm	NOUN
cana-803	184	25	,	,	PUNCT
cana-803	184	26	is	be	AUX
cana-803	184	27	shown	show	VERB
cana-803	184	28	by	by	ADP
cana-803	184	29	a	a	DET
cana-803	184	30	bar	bar	NOUN
cana-803	184	31	.	.	PUNCT
cana-803	185	1	communications	communication	NOUN
cana-803	185	2	on	on	ADP
cana-803	185	3	applied	apply	VERB
cana-803	185	4	nonlinear	nonlinear	ADJ
cana-803	185	5	analysis	analysis	NOUN
cana-803	185	6	issn	issn	NOUN
cana-803	185	7	:	:	PUNCT
cana-803	185	8	1074	1074	NUM
cana-803	185	9	-	-	PUNCT
cana-803	185	10	133x	133x	NUM
cana-803	185	11	vol	vol	NOUN
cana-803	185	12	31	31	NUM
cana-803	185	13	no	no	NOUN
cana-803	185	14	.	.	PUNCT
cana-803	186	1	3s	3s	NUM
cana-803	186	2	(	(	PUNCT
cana-803	186	3	2024	2024	NUM
cana-803	186	4	)	)	PUNCT
cana-803	186	5	497	497	NUM
cana-803	186	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-803	186	7	figure	figure	NOUN
cana-803	186	8	4	4	NUM
cana-803	186	9	:	:	PUNCT
cana-803	186	10	performance	performance	NOUN
cana-803	186	11	metric	metric	NOUN
cana-803	186	12	of	of	ADP
cana-803	186	13	different	different	ADJ
cana-803	186	14	methods	method	NOUN
cana-803	186	15	for	for	ADP
cana-803	186	16	attack	attack	NOUN
cana-803	186	17	signature	signature	NOUN
cana-803	186	18	identification	identification	NOUN
cana-803	186	19	the	the	DET
cana-803	186	20	height	height	NOUN
cana-803	186	21	of	of	ADP
cana-803	186	22	the	the	DET
cana-803	186	23	bar	bar	NOUN
cana-803	186	24	shows	show	VERB
cana-803	186	25	what	what	DET
cana-803	186	26	percentage	percentage	NOUN
cana-803	186	27	of	of	ADP
cana-803	186	28	the	the	DET
cana-803	186	29	time	time	NOUN
cana-803	186	30	the	the	DET
cana-803	186	31	method	method	NOUN
cana-803	186	32	is	be	AUX
cana-803	186	33	correct	correct	ADJ
cana-803	186	34	.	.	PUNCT
cana-803	187	1	the	the	DET
cana-803	187	2	suggested	suggest	VERB
cana-803	187	3	algorithm	algorithm	NOUN
cana-803	187	4	stands	stand	VERB
cana-803	187	5	out	out	ADP
cana-803	187	6	because	because	SCONJ
cana-803	187	7	it	it	PRON
cana-803	187	8	is	be	AUX
cana-803	187	9	the	the	DET
cana-803	187	10	most	most	ADV
cana-803	187	11	accurate	accurate	ADJ
cana-803	187	12	(	(	PUNCT
cana-803	187	13	92	92	NUM
cana-803	187	14	%	%	NOUN
cana-803	187	15	of	of	ADP
cana-803	187	16	the	the	DET
cana-803	187	17	time	time	NOUN
cana-803	187	18	)	)	PUNCT
cana-803	187	19	,	,	PUNCT
cana-803	187	20	which	which	PRON
cana-803	187	21	means	mean	VERB
cana-803	187	22	it	it	PRON
cana-803	187	23	is	be	AUX
cana-803	187	24	better	well	ADJ
cana-803	187	25	at	at	ADP
cana-803	187	26	correctly	correctly	ADV
cana-803	187	27	finding	find	VERB
cana-803	187	28	attack	attack	NOUN
cana-803	187	29	patterns	pattern	NOUN
cana-803	187	30	than	than	ADP
cana-803	187	31	other	other	ADJ
cana-803	187	32	methods	method	NOUN
cana-803	187	33	.	.	PUNCT
cana-803	188	1	the	the	DET
cana-803	188	2	machine	machine	NOUN
cana-803	188	3	learning	learn	VERB
cana-803	188	4	approach	approach	NOUN
cana-803	188	5	comes	come	VERB
cana-803	188	6	in	in	ADP
cana-803	188	7	second	second	ADJ
cana-803	188	8	with	with	ADP
cana-803	188	9	an	an	DET
cana-803	188	10	accuracy	accuracy	NOUN
cana-803	188	11	rate	rate	NOUN
cana-803	188	12	of	of	ADP
cana-803	188	13	88	88	NUM
cana-803	188	14	%	%	NOUN
cana-803	188	15	,	,	PUNCT
cana-803	188	16	showing	show	VERB
cana-803	188	17	how	how	SCONJ
cana-803	188	18	well	well	ADV
cana-803	188	19	it	it	PRON
cana-803	188	20	can	can	AUX
cana-803	188	21	use	use	VERB
cana-803	188	22	data	data	NOUN
cana-803	188	23	-	-	PUNCT
cana-803	188	24	driven	drive	VERB
cana-803	188	25	methods	method	NOUN
cana-803	188	26	for	for	ADP
cana-803	188	27	accurate	accurate	ADJ
cana-803	188	28	spotting	spotting	NOUN
cana-803	188	29	.	.	PUNCT
cana-803	189	1	the	the	DET
cana-803	189	2	accuracy	accuracy	NOUN
cana-803	189	3	numbers	number	NOUN
cana-803	189	4	for	for	ADP
cana-803	189	5	signature	signature	NOUN
cana-803	189	6	-	-	PUNCT
cana-803	189	7	based	base	VERB
cana-803	189	8	ids	id	NOUN
cana-803	189	9	and	and	CCONJ
cana-803	189	10	anomaly	anomaly	NOUN
cana-803	189	11	-	-	PUNCT
cana-803	189	12	based	base	VERB
cana-803	189	13	ids	id	NOUN
cana-803	189	14	are	be	AUX
cana-803	189	15	lower	low	ADJ
cana-803	189	16	,	,	PUNCT
cana-803	189	17	at	at	ADP
cana-803	189	18	85	85	NUM
cana-803	189	19	%	%	NOUN
cana-803	189	20	and	and	CCONJ
cana-803	189	21	80	80	NUM
cana-803	189	22	%	%	NOUN
cana-803	189	23	,	,	PUNCT
cana-803	189	24	respectively	respectively	ADV
cana-803	189	25	.	.	PUNCT
cana-803	190	1	this	this	PRON
cana-803	190	2	suggests	suggest	VERB
cana-803	190	3	that	that	SCONJ
cana-803	190	4	they	they	PRON
cana-803	190	5	may	may	AUX
cana-803	190	6	not	not	PART
cana-803	190	7	be	be	AUX
cana-803	190	8	able	able	ADJ
cana-803	190	9	to	to	PART
cana-803	190	10	correctly	correctly	ADV
cana-803	190	11	find	find	VERB
cana-803	190	12	and	and	CCONJ
cana-803	190	13	classify	classify	VERB
cana-803	190	14	harmful	harmful	ADJ
cana-803	190	15	actions	action	NOUN
cana-803	190	16	.	.	PUNCT
cana-803	191	1	there	there	PRON
cana-803	191	2	is	be	VERB
cana-803	191	3	a	a	DET
cana-803	191	4	clear	clear	ADJ
cana-803	191	5	visual	visual	ADJ
cana-803	191	6	comparison	comparison	NOUN
cana-803	191	7	of	of	ADP
cana-803	191	8	the	the	DET
cana-803	191	9	levels	level	NOUN
cana-803	191	10	of	of	ADP
cana-803	191	11	accuracy	accuracy	NOUN
cana-803	191	12	achieved	achieve	VERB
cana-803	191	13	by	by	ADP
cana-803	191	14	each	each	DET
cana-803	191	15	method	method	NOUN
cana-803	191	16	in	in	ADP
cana-803	191	17	the	the	DET
cana-803	191	18	bar	bar	NOUN
cana-803	191	19	graph	graph	NOUN
cana-803	191	20	.	.	PUNCT
cana-803	192	1	this	this	PRON
cana-803	192	2	shows	show	VERB
cana-803	192	3	that	that	SCONJ
cana-803	192	4	the	the	DET
cana-803	192	5	suggested	suggest	VERB
cana-803	192	6	algorithm	algorithm	NOUN
cana-803	192	7	is	be	AUX
cana-803	192	8	better	well	ADJ
cana-803	192	9	at	at	ADP
cana-803	192	10	identifying	identify	VERB
cana-803	192	11	attack	attack	NOUN
cana-803	192	12	signatures	signature	NOUN
cana-803	192	13	with	with	ADP
cana-803	192	14	high	high	ADJ
cana-803	192	15	accuracy	accuracy	NOUN
cana-803	192	16	.	.	PUNCT
cana-803	193	1	the	the	DET
cana-803	193	2	line	line	NOUN
cana-803	193	3	graph	graph	NOUN
cana-803	193	4	as	as	SCONJ
cana-803	193	5	shown	show	VERB
cana-803	193	6	in	in	ADP
cana-803	193	7	the	the	DET
cana-803	193	8	figure	figure	NOUN
cana-803	193	9	(	(	PUNCT
cana-803	193	10	4	4	NUM
cana-803	193	11	)	)	PUNCT
cana-803	193	12	,	,	PUNCT
cana-803	193	13	illustrates	illustrate	VERB
cana-803	193	14	the	the	DET
cana-803	193	15	performance	performance	NOUN
cana-803	193	16	metrics	metric	NOUN
cana-803	193	17	(	(	PUNCT
cana-803	193	18	accuracy	accuracy	NOUN
cana-803	193	19	,	,	PUNCT
cana-803	193	20	precision	precision	NOUN
cana-803	193	21	,	,	PUNCT
cana-803	193	22	f1	f1	NOUN
cana-803	193	23	score	score	NOUN
cana-803	193	24	,	,	PUNCT
cana-803	193	25	and	and	CCONJ
cana-803	193	26	recall	recall	NOUN
cana-803	193	27	)	)	PUNCT
cana-803	193	28	of	of	ADP
cana-803	193	29	various	various	ADJ
cana-803	193	30	methods	method	NOUN
cana-803	193	31	for	for	ADP
cana-803	193	32	attack	attack	NOUN
cana-803	193	33	signature	signature	NOUN
cana-803	193	34	identification	identification	NOUN
cana-803	193	35	.	.	PUNCT
cana-803	194	1	each	each	DET
cana-803	194	2	method	method	NOUN
cana-803	194	3	,	,	PUNCT
cana-803	194	4	including	include	VERB
cana-803	194	5	signature	signature	NOUN
cana-803	194	6	-	-	PUNCT
cana-803	194	7	based	base	VERB
cana-803	194	8	ids	id	NOUN
cana-803	194	9	,	,	PUNCT
cana-803	194	10	anomaly	anomaly	NOUN
cana-803	194	11	-	-	PUNCT
cana-803	194	12	based	base	VERB
cana-803	194	13	ids	id	NOUN
cana-803	194	14	,	,	PUNCT
cana-803	194	15	a	a	DET
cana-803	194	16	machine	machine	NOUN
cana-803	194	17	learning	learn	VERB
cana-803	194	18	approach	approach	NOUN
cana-803	194	19	,	,	PUNCT
cana-803	194	20	and	and	CCONJ
cana-803	194	21	the	the	DET
cana-803	194	22	proposed	propose	VERB
cana-803	194	23	algorithm	algorithm	NOUN
cana-803	194	24	,	,	PUNCT
cana-803	194	25	is	be	AUX
cana-803	194	26	represented	represent	VERB
cana-803	194	27	by	by	ADP
cana-803	194	28	lines	line	NOUN
cana-803	194	29	on	on	ADP
cana-803	194	30	the	the	DET
cana-803	194	31	graph	graph	NOUN
cana-803	194	32	.	.	PUNCT
cana-803	195	1	the	the	DET
cana-803	195	2	x	x	X
cana-803	195	3	-	-	ADJ
cana-803	195	4	axis	axis	NOUN
cana-803	195	5	indicates	indicate	VERB
cana-803	195	6	the	the	DET
cana-803	195	7	methods	method	NOUN
cana-803	195	8	,	,	PUNCT
cana-803	195	9	while	while	SCONJ
cana-803	195	10	the	the	DET
cana-803	195	11	y	y	NOUN
cana-803	195	12	-	-	PUNCT
cana-803	195	13	axis	axis	NOUN
cana-803	195	14	represents	represent	VERB
cana-803	195	15	the	the	DET
cana-803	195	16	percentage	percentage	NOUN
cana-803	195	17	values	value	NOUN
cana-803	195	18	of	of	ADP
cana-803	195	19	the	the	DET
cana-803	195	20	performance	performance	NOUN
cana-803	195	21	metrics	metric	NOUN
cana-803	195	22	.	.	PUNCT
cana-803	196	1	the	the	DET
cana-803	196	2	proposed	propose	VERB
cana-803	196	3	algorithm	algorithm	NOUN
cana-803	196	4	consistently	consistently	ADV
cana-803	196	5	outperforms	outperform	VERB
cana-803	196	6	other	other	ADJ
cana-803	196	7	methods	method	NOUN
cana-803	196	8	across	across	ADP
cana-803	196	9	all	all	DET
cana-803	196	10	metrics	metric	NOUN
cana-803	196	11	,	,	PUNCT
cana-803	196	12	exhibiting	exhibit	VERB
cana-803	196	13	higher	high	ADJ
cana-803	196	14	values	value	NOUN
cana-803	196	15	for	for	ADP
cana-803	196	16	accuracy	accuracy	NOUN
cana-803	196	17	,	,	PUNCT
cana-803	196	18	precision	precision	NOUN
cana-803	196	19	,	,	PUNCT
cana-803	196	20	f1	f1	NOUN
cana-803	196	21	score	score	NOUN
cana-803	196	22	,	,	PUNCT
cana-803	196	23	and	and	CCONJ
cana-803	196	24	recall	recall	NOUN
cana-803	196	25	.	.	PUNCT
cana-803	197	1	the	the	DET
cana-803	197	2	graph	graph	NOUN
cana-803	197	3	provides	provide	VERB
cana-803	197	4	a	a	DET
cana-803	197	5	clear	clear	ADJ
cana-803	197	6	visual	visual	ADJ
cana-803	197	7	comparison	comparison	NOUN
cana-803	197	8	of	of	ADP
cana-803	197	9	the	the	DET
cana-803	197	10	performance	performance	NOUN
cana-803	197	11	of	of	ADP
cana-803	197	12	each	each	DET
cana-803	197	13	method	method	NOUN
cana-803	197	14	,	,	PUNCT
cana-803	197	15	highlighting	highlight	VERB
cana-803	197	16	the	the	DET
cana-803	197	17	strengths	strength	NOUN
cana-803	197	18	of	of	ADP
cana-803	197	19	the	the	DET
cana-803	197	20	proposed	propose	VERB
cana-803	197	21	algorithm	algorithm	NOUN
cana-803	197	22	in	in	ADP
cana-803	197	23	achieving	achieve	VERB
cana-803	197	24	superior	superior	ADJ
cana-803	197	25	performance	performance	NOUN
cana-803	197	26	in	in	ADP
cana-803	197	27	attack	attack	NOUN
cana-803	197	28	signature	signature	NOUN
cana-803	197	29	identification	identification	NOUN
cana-803	197	30	.	.	PUNCT
cana-803	198	1	table	table	NOUN
cana-803	198	2	3	3	NUM
cana-803	198	3	:	:	PUNCT
cana-803	198	4	performance	performance	NOUN
cana-803	198	5	metric	metric	NOUN
cana-803	198	6	of	of	ADP
cana-803	198	7	stochastic	stochastic	ADJ
cana-803	198	8	optimization	optimization	NOUN
cana-803	198	9	algorithm	algorithm	NOUN
cana-803	198	10	method	method	NOUN
cana-803	198	11	accuracy	accuracy	NOUN
cana-803	198	12	(	(	PUNCT
cana-803	198	13	%	%	INTJ
cana-803	198	14	)	)	PUNCT
cana-803	198	15	precision	precision	NOUN
cana-803	198	16	(	(	PUNCT
cana-803	198	17	%	%	INTJ
cana-803	198	18	)	)	PUNCT
cana-803	198	19	f1	f1	NOUN
cana-803	198	20	score	score	NOUN
cana-803	198	21	(	(	PUNCT
cana-803	198	22	%	%	INTJ
cana-803	198	23	)	)	PUNCT
cana-803	198	24	recall	recall	NOUN
cana-803	198	25	(	(	PUNCT
cana-803	198	26	%	%	NOUN
cana-803	198	27	)	)	PUNCT
cana-803	198	28	signature	signature	NOUN
cana-803	198	29	-	-	PUNCT
cana-803	198	30	based	base	VERB
cana-803	198	31	ids	id	NOUN
cana-803	198	32	85	85	NUM
cana-803	198	33	80	80	NUM
cana-803	198	34	87	87	NUM
cana-803	198	35	85	85	NUM
cana-803	198	36	anomaly	anomaly	NOUN
cana-803	198	37	-	-	PUNCT
cana-803	198	38	based	base	VERB
cana-803	198	39	ids	id	NOUN
cana-803	198	40	80	80	NUM
cana-803	198	41	75	75	NUM
cana-803	198	42	82	82	NUM
cana-803	198	43	78	78	NUM
cana-803	198	44	communications	communication	NOUN
cana-803	198	45	on	on	ADP
cana-803	198	46	applied	apply	VERB
cana-803	198	47	nonlinear	nonlinear	ADJ
cana-803	198	48	analysis	analysis	NOUN
cana-803	198	49	issn	issn	NOUN
cana-803	198	50	:	:	PUNCT
cana-803	198	51	1074	1074	NUM
cana-803	198	52	-	-	PUNCT
cana-803	198	53	133x	133x	NUM
cana-803	198	54	vol	vol	NOUN
cana-803	198	55	31	31	NUM
cana-803	198	56	no	no	NOUN
cana-803	198	57	.	.	PUNCT
cana-803	199	1	3s	3s	NUM
cana-803	199	2	(	(	PUNCT
cana-803	199	3	2024	2024	NUM
cana-803	199	4	)	)	PUNCT
cana-803	199	5	498	498	NUM
cana-803	199	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-803	199	7	machine	machine	NOUN
cana-803	199	8	learning	learn	VERB
cana-803	199	9	approach	approach	NOUN
cana-803	199	10	88	88	NUM
cana-803	199	11	86	86	NUM
cana-803	199	12	89	89	NUM
cana-803	199	13	87	87	NUM
cana-803	199	14	proposed	propose	VERB
cana-803	199	15	algorithm	algorithm	NOUN
cana-803	199	16	(	(	PUNCT
cana-803	199	17	before	before	ADP
cana-803	199	18	)	)	PUNCT
cana-803	199	19	92	92	NUM
cana-803	199	20	90	90	NUM
cana-803	199	21	93	93	NUM
cana-803	199	22	91	91	NUM
cana-803	199	23	proposed	propose	VERB
cana-803	199	24	algorithm	algorithm	NOUN
cana-803	199	25	(	(	PUNCT
cana-803	199	26	after	after	ADP
cana-803	199	27	)	)	PUNCT
cana-803	199	28	95	95	NUM
cana-803	199	29	92	92	NUM
cana-803	199	30	96	96	NUM
cana-803	199	31	94	94	NUM
cana-803	199	32	the	the	DET
cana-803	199	33	table	table	NOUN
cana-803	199	34	3	3	NUM
cana-803	199	35	,	,	PUNCT
cana-803	199	36	shows	show	VERB
cana-803	199	37	how	how	SCONJ
cana-803	199	38	well	well	ADV
cana-803	199	39	different	different	ADJ
cana-803	199	40	attack	attack	NOUN
cana-803	199	41	signature	signature	NOUN
cana-803	199	42	recognition	recognition	NOUN
cana-803	199	43	methods	method	NOUN
cana-803	199	44	work	work	VERB
cana-803	199	45	.	.	PUNCT
cana-803	200	1	these	these	PRON
cana-803	200	2	include	include	VERB
cana-803	200	3	signature	signature	NOUN
cana-803	200	4	-	-	PUNCT
cana-803	200	5	based	base	VERB
cana-803	200	6	ids	id	NOUN
cana-803	200	7	,	,	PUNCT
cana-803	200	8	anomaly	anomaly	NOUN
cana-803	200	9	-	-	PUNCT
cana-803	200	10	based	base	VERB
cana-803	200	11	ids	id	NOUN
cana-803	200	12	,	,	PUNCT
cana-803	200	13	a	a	DET
cana-803	200	14	machine	machine	NOUN
cana-803	200	15	learning	learn	VERB
cana-803	200	16	approach	approach	NOUN
cana-803	200	17	,	,	PUNCT
cana-803	200	18	and	and	CCONJ
cana-803	200	19	the	the	DET
cana-803	200	20	suggested	suggest	VERB
cana-803	200	21	algorithm	algorithm	NOUN
cana-803	200	22	both	both	CCONJ
cana-803	200	23	before	before	ADP
cana-803	200	24	and	and	CCONJ
cana-803	200	25	after	after	ADP
cana-803	200	26	random	random	ADJ
cana-803	200	27	optimization	optimization	NOUN
cana-803	200	28	techniques	technique	NOUN
cana-803	200	29	were	be	AUX
cana-803	200	30	used	use	VERB
cana-803	200	31	.	.	PUNCT
cana-803	201	1	there	there	PRON
cana-803	201	2	is	be	VERB
cana-803	201	3	an	an	DET
cana-803	201	4	initial	initial	ADJ
cana-803	201	5	accuracy	accuracy	NOUN
cana-803	201	6	of	of	ADP
cana-803	201	7	85	85	NUM
cana-803	201	8	%	%	NOUN
cana-803	201	9	for	for	ADP
cana-803	201	10	the	the	DET
cana-803	201	11	signature	signature	NOUN
cana-803	201	12	-	-	PUNCT
cana-803	201	13	based	base	VERB
cana-803	201	14	ids	id	NOUN
cana-803	201	15	,	,	PUNCT
cana-803	201	16	with	with	ADP
cana-803	201	17	80	80	NUM
cana-803	201	18	%	%	NOUN
cana-803	201	19	for	for	ADP
cana-803	201	20	precision	precision	NOUN
cana-803	201	21	,	,	PUNCT
cana-803	201	22	85	85	NUM
cana-803	201	23	%	%	NOUN
cana-803	201	24	for	for	ADP
cana-803	201	25	memory	memory	NOUN
cana-803	201	26	,	,	PUNCT
cana-803	201	27	and	and	CCONJ
cana-803	201	28	87	87	NUM
cana-803	201	29	%	%	NOUN
cana-803	201	30	for	for	ADP
cana-803	201	31	f1	f1	NOUN
cana-803	201	32	.	.	PUNCT
cana-803	202	1	with	with	ADP
cana-803	202	2	an	an	DET
cana-803	202	3	accuracy	accuracy	NOUN
cana-803	202	4	of	of	ADP
cana-803	202	5	80	80	NUM
cana-803	202	6	%	%	NOUN
cana-803	202	7	,	,	PUNCT
cana-803	202	8	a	a	DET
cana-803	202	9	precision	precision	NOUN
cana-803	202	10	of	of	ADP
cana-803	202	11	75	75	NUM
cana-803	202	12	%	%	NOUN
cana-803	202	13	,	,	PUNCT
cana-803	202	14	a	a	DET
cana-803	202	15	recall	recall	NOUN
cana-803	202	16	of	of	ADP
cana-803	202	17	78	78	NUM
cana-803	202	18	%	%	NOUN
cana-803	202	19	,	,	PUNCT
cana-803	202	20	and	and	CCONJ
cana-803	202	21	an	an	DET
cana-803	202	22	f1	f1	ADJ
cana-803	202	23	score	score	NOUN
cana-803	202	24	of	of	ADP
cana-803	202	25	82	82	NUM
cana-803	202	26	%	%	NOUN
cana-803	202	27	,	,	PUNCT
cana-803	202	28	the	the	DET
cana-803	202	29	anomaly	anomaly	NOUN
cana-803	202	30	-	-	PUNCT
cana-803	202	31	based	base	VERB
cana-803	202	32	ids	id	NOUN
cana-803	202	33	does	do	AUX
cana-803	202	34	a	a	DET
cana-803	202	35	little	little	ADJ
cana-803	202	36	worse	bad	ADJ
cana-803	202	37	.	.	PUNCT
cana-803	203	1	with	with	ADP
cana-803	203	2	precision	precision	NOUN
cana-803	203	3	scores	score	NOUN
cana-803	203	4	of	of	ADP
cana-803	203	5	86	86	NUM
cana-803	203	6	%	%	NOUN
cana-803	203	7	,	,	PUNCT
cana-803	203	8	memory	memory	NOUN
cana-803	203	9	scores	score	NOUN
cana-803	203	10	of	of	ADP
cana-803	203	11	87	87	NUM
cana-803	203	12	%	%	NOUN
cana-803	203	13	,	,	PUNCT
cana-803	203	14	and	and	CCONJ
cana-803	203	15	f1	f1	NOUN
cana-803	203	16	scores	score	NOUN
cana-803	203	17	of	of	ADP
cana-803	203	18	89	89	NUM
cana-803	203	19	%	%	NOUN
cana-803	203	20	,	,	PUNCT
cana-803	203	21	the	the	DET
cana-803	203	22	machine	machine	NOUN
cana-803	203	23	learning	learning	NOUN
cana-803	203	24	method	method	NOUN
cana-803	203	25	is	be	AUX
cana-803	203	26	more	more	ADV
cana-803	203	27	accurate	accurate	ADJ
cana-803	203	28	(	(	PUNCT
cana-803	203	29	88	88	NUM
cana-803	203	30	%	%	NOUN
cana-803	203	31	)	)	PUNCT
cana-803	203	32	.	.	PUNCT
cana-803	204	1	(	(	PUNCT
cana-803	204	2	a	a	X
cana-803	204	3	)	)	PUNCT
cana-803	204	4	(	(	PUNCT
cana-803	204	5	b	b	X
cana-803	204	6	)	)	PUNCT
cana-803	204	7	(	(	PUNCT
cana-803	204	8	c	c	X
cana-803	204	9	)	)	PUNCT
cana-803	204	10	(	(	PUNCT
cana-803	204	11	d	d	X
cana-803	204	12	)	)	PUNCT
cana-803	204	13	figure	figure	NOUN
cana-803	204	14	5	5	NUM
cana-803	204	15	:	:	PUNCT
cana-803	204	16	performance	performance	NOUN
cana-803	204	17	metrics	metric	NOUN
cana-803	204	18	of	of	ADP
cana-803	204	19	various	various	ADJ
cana-803	204	20	methods	method	NOUN
cana-803	204	21	for	for	ADP
cana-803	204	22	attack	attack	NOUN
cana-803	204	23	signature	signature	NOUN
cana-803	204	24	identification	identification	NOUN
cana-803	204	25	(	(	PUNCT
cana-803	204	26	a	a	NOUN
cana-803	204	27	)	)	PUNCT
cana-803	204	28	accuracy	accuracy	NOUN
cana-803	204	29	(	(	PUNCT
cana-803	204	30	b	b	NOUN
cana-803	204	31	)	)	PUNCT
cana-803	204	32	precision	precision	NOUN
cana-803	204	33	(	(	PUNCT
cana-803	204	34	c	c	NOUN
cana-803	204	35	)	)	PUNCT
cana-803	204	36	f1	f1	NOUN
cana-803	204	37	score	score	NOUN
cana-803	204	38	(	(	PUNCT
cana-803	204	39	d	d	NOUN
cana-803	204	40	)	)	PUNCT
cana-803	204	41	recall	recall	NOUN
cana-803	204	42	with	with	ADP
cana-803	204	43	an	an	DET
cana-803	204	44	accuracy	accuracy	NOUN
cana-803	204	45	of	of	ADP
cana-803	204	46	92	92	NUM
cana-803	204	47	%	%	NOUN
cana-803	204	48	,	,	PUNCT
cana-803	204	49	a	a	DET
cana-803	204	50	precision	precision	NOUN
cana-803	204	51	of	of	ADP
cana-803	204	52	90	90	NUM
cana-803	204	53	%	%	NOUN
cana-803	204	54	,	,	PUNCT
cana-803	204	55	a	a	DET
cana-803	204	56	recall	recall	NOUN
cana-803	204	57	of	of	ADP
cana-803	204	58	91	91	NUM
cana-803	204	59	%	%	NOUN
cana-803	204	60	,	,	PUNCT
cana-803	204	61	and	and	CCONJ
cana-803	204	62	an	an	DET
cana-803	204	63	f1	f1	ADJ
cana-803	204	64	score	score	NOUN
cana-803	204	65	of	of	ADP
cana-803	204	66	93	93	NUM
cana-803	204	67	%	%	NOUN
cana-803	204	68	,	,	PUNCT
cana-803	204	69	the	the	DET
cana-803	204	70	suggested	suggest	VERB
cana-803	204	71	method	method	NOUN
cana-803	204	72	already	already	ADV
cana-803	204	73	does	do	VERB
cana-803	204	74	a	a	DET
cana-803	204	75	good	good	ADJ
cana-803	204	76	job	job	NOUN
cana-803	204	77	without	without	ADP
cana-803	204	78	random	random	ADJ
cana-803	204	79	optimization	optimization	NOUN
cana-803	204	80	.	.	PUNCT
cana-803	205	1	but	but	CCONJ
cana-803	205	2	when	when	SCONJ
cana-803	205	3	stochastic	stochastic	ADJ
cana-803	205	4	optimization	optimization	NOUN
cana-803	205	5	methods	method	NOUN
cana-803	205	6	are	be	AUX
cana-803	205	7	used	use	VERB
cana-803	205	8	,	,	PUNCT
cana-803	205	9	its	its	PRON
cana-803	205	10	performance	performance	NOUN
cana-803	205	11	gets	get	VERB
cana-803	205	12	a	a	DET
cana-803	205	13	lot	lot	NOUN
cana-803	205	14	better	well	ADJ
cana-803	205	15	.	.	PUNCT
cana-803	206	1	its	its	PRON
cana-803	206	2	accuracy	accuracy	NOUN
cana-803	206	3	goes	go	VERB
cana-803	206	4	up	up	ADP
cana-803	206	5	to	to	PART
cana-803	206	6	95	95	NUM
cana-803	206	7	%	%	NOUN
cana-803	206	8	,	,	PUNCT
cana-803	206	9	its	its	PRON
cana-803	206	10	precision	precision	NOUN
cana-803	206	11	to	to	ADP
cana-803	206	12	92	92	NUM
cana-803	206	13	%	%	NOUN
cana-803	206	14	,	,	PUNCT
cana-803	206	15	its	its	PRON
cana-803	206	16	memory	memory	NOUN
cana-803	206	17	to	to	ADP
cana-803	206	18	94	94	NUM
cana-803	206	19	%	%	NOUN
cana-803	206	20	,	,	PUNCT
cana-803	206	21	and	and	CCONJ
cana-803	206	22	its	its	PRON
cana-803	206	23	f1	f1	ADJ
cana-803	206	24	score	score	NOUN
cana-803	206	25	to	to	ADP
cana-803	206	26	96	96	NUM
cana-803	206	27	%	%	NOUN
cana-803	206	28	.	.	PUNCT
cana-803	207	1	these	these	DET
cana-803	207	2	improvements	improvement	NOUN
cana-803	207	3	show	show	VERB
cana-803	207	4	that	that	SCONJ
cana-803	207	5	stochastic	stochastic	ADJ
cana-803	207	6	optimization	optimization	NOUN
cana-803	207	7	is	be	AUX
cana-803	207	8	a	a	DET
cana-803	207	9	good	good	ADJ
cana-803	207	10	way	way	NOUN
cana-803	207	11	to	to	ADP
cana-803	207	12	fine	fine	ADJ
cana-803	207	13	-	-	PUNCT
cana-803	207	14	tune	tune	NOUN
cana-803	207	15	the	the	DET
cana-803	207	16	suggested	suggest	VERB
cana-803	207	17	method	method	NOUN
cana-803	207	18	,	,	PUNCT
cana-803	207	19	which	which	PRON
cana-803	207	20	leads	lead	VERB
cana-803	207	21	to	to	ADP
cana-803	207	22	better	well	ADJ
cana-803	207	23	accuracy	accuracy	NOUN
cana-803	207	24	,	,	PUNCT
cana-803	207	25	precision	precision	NOUN
cana-803	207	26	,	,	PUNCT
cana-803	207	27	memory	memory	NOUN
cana-803	207	28	,	,	PUNCT
cana-803	207	29	and	and	CCONJ
cana-803	207	30	total	total	ADJ
cana-803	207	31	performance	performance	NOUN
cana-803	207	32	when	when	SCONJ
cana-803	207	33	looking	look	VERB
cana-803	207	34	for	for	ADP
cana-803	207	35	attack	attack	NOUN
cana-803	207	36	patterns	pattern	NOUN
cana-803	207	37	in	in	ADP
cana-803	207	38	network	network	NOUN
cana-803	207	39	communications	communication	NOUN
cana-803	207	40	on	on	ADP
cana-803	207	41	applied	apply	VERB
cana-803	207	42	nonlinear	nonlinear	ADJ
cana-803	207	43	analysis	analysis	NOUN
cana-803	207	44	issn	issn	NOUN
cana-803	207	45	:	:	PUNCT
cana-803	207	46	1074	1074	NUM
cana-803	207	47	-	-	PUNCT
cana-803	207	48	133x	133x	NUM
cana-803	207	49	vol	vol	NOUN
cana-803	207	50	31	31	NUM
cana-803	207	51	no	no	NOUN
cana-803	207	52	.	.	PUNCT
cana-803	208	1	3s	3s	NUM
cana-803	208	2	(	(	PUNCT
cana-803	208	3	2024	2024	NUM
cana-803	208	4	)	)	PUNCT
cana-803	208	5	499	499	NUM
cana-803	208	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-803	208	7	traffic	traffic	NOUN
cana-803	208	8	.	.	PUNCT
cana-803	209	1	figure	figure	NOUN
cana-803	209	2	(	(	PUNCT
cana-803	209	3	5	5	NUM
cana-803	209	4	)	)	PUNCT
cana-803	209	5	shows	show	VERB
cana-803	209	6	a	a	DET
cana-803	209	7	set	set	NOUN
cana-803	209	8	of	of	ADP
cana-803	209	9	bar	bar	NOUN
cana-803	209	10	graphs	graph	NOUN
cana-803	209	11	that	that	PRON
cana-803	209	12	show	show	VERB
cana-803	209	13	how	how	SCONJ
cana-803	209	14	well	well	ADV
cana-803	209	15	different	different	ADJ
cana-803	209	16	attack	attack	NOUN
cana-803	209	17	signature	signature	NOUN
cana-803	209	18	identification	identification	NOUN
cana-803	209	19	methods	method	NOUN
cana-803	209	20	work	work	VERB
cana-803	209	21	.	.	PUNCT
cana-803	210	1	these	these	PRON
cana-803	210	2	include	include	VERB
cana-803	210	3	signature	signature	NOUN
cana-803	210	4	-	-	PUNCT
cana-803	210	5	based	base	VERB
cana-803	210	6	ids	id	NOUN
cana-803	210	7	,	,	PUNCT
cana-803	210	8	anomaly	anomaly	NOUN
cana-803	210	9	-	-	PUNCT
cana-803	210	10	based	base	VERB
cana-803	210	11	ids	id	NOUN
cana-803	210	12	,	,	PUNCT
cana-803	210	13	a	a	DET
cana-803	210	14	machine	machine	NOUN
cana-803	210	15	learning	learn	VERB
cana-803	210	16	approach	approach	NOUN
cana-803	210	17	,	,	PUNCT
cana-803	210	18	and	and	CCONJ
cana-803	210	19	the	the	DET
cana-803	210	20	suggested	suggest	VERB
cana-803	210	21	algorithm	algorithm	NOUN
cana-803	210	22	both	both	CCONJ
cana-803	210	23	before	before	ADP
cana-803	210	24	and	and	CCONJ
cana-803	210	25	after	after	SCONJ
cana-803	210	26	it	it	PRON
cana-803	210	27	was	be	AUX
cana-803	210	28	optimized	optimize	VERB
cana-803	210	29	.	.	PUNCT
cana-803	211	1	the	the	DET
cana-803	211	2	x	x	ADJ
cana-803	211	3	-	-	ADJ
cana-803	211	4	axis	axis	NOUN
cana-803	211	5	shows	show	VERB
cana-803	211	6	the	the	DET
cana-803	211	7	different	different	ADJ
cana-803	211	8	ways	way	NOUN
cana-803	211	9	,	,	PUNCT
cana-803	211	10	and	and	CCONJ
cana-803	211	11	the	the	DET
cana-803	211	12	y	y	NOUN
cana-803	211	13	-	-	PUNCT
cana-803	211	14	axis	axis	NOUN
cana-803	211	15	shows	show	VERB
cana-803	211	16	the	the	DET
cana-803	211	17	%	%	NOUN
cana-803	211	18	values	value	NOUN
cana-803	211	19	of	of	ADP
cana-803	211	20	each	each	DET
cana-803	211	21	measure	measure	NOUN
cana-803	211	22	.	.	PUNCT
cana-803	212	1	each	each	DET
cana-803	212	2	bar	bar	NOUN
cana-803	212	3	graph	graph	NOUN
cana-803	212	4	shows	show	VERB
cana-803	212	5	a	a	DET
cana-803	212	6	different	different	ADJ
cana-803	212	7	performance	performance	NOUN
cana-803	212	8	metric	metric	ADJ
cana-803	212	9	,	,	PUNCT
cana-803	212	10	such	such	ADJ
cana-803	212	11	as	as	ADP
cana-803	212	12	accuracy	accuracy	NOUN
cana-803	212	13	,	,	PUNCT
cana-803	212	14	precision	precision	NOUN
cana-803	212	15	,	,	PUNCT
cana-803	212	16	f1	f1	NOUN
cana-803	212	17	score	score	NOUN
cana-803	212	18	,	,	PUNCT
cana-803	212	19	and	and	CCONJ
cana-803	212	20	memory	memory	NOUN
cana-803	212	21	.	.	PUNCT
cana-803	213	1	the	the	DET
cana-803	213	2	bars	bar	NOUN
cana-803	213	3	on	on	ADP
cana-803	213	4	the	the	DET
cana-803	213	5	accuracy	accuracy	NOUN
cana-803	213	6	line	line	NOUN
cana-803	213	7	show	show	VERB
cana-803	213	8	what	what	DET
cana-803	213	9	percentage	percentage	NOUN
cana-803	213	10	of	of	ADP
cana-803	213	11	the	the	DET
cana-803	213	12	time	time	NOUN
cana-803	213	13	each	each	DET
cana-803	213	14	method	method	NOUN
cana-803	213	15	was	be	AUX
cana-803	213	16	right	right	ADJ
cana-803	213	17	.	.	PUNCT
cana-803	214	1	there	there	PRON
cana-803	214	2	is	be	VERB
cana-803	214	3	no	no	DET
cana-803	214	4	doubt	doubt	NOUN
cana-803	214	5	that	that	SCONJ
cana-803	214	6	the	the	DET
cana-803	214	7	suggested	suggest	VERB
cana-803	214	8	method	method	NOUN
cana-803	214	9	is	be	AUX
cana-803	214	10	the	the	DET
cana-803	214	11	best	good	ADJ
cana-803	214	12	at	at	ADP
cana-803	214	13	finding	find	VERB
cana-803	214	14	attack	attack	NOUN
cana-803	214	15	patterns	pattern	NOUN
cana-803	214	16	in	in	ADP
cana-803	214	17	network	network	NOUN
cana-803	214	18	data	datum	NOUN
cana-803	214	19	.	.	PUNCT
cana-803	215	1	it	it	PRON
cana-803	215	2	has	have	VERB
cana-803	215	3	the	the	DET
cana-803	215	4	highest	high	ADJ
cana-803	215	5	accuracy	accuracy	NOUN
cana-803	215	6	numbers	number	NOUN
cana-803	215	7	both	both	CCONJ
cana-803	215	8	before	before	ADP
cana-803	215	9	and	and	CCONJ
cana-803	215	10	after	after	ADP
cana-803	215	11	improvement	improvement	NOUN
cana-803	215	12	.	.	PUNCT
cana-803	216	1	similarly	similarly	ADV
cana-803	216	2	,	,	PUNCT
cana-803	216	3	the	the	DET
cana-803	216	4	bars	bar	NOUN
cana-803	216	5	in	in	ADP
cana-803	216	6	the	the	DET
cana-803	216	7	precision	precision	NOUN
cana-803	216	8	graph	graph	NOUN
cana-803	216	9	show	show	VERB
cana-803	216	10	the	the	DET
cana-803	216	11	precision	precision	NOUN
cana-803	216	12	percentages	percentage	NOUN
cana-803	216	13	,	,	PUNCT
cana-803	216	14	which	which	PRON
cana-803	216	15	show	show	VERB
cana-803	216	16	how	how	SCONJ
cana-803	216	17	well	well	ADV
cana-803	216	18	each	each	DET
cana-803	216	19	method	method	NOUN
cana-803	216	20	can	can	AUX
cana-803	216	21	correctly	correctly	ADV
cana-803	216	22	label	label	VERB
cana-803	216	23	risks	risk	NOUN
cana-803	216	24	that	that	PRON
cana-803	216	25	have	have	AUX
cana-803	216	26	been	be	AUX
cana-803	216	27	found	find	VERB
cana-803	216	28	.	.	PUNCT
cana-803	217	1	figure	figure	VERB
cana-803	217	2	6	6	NUM
cana-803	217	3	:	:	PUNCT
cana-803	217	4	performance	performance	NOUN
cana-803	217	5	metric	metric	NOUN
cana-803	217	6	of	of	ADP
cana-803	217	7	proposed	propose	VERB
cana-803	217	8	algorithm	algorithm	NOUN
cana-803	217	9	before	before	ADP
cana-803	217	10	and	and	CCONJ
cana-803	217	11	after	after	ADP
cana-803	217	12	optimization	optimization	NOUN
cana-803	217	13	the	the	DET
cana-803	217	14	suggested	suggest	VERB
cana-803	217	15	algorithm	algorithm	NOUN
cana-803	217	16	has	have	VERB
cana-803	217	17	higher	high	ADJ
cana-803	217	18	accuracy	accuracy	NOUN
cana-803	217	19	values	value	NOUN
cana-803	217	20	than	than	ADP
cana-803	217	21	other	other	ADJ
cana-803	217	22	methods	method	NOUN
cana-803	217	23	,	,	PUNCT
cana-803	217	24	especially	especially	ADV
cana-803	217	25	after	after	ADP
cana-803	217	26	improvement	improvement	NOUN
cana-803	217	27	,	,	PUNCT
cana-803	217	28	which	which	PRON
cana-803	217	29	suggests	suggest	VERB
cana-803	217	30	that	that	SCONJ
cana-803	217	31	it	it	PRON
cana-803	217	32	can	can	AUX
cana-803	217	33	reduce	reduce	VERB
cana-803	217	34	the	the	DET
cana-803	217	35	number	number	NOUN
cana-803	217	36	of	of	ADP
cana-803	217	37	false	false	ADJ
cana-803	217	38	positives	positive	NOUN
cana-803	217	39	.	.	PUNCT
cana-803	218	1	the	the	DET
cana-803	218	2	f1	f1	PROPN
cana-803	218	3	score	score	NOUN
cana-803	218	4	line	line	NOUN
cana-803	218	5	shows	show	VERB
cana-803	218	6	the	the	DET
cana-803	218	7	harmonic	harmonic	ADJ
cana-803	218	8	mean	mean	NOUN
cana-803	218	9	of	of	ADP
cana-803	218	10	accuracy	accuracy	NOUN
cana-803	218	11	and	and	CCONJ
cana-803	218	12	recall	recall	NOUN
cana-803	218	13	,	,	PUNCT
cana-803	218	14	which	which	PRON
cana-803	218	15	gives	give	VERB
cana-803	218	16	an	an	DET
cana-803	218	17	accurate	accurate	ADJ
cana-803	218	18	picture	picture	NOUN
cana-803	218	19	of	of	ADP
cana-803	218	20	how	how	SCONJ
cana-803	218	21	well	well	ADV
cana-803	218	22	each	each	DET
cana-803	218	23	method	method	NOUN
cana-803	218	24	finds	find	VERB
cana-803	218	25	both	both	DET
cana-803	218	26	true	true	ADJ
cana-803	218	27	positives	positive	NOUN
cana-803	218	28	and	and	CCONJ
cana-803	218	29	fake	fake	ADJ
cana-803	218	30	negatives	negative	NOUN
cana-803	218	31	.	.	PUNCT
cana-803	219	1	once	once	ADV
cana-803	219	2	more	more	ADV
cana-803	219	3	,	,	PUNCT
cana-803	219	4	the	the	DET
cana-803	219	5	suggested	suggest	VERB
cana-803	219	6	algorithm	algorithm	NOUN
cana-803	219	7	has	have	VERB
cana-803	219	8	the	the	DET
cana-803	219	9	best	good	ADJ
cana-803	219	10	f1	f1	NOUN
cana-803	219	11	score	score	NOUN
cana-803	219	12	,	,	PUNCT
cana-803	219	13	which	which	PRON
cana-803	219	14	shows	show	VERB
cana-803	219	15	that	that	SCONJ
cana-803	219	16	it	it	PRON
cana-803	219	17	can	can	AUX
cana-803	219	18	find	find	VERB
cana-803	219	19	a	a	DET
cana-803	219	20	good	good	ADJ
cana-803	219	21	mix	mix	NOUN
cana-803	219	22	between	between	ADP
cana-803	219	23	accuracy	accuracy	NOUN
cana-803	219	24	and	and	CCONJ
cana-803	219	25	memory	memory	NOUN
cana-803	219	26	.	.	PUNCT
cana-803	220	1	lastly	lastly	ADV
cana-803	220	2	,	,	PUNCT
cana-803	220	3	the	the	DET
cana-803	220	4	memory	memory	NOUN
cana-803	220	5	line	line	NOUN
cana-803	220	6	shows	show	VERB
cana-803	220	7	how	how	SCONJ
cana-803	220	8	well	well	ADV
cana-803	220	9	each	each	DET
cana-803	220	10	method	method	NOUN
cana-803	220	11	can	can	AUX
cana-803	220	12	find	find	VERB
cana-803	220	13	real	real	ADJ
cana-803	220	14	threats	threat	NOUN
cana-803	220	15	.	.	PUNCT
cana-803	221	1	there	there	PRON
cana-803	221	2	are	be	VERB
cana-803	221	3	the	the	DET
cana-803	221	4	best	good	ADJ
cana-803	221	5	recall	recall	NOUN
cana-803	221	6	numbers	number	NOUN
cana-803	221	7	for	for	ADP
cana-803	221	8	the	the	DET
cana-803	221	9	suggested	suggest	VERB
cana-803	221	10	method	method	NOUN
cana-803	221	11	,	,	PUNCT
cana-803	221	12	which	which	PRON
cana-803	221	13	means	mean	VERB
cana-803	221	14	it	it	PRON
cana-803	221	15	is	be	AUX
cana-803	221	16	good	good	ADJ
cana-803	221	17	at	at	ADP
cana-803	221	18	finding	find	VERB
cana-803	221	19	a	a	DET
cana-803	221	20	lot	lot	NOUN
cana-803	221	21	of	of	ADP
cana-803	221	22	real	real	ADJ
cana-803	221	23	threats	threat	NOUN
cana-803	221	24	.	.	PUNCT
cana-803	222	1	one	one	NUM
cana-803	222	2	way	way	NOUN
cana-803	222	3	to	to	PART
cana-803	222	4	see	see	VERB
cana-803	222	5	how	how	SCONJ
cana-803	222	6	well	well	ADV
cana-803	222	7	the	the	DET
cana-803	222	8	optimization	optimization	NOUN
cana-803	222	9	process	process	NOUN
cana-803	222	10	improved	improve	VERB
cana-803	222	11	the	the	DET
cana-803	222	12	suggested	suggest	VERB
cana-803	222	13	algorithm	algorithm	NOUN
cana-803	222	14	's	's	PART
cana-803	222	15	ability	ability	NOUN
cana-803	222	16	to	to	PART
cana-803	222	17	find	find	VERB
cana-803	222	18	and	and	CCONJ
cana-803	222	19	stop	stop	VERB
cana-803	222	20	cyberattacks	cyberattack	NOUN
cana-803	222	21	is	be	AUX
cana-803	222	22	to	to	PART
cana-803	222	23	look	look	VERB
cana-803	222	24	at	at	ADP
cana-803	222	25	the	the	DET
cana-803	222	26	bar	bar	NOUN
cana-803	222	27	graph	graph	NOUN
cana-803	222	28	in	in	ADP
cana-803	222	29	figure	figure	NOUN
cana-803	222	30	(	(	PUNCT
cana-803	222	31	6	6	NUM
cana-803	222	32	)	)	PUNCT
cana-803	222	33	,	,	PUNCT
cana-803	222	34	which	which	PRON
cana-803	222	35	shows	show	VERB
cana-803	222	36	the	the	DET
cana-803	222	37	performance	performance	NOUN
cana-803	222	38	measures	measure	NOUN
cana-803	222	39	of	of	ADP
cana-803	222	40	the	the	DET
cana-803	222	41	algorithm	algorithm	NOUN
cana-803	222	42	before	before	ADP
cana-803	222	43	and	and	CCONJ
cana-803	222	44	after	after	ADP
cana-803	222	45	optimization	optimization	NOUN
cana-803	222	46	.	.	PUNCT
cana-803	223	1	there	there	PRON
cana-803	223	2	are	be	VERB
cana-803	223	3	two	two	NUM
cana-803	223	4	sets	set	NOUN
cana-803	223	5	of	of	ADP
cana-803	223	6	bars	bar	NOUN
cana-803	223	7	on	on	ADP
cana-803	223	8	the	the	DET
cana-803	223	9	graph	graph	NOUN
cana-803	223	10	that	that	PRON
cana-803	223	11	show	show	VERB
cana-803	223	12	how	how	SCONJ
cana-803	223	13	well	well	ADV
cana-803	223	14	the	the	DET
cana-803	223	15	algorithm	algorithm	NOUN
cana-803	223	16	worked	work	VERB
cana-803	223	17	before	before	ADV
cana-803	223	18	and	and	CCONJ
cana-803	223	19	after	after	SCONJ
cana-803	223	20	it	it	PRON
cana-803	223	21	was	be	AUX
cana-803	223	22	optimized	optimize	VERB
cana-803	223	23	.	.	PUNCT
cana-803	224	1	each	each	DET
cana-803	224	2	set	set	NOUN
cana-803	224	3	of	of	ADP
cana-803	224	4	bars	bar	NOUN
cana-803	224	5	shows	show	VERB
cana-803	224	6	a	a	DET
cana-803	224	7	different	different	ADJ
cana-803	224	8	performance	performance	NOUN
cana-803	224	9	measure	measure	NOUN
cana-803	224	10	,	,	PUNCT
cana-803	224	11	such	such	ADJ
cana-803	224	12	as	as	ADP
cana-803	224	13	accuracy	accuracy	NOUN
cana-803	224	14	,	,	PUNCT
cana-803	224	15	precision	precision	NOUN
cana-803	224	16	,	,	PUNCT
cana-803	224	17	f1	f1	NOUN
cana-803	224	18	score	score	NOUN
cana-803	224	19	,	,	PUNCT
cana-803	224	20	and	and	CCONJ
cana-803	224	21	recall	recall	NOUN
cana-803	224	22	.	.	PUNCT
cana-803	225	1	before	before	SCONJ
cana-803	225	2	it	it	PRON
cana-803	225	3	is	be	AUX
cana-803	225	4	optimized	optimize	VERB
cana-803	225	5	,	,	PUNCT
cana-803	225	6	the	the	DET
cana-803	225	7	suggested	suggest	VERB
cana-803	225	8	algorithm	algorithm	NOUN
cana-803	225	9	does	do	VERB
cana-803	225	10	a	a	DET
cana-803	225	11	good	good	ADJ
cana-803	225	12	job	job	NOUN
cana-803	225	13	by	by	ADP
cana-803	225	14	all	all	DET
cana-803	225	15	measures	measure	NOUN
cana-803	225	16	.	.	PUNCT
cana-803	226	1	its	its	PRON
cana-803	226	2	accuracy	accuracy	NOUN
cana-803	226	3	,	,	PUNCT
cana-803	226	4	precision	precision	NOUN
cana-803	226	5	,	,	PUNCT
cana-803	226	6	f1	f1	NOUN
cana-803	226	7	score	score	NOUN
cana-803	226	8	,	,	PUNCT
cana-803	226	9	and	and	CCONJ
cana-803	226	10	recall	recall	NOUN
cana-803	226	11	are	be	AUX
cana-803	226	12	all	all	ADV
cana-803	226	13	around	around	ADP
cana-803	226	14	92	92	NUM
cana-803	226	15	%	%	NOUN
cana-803	226	16	,	,	PUNCT
cana-803	226	17	90	90	NUM
cana-803	226	18	%	%	NOUN
cana-803	226	19	,	,	PUNCT
cana-803	226	20	93	93	NUM
cana-803	226	21	%	%	NOUN
cana-803	226	22	,	,	PUNCT
cana-803	226	23	and	and	CCONJ
cana-803	226	24	91	91	NUM
cana-803	226	25	%	%	NOUN
cana-803	226	26	,	,	PUNCT
cana-803	226	27	respectively	respectively	ADV
cana-803	226	28	.	.	PUNCT
cana-803	227	1	according	accord	VERB
cana-803	227	2	to	to	ADP
cana-803	227	3	communications	communication	NOUN
cana-803	227	4	on	on	ADP
cana-803	227	5	applied	apply	VERB
cana-803	227	6	nonlinear	nonlinear	ADJ
cana-803	227	7	analysis	analysis	NOUN
cana-803	227	8	issn	issn	NOUN
cana-803	227	9	:	:	PUNCT
cana-803	227	10	1074	1074	NUM
cana-803	227	11	-	-	PUNCT
cana-803	227	12	133x	133x	NUM
cana-803	227	13	vol	vol	NOUN
cana-803	227	14	31	31	NUM
cana-803	227	15	no	no	NOUN
cana-803	227	16	.	.	PUNCT
cana-803	228	1	3s	3s	NUM
cana-803	228	2	(	(	PUNCT
cana-803	228	3	2024	2024	NUM
cana-803	228	4	)	)	PUNCT
cana-803	228	5	500	500	NUM
cana-803	228	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-803	228	7	these	these	DET
cana-803	228	8	early	early	ADJ
cana-803	228	9	performance	performance	NOUN
cana-803	228	10	measures	measure	NOUN
cana-803	228	11	,	,	PUNCT
cana-803	228	12	the	the	DET
cana-803	228	13	program	program	NOUN
cana-803	228	14	can	can	AUX
cana-803	228	15	successfully	successfully	ADV
cana-803	228	16	find	find	VERB
cana-803	228	17	and	and	CCONJ
cana-803	228	18	deal	deal	VERB
cana-803	228	19	with	with	ADP
cana-803	228	20	hacking	hack	VERB
cana-803	228	21	risks	risk	NOUN
cana-803	228	22	in	in	ADP
cana-803	228	23	network	network	NOUN
cana-803	228	24	traffic	traffic	NOUN
cana-803	228	25	.	.	PUNCT
cana-803	229	1	after	after	ADP
cana-803	229	2	optimization	optimization	NOUN
cana-803	229	3	,	,	PUNCT
cana-803	229	4	big	big	ADJ
cana-803	229	5	gains	gain	NOUN
cana-803	229	6	are	be	AUX
cana-803	229	7	seen	see	VERB
cana-803	229	8	in	in	ADP
cana-803	229	9	all	all	DET
cana-803	229	10	speed	speed	NOUN
cana-803	229	11	measures	measure	NOUN
cana-803	229	12	,	,	PUNCT
cana-803	229	13	as	as	SCONJ
cana-803	229	14	shown	show	VERB
cana-803	229	15	by	by	ADP
cana-803	229	16	the	the	DET
cana-803	229	17	bars	bar	NOUN
cana-803	229	18	with	with	ADP
cana-803	229	19	higher	high	ADJ
cana-803	229	20	numbers	number	NOUN
cana-803	229	21	that	that	PRON
cana-803	229	22	show	show	VERB
cana-803	229	23	how	how	SCONJ
cana-803	229	24	well	well	ADV
cana-803	229	25	the	the	DET
cana-803	229	26	program	program	NOUN
cana-803	229	27	worked	work	VERB
cana-803	229	28	after	after	ADP
cana-803	229	29	optimization	optimization	NOUN
cana-803	229	30	.	.	PUNCT
cana-803	230	1	the	the	DET
cana-803	230	2	bar	bar	NOUN
cana-803	230	3	for	for	ADP
cana-803	230	4	accuracy	accuracy	NOUN
cana-803	230	5	goes	go	VERB
cana-803	230	6	up	up	ADP
cana-803	230	7	to	to	PART
cana-803	230	8	95	95	NUM
cana-803	230	9	%	%	NOUN
cana-803	230	10	,	,	PUNCT
cana-803	230	11	which	which	PRON
cana-803	230	12	shows	show	VERB
cana-803	230	13	that	that	SCONJ
cana-803	230	14	the	the	DET
cana-803	230	15	program	program	NOUN
cana-803	230	16	is	be	AUX
cana-803	230	17	much	much	ADV
cana-803	230	18	better	well	ADJ
cana-803	230	19	at	at	ADP
cana-803	230	20	telling	tell	VERB
cana-803	230	21	the	the	DET
cana-803	230	22	difference	difference	NOUN
cana-803	230	23	between	between	ADP
cana-803	230	24	good	good	ADJ
cana-803	230	25	and	and	CCONJ
cana-803	230	26	bad	bad	ADJ
cana-803	230	27	network	network	NOUN
cana-803	230	28	data	datum	NOUN
cana-803	230	29	.	.	PUNCT
cana-803	231	1	in	in	ADP
cana-803	231	2	the	the	DET
cana-803	231	3	same	same	ADJ
cana-803	231	4	way	way	NOUN
cana-803	231	5	,	,	PUNCT
cana-803	231	6	the	the	DET
cana-803	231	7	bars	bar	NOUN
cana-803	231	8	for	for	ADP
cana-803	231	9	precision	precision	NOUN
cana-803	231	10	,	,	PUNCT
cana-803	231	11	f1	f1	NOUN
cana-803	231	12	score	score	NOUN
cana-803	231	13	,	,	PUNCT
cana-803	231	14	and	and	CCONJ
cana-803	231	15	memory	memory	NOUN
cana-803	231	16	all	all	PRON
cana-803	231	17	show	show	VERB
cana-803	231	18	big	big	ADJ
cana-803	231	19	jumps	jump	NOUN
cana-803	231	20	,	,	PUNCT
cana-803	231	21	with	with	ADP
cana-803	231	22	values	value	NOUN
cana-803	231	23	hitting	hit	VERB
cana-803	231	24	92	92	NUM
cana-803	231	25	%	%	NOUN
cana-803	231	26	,	,	PUNCT
cana-803	231	27	96	96	NUM
cana-803	231	28	%	%	NOUN
cana-803	231	29	,	,	PUNCT
cana-803	231	30	and	and	CCONJ
cana-803	231	31	94	94	NUM
cana-803	231	32	%	%	NOUN
cana-803	231	33	,	,	PUNCT
cana-803	231	34	respectively	respectively	ADV
cana-803	231	35	.	.	PUNCT
cana-803	232	1	the	the	DET
cana-803	232	2	comparison	comparison	NOUN
cana-803	232	3	provided	provide	VERB
cana-803	232	4	by	by	ADP
cana-803	232	5	the	the	DET
cana-803	232	6	bar	bar	NOUN
cana-803	232	7	graph	graph	NOUN
cana-803	232	8	shows	show	VERB
cana-803	232	9	how	how	SCONJ
cana-803	232	10	well	well	ADV
cana-803	232	11	the	the	DET
cana-803	232	12	optimization	optimization	NOUN
cana-803	232	13	process	process	NOUN
cana-803	232	14	worked	work	VERB
cana-803	232	15	to	to	ADP
cana-803	232	16	fine	fine	ADJ
cana-803	232	17	-	-	PUNCT
cana-803	232	18	tune	tune	NOUN
cana-803	232	19	the	the	DET
cana-803	232	20	suggested	suggest	VERB
cana-803	232	21	algorithm	algorithm	NOUN
cana-803	232	22	,	,	PUNCT
cana-803	232	23	which	which	PRON
cana-803	232	24	led	lead	VERB
cana-803	232	25	to	to	ADP
cana-803	232	26	real	real	ADJ
cana-803	232	27	improvements	improvement	NOUN
cana-803	232	28	in	in	ADP
cana-803	232	29	its	its	PRON
cana-803	232	30	performance	performance	NOUN
cana-803	232	31	across	across	ADP
cana-803	232	32	a	a	DET
cana-803	232	33	number	number	NOUN
cana-803	232	34	of	of	ADP
cana-803	232	35	areas	area	NOUN
cana-803	232	36	.	.	PUNCT
cana-803	233	1	the	the	DET
cana-803	233	2	clear	clear	ADJ
cana-803	233	3	difference	difference	NOUN
cana-803	233	4	between	between	ADP
cana-803	233	5	the	the	DET
cana-803	233	6	bars	bar	NOUN
cana-803	233	7	showing	show	VERB
cana-803	233	8	how	how	SCONJ
cana-803	233	9	well	well	ADV
cana-803	233	10	the	the	DET
cana-803	233	11	algorithm	algorithm	NOUN
cana-803	233	12	worked	work	VERB
cana-803	233	13	before	before	ADV
cana-803	233	14	and	and	CCONJ
cana-803	233	15	after	after	ADP
cana-803	233	16	optimization	optimization	NOUN
cana-803	233	17	shows	show	VERB
cana-803	233	18	how	how	SCONJ
cana-803	233	19	important	important	ADJ
cana-803	233	20	optimization	optimization	NOUN
cana-803	233	21	methods	method	NOUN
cana-803	233	22	are	be	AUX
cana-803	233	23	for	for	ADP
cana-803	233	24	making	make	VERB
cana-803	233	25	the	the	DET
cana-803	233	26	algorithm	algorithm	NOUN
cana-803	233	27	better	well	ADV
cana-803	233	28	at	at	ADP
cana-803	233	29	finding	find	VERB
cana-803	233	30	and	and	CCONJ
cana-803	233	31	responding	respond	VERB
cana-803	233	32	to	to	ADP
cana-803	233	33	cyber	cyber	NOUN
cana-803	233	34	attacks	attack	NOUN
cana-803	233	35	.	.	PUNCT
cana-803	234	1	5.conclusion	5.conclusion	NUM
cana-803	234	2	with	with	ADP
cana-803	234	3	using	use	VERB
cana-803	234	4	random	random	ADJ
cana-803	234	5	models	model	NOUN
cana-803	234	6	could	could	AUX
cana-803	234	7	be	be	AUX
cana-803	234	8	a	a	DET
cana-803	234	9	good	good	ADJ
cana-803	234	10	way	way	NOUN
cana-803	234	11	to	to	PART
cana-803	234	12	make	make	VERB
cana-803	234	13	intrusion	intrusion	NOUN
cana-803	234	14	detection	detection	NOUN
cana-803	234	15	systems	system	NOUN
cana-803	234	16	(	(	PUNCT
cana-803	234	17	ids	id	NOUN
cana-803	234	18	)	)	PUNCT
cana-803	234	19	better	well	ADV
cana-803	234	20	at	at	ADP
cana-803	234	21	finding	find	VERB
cana-803	234	22	and	and	CCONJ
cana-803	234	23	responding	respond	VERB
cana-803	234	24	to	to	ADP
cana-803	234	25	cyberattacks	cyberattack	NOUN
cana-803	234	26	.	.	PUNCT
cana-803	235	1	as	as	ADP
cana-803	235	2	part	part	NOUN
cana-803	235	3	of	of	ADP
cana-803	235	4	this	this	DET
cana-803	235	5	study	study	NOUN
cana-803	235	6	,	,	PUNCT
cana-803	235	7	we	we	PRON
cana-803	235	8	looked	look	VERB
cana-803	235	9	into	into	ADP
cana-803	235	10	how	how	SCONJ
cana-803	235	11	well	well	ADV
cana-803	235	12	using	use	VERB
cana-803	235	13	mathematical	mathematical	ADJ
cana-803	235	14	methods	method	NOUN
cana-803	235	15	based	base	VERB
cana-803	235	16	on	on	ADP
cana-803	235	17	probability	probability	NOUN
cana-803	235	18	theory	theory	NOUN
cana-803	235	19	,	,	PUNCT
cana-803	235	20	queuing	queue	VERB
cana-803	235	21	theory	theory	NOUN
cana-803	235	22	,	,	PUNCT
cana-803	235	23	and	and	CCONJ
cana-803	235	24	stochastic	stochastic	ADJ
cana-803	235	25	optimization	optimization	NOUN
cana-803	235	26	can	can	AUX
cana-803	235	27	improve	improve	VERB
cana-803	235	28	ids	id	NOUN
cana-803	235	29	's	's	PART
cana-803	235	30	ability	ability	NOUN
cana-803	235	31	to	to	PART
cana-803	235	32	protect	protect	VERB
cana-803	235	33	digital	digital	ADJ
cana-803	235	34	systems	system	NOUN
cana-803	235	35	from	from	ADP
cana-803	235	36	new	new	ADJ
cana-803	235	37	cyber	cyber	NOUN
cana-803	235	38	dangers	danger	NOUN
cana-803	235	39	.	.	PUNCT
cana-803	236	1	it	it	PRON
cana-803	236	2	is	be	AUX
cana-803	236	3	possible	possible	ADJ
cana-803	236	4	to	to	PART
cana-803	236	5	use	use	VERB
cana-803	236	6	stochastic	stochastic	ADJ
cana-803	236	7	models	model	NOUN
cana-803	236	8	to	to	PART
cana-803	236	9	make	make	VERB
cana-803	236	10	monitoring	monitoring	NOUN
cana-803	236	11	systems	system	NOUN
cana-803	236	12	that	that	PRON
cana-803	236	13	are	be	AUX
cana-803	236	14	more	more	ADV
cana-803	236	15	reliable	reliable	ADJ
cana-803	236	16	and	and	CCONJ
cana-803	236	17	flexible	flexible	ADJ
cana-803	236	18	by	by	ADP
cana-803	236	19	taking	take	VERB
cana-803	236	20	into	into	ADP
cana-803	236	21	account	account	NOUN
cana-803	236	22	the	the	DET
cana-803	236	23	uncertainty	uncertainty	NOUN
cana-803	236	24	and	and	CCONJ
cana-803	236	25	variability	variability	NOUN
cana-803	236	26	that	that	PRON
cana-803	236	27	are	be	AUX
cana-803	236	28	naturally	naturally	ADV
cana-803	236	29	present	present	ADJ
cana-803	236	30	in	in	ADP
cana-803	236	31	network	network	NOUN
cana-803	236	32	traffic	traffic	NOUN
cana-803	236	33	data	datum	NOUN
cana-803	236	34	.	.	PUNCT
cana-803	237	1	we	we	PRON
cana-803	237	2	learn	learn	VERB
cana-803	237	3	a	a	DET
cana-803	237	4	lot	lot	NOUN
cana-803	237	5	about	about	ADP
cana-803	237	6	how	how	SCONJ
cana-803	237	7	cyberattacks	cyberattack	NOUN
cana-803	237	8	work	work	NOUN
cana-803	237	9	and	and	CCONJ
cana-803	237	10	can	can	AUX
cana-803	237	11	spot	spot	VERB
cana-803	237	12	strange	strange	ADJ
cana-803	237	13	behavior	behavior	NOUN
cana-803	237	14	that	that	PRON
cana-803	237	15	points	point	VERB
cana-803	237	16	to	to	ADP
cana-803	237	17	bad	bad	ADJ
cana-803	237	18	behavior	behavior	NOUN
cana-803	237	19	by	by	ADP
cana-803	237	20	thinking	think	VERB
cana-803	237	21	about	about	ADP
cana-803	237	22	network	network	NOUN
cana-803	237	23	behavior	behavior	NOUN
cana-803	237	24	as	as	ADP
cana-803	237	25	random	random	ADJ
cana-803	237	26	processes	process	NOUN
cana-803	237	27	and	and	CCONJ
cana-803	237	28	using	use	VERB
cana-803	237	29	queue	queue	NOUN
cana-803	237	30	theory	theory	NOUN
cana-803	237	31	to	to	PART
cana-803	237	32	look	look	VERB
cana-803	237	33	at	at	ADP
cana-803	237	34	traffic	traffic	NOUN
cana-803	237	35	patterns	pattern	NOUN
cana-803	237	36	.	.	PUNCT
cana-803	238	1	using	use	VERB
cana-803	238	2	random	random	ADJ
cana-803	238	3	optimization	optimization	NOUN
cana-803	238	4	methods	method	NOUN
cana-803	238	5	also	also	ADV
cana-803	238	6	lets	let	VERB
cana-803	238	7	you	you	PRON
cana-803	238	8	change	change	VERB
cana-803	238	9	how	how	SCONJ
cana-803	238	10	resources	resource	NOUN
cana-803	238	11	are	be	AUX
cana-803	238	12	allocated	allocate	VERB
cana-803	238	13	and	and	CCONJ
cana-803	238	14	how	how	SCONJ
cana-803	238	15	responses	response	NOUN
cana-803	238	16	are	be	AUX
cana-803	238	17	prioritized	prioritize	VERB
cana-803	238	18	.	.	PUNCT
cana-803	239	1	this	this	PRON
cana-803	239	2	makes	make	VERB
cana-803	239	3	the	the	DET
cana-803	239	4	best	good	ADJ
cana-803	239	5	use	use	NOUN
cana-803	239	6	of	of	ADP
cana-803	239	7	defenses	defense	NOUN
cana-803	239	8	and	and	CCONJ
cana-803	239	9	lessens	lessen	VERB
cana-803	239	10	the	the	DET
cana-803	239	11	effect	effect	NOUN
cana-803	239	12	cyberattacks	cyberattack	NOUN
cana-803	239	13	have	have	VERB
cana-803	239	14	on	on	ADP
cana-803	239	15	network	network	NOUN
cana-803	239	16	performance	performance	NOUN
cana-803	239	17	.	.	PUNCT
cana-803	240	1	our	our	PRON
cana-803	240	2	research	research	NOUN
cana-803	240	3	has	have	AUX
cana-803	240	4	shown	show	VERB
cana-803	240	5	that	that	SCONJ
cana-803	240	6	ids	id	NOUN
cana-803	240	7	's	's	PART
cana-803	240	8	performance	performance	NOUN
cana-803	240	9	measures	measure	NOUN
cana-803	240	10	have	have	AUX
cana-803	240	11	improved	improve	VERB
cana-803	240	12	significantly	significantly	ADV
cana-803	240	13	,	,	PUNCT
cana-803	240	14	especially	especially	ADV
cana-803	240	15	since	since	SCONJ
cana-803	240	16	random	random	ADJ
cana-803	240	17	models	model	NOUN
cana-803	240	18	were	be	AUX
cana-803	240	19	added	add	VERB
cana-803	240	20	.	.	PUNCT
cana-803	241	1	compared	compare	VERB
cana-803	241	2	to	to	ADP
cana-803	241	3	signature	signature	NOUN
cana-803	241	4	-	-	PUNCT
cana-803	241	5	based	base	VERB
cana-803	241	6	and	and	CCONJ
cana-803	241	7	anomaly	anomaly	NOUN
cana-803	241	8	-	-	PUNCT
cana-803	241	9	based	base	VERB
cana-803	241	10	ids	id	NOUN
cana-803	241	11	,	,	PUNCT
cana-803	241	12	the	the	DET
cana-803	241	13	suggested	suggest	VERB
cana-803	241	14	statistical	statistical	ADJ
cana-803	241	15	method	method	NOUN
cana-803	241	16	has	have	AUX
cana-803	241	17	shown	show	VERB
cana-803	241	18	to	to	PART
cana-803	241	19	be	be	AUX
cana-803	241	20	more	more	ADV
cana-803	241	21	accurate	accurate	ADJ
cana-803	241	22	,	,	PUNCT
cana-803	241	23	precise	precise	ADJ
cana-803	241	24	,	,	PUNCT
cana-803	241	25	recallable	recallable	ADJ
cana-803	241	26	,	,	PUNCT
cana-803	241	27	and	and	CCONJ
cana-803	241	28	have	have	VERB
cana-803	241	29	a	a	DET
cana-803	241	30	higher	high	ADJ
cana-803	241	31	f1	f1	NOUN
cana-803	241	32	score	score	NOUN
cana-803	241	33	.	.	PUNCT
cana-803	242	1	we	we	PRON
cana-803	242	2	have	have	AUX
cana-803	242	3	gotten	get	VERB
cana-803	242	4	a	a	DET
cana-803	242	5	lot	lot	NOUN
cana-803	242	6	better	well	ADJ
cana-803	242	7	at	at	ADP
cana-803	242	8	finding	find	VERB
cana-803	242	9	known	know	VERB
cana-803	242	10	attack	attack	NOUN
cana-803	242	11	patterns	pattern	NOUN
cana-803	242	12	and	and	CCONJ
cana-803	242	13	risks	risk	NOUN
cana-803	242	14	we	we	PRON
cana-803	242	15	had	have	AUX
cana-803	242	16	n't	not	PART
cana-803	242	17	seen	see	VERB
cana-803	242	18	before	before	ADV
cana-803	242	19	in	in	ADP
cana-803	242	20	real	real	ADJ
cana-803	242	21	time	time	NOUN
cana-803	242	22	by	by	ADP
cana-803	242	23	using	use	VERB
cana-803	242	24	statistical	statistical	ADJ
cana-803	242	25	models	model	NOUN
cana-803	242	26	and	and	CCONJ
cana-803	242	27	dynamic	dynamic	ADJ
cana-803	242	28	optimization	optimization	NOUN
cana-803	242	29	techniques.the	techniques.the	PRON
cana-803	242	30	suggested	suggest	VERB
cana-803	242	31	approach	approach	NOUN
cana-803	242	32	is	be	AUX
cana-803	242	33	scalable	scalable	ADJ
cana-803	242	34	and	and	CCONJ
cana-803	242	35	flexible	flexible	ADJ
cana-803	242	36	,	,	PUNCT
cana-803	242	37	so	so	SCONJ
cana-803	242	38	it	it	PRON
cana-803	242	39	can	can	AUX
cana-803	242	40	be	be	AUX
cana-803	242	41	used	use	VERB
cana-803	242	42	in	in	ADP
cana-803	242	43	a	a	DET
cana-803	242	44	wide	wide	ADJ
cana-803	242	45	range	range	NOUN
cana-803	242	46	of	of	ADP
cana-803	242	47	network	network	NOUN
cana-803	242	48	settings	setting	NOUN
cana-803	242	49	and	and	CCONJ
cana-803	242	50	as	as	SCONJ
cana-803	242	51	threats	threat	NOUN
cana-803	242	52	change	change	VERB
cana-803	242	53	.	.	PUNCT
cana-803	243	1	because	because	SCONJ
cana-803	243	2	stochastic	stochastic	ADJ
cana-803	243	3	models	model	NOUN
cana-803	243	4	are	be	AUX
cana-803	243	5	flexible	flexible	ADJ
cana-803	243	6	,	,	PUNCT
cana-803	243	7	detection	detection	NOUN
cana-803	243	8	methods	method	NOUN
cana-803	243	9	can	can	AUX
cana-803	243	10	be	be	AUX
cana-803	243	11	improved	improve	VERB
cana-803	243	12	and	and	CCONJ
cana-803	243	13	fine	fine	ADV
cana-803	243	14	-	-	PUNCT
cana-803	243	15	tuned	tune	VERB
cana-803	243	16	all	all	DET
cana-803	243	17	the	the	DET
cana-803	243	18	time	time	NOUN
cana-803	243	19	.	.	PUNCT
cana-803	244	1	this	this	PRON
cana-803	244	2	makes	make	VERB
cana-803	244	3	sure	sure	ADJ
cana-803	244	4	that	that	SCONJ
cana-803	244	5	ids	id	NOUN
cana-803	244	6	are	be	AUX
cana-803	244	7	strong	strong	ADJ
cana-803	244	8	enough	enough	ADV
cana-803	244	9	to	to	PART
cana-803	244	10	handle	handle	VERB
cana-803	244	11	new	new	ADJ
cana-803	244	12	cyber	cyber	NOUN
cana-803	244	13	dangers	danger	NOUN
cana-803	244	14	.	.	PUNCT
cana-803	245	1	in	in	ADP
cana-803	245	2	the	the	DET
cana-803	245	3	future	future	NOUN
cana-803	245	4	,	,	PUNCT
cana-803	245	5	more	more	ADJ
cana-803	245	6	study	study	NOUN
cana-803	245	7	and	and	CCONJ
cana-803	245	8	development	development	NOUN
cana-803	245	9	in	in	ADP
cana-803	245	10	the	the	DET
cana-803	245	11	area	area	NOUN
cana-803	245	12	of	of	ADP
cana-803	245	13	random	random	ADJ
cana-803	245	14	models	model	NOUN
cana-803	245	15	for	for	ADP
cana-803	245	16	cyber	cyber	NOUN
cana-803	245	17	attack	attack	NOUN
cana-803	245	18	detection	detection	NOUN
cana-803	245	19	and	and	CCONJ
cana-803	245	20	reaction	reaction	NOUN
cana-803	245	21	could	could	AUX
cana-803	245	22	help	help	VERB
cana-803	245	23	a	a	DET
cana-803	245	24	lot	lot	NOUN
cana-803	245	25	with	with	ADP
cana-803	245	26	dealing	deal	VERB
cana-803	245	27	with	with	ADP
cana-803	245	28	cyber	cyber	NOUN
cana-803	245	29	threats	threat	NOUN
cana-803	245	30	as	as	SCONJ
cana-803	245	31	they	they	PRON
cana-803	245	32	change	change	VERB
cana-803	245	33	.	.	PUNCT
cana-803	246	1	more	more	ADV
cana-803	246	2	advanced	advanced	ADJ
cana-803	246	3	probabilistic	probabilistic	ADJ
cana-803	246	4	models	model	NOUN
cana-803	246	5	could	could	AUX
cana-803	246	6	be	be	AUX
cana-803	246	7	studied	study	VERB
cana-803	246	8	in	in	ADP
cana-803	246	9	the	the	DET
cana-803	246	10	future	future	NOUN
cana-803	246	11	,	,	PUNCT
cana-803	246	12	along	along	ADP
cana-803	246	13	with	with	ADP
cana-803	246	14	machine	machine	NOUN
cana-803	246	15	learning	learn	VERB
cana-803	246	16	techniques	technique	NOUN
cana-803	246	17	for	for	ADP
cana-803	246	18	pattern	pattern	NOUN
cana-803	246	19	recognition	recognition	NOUN
cana-803	246	20	and	and	CCONJ
cana-803	246	21	problem	problem	NOUN
cana-803	246	22	detection	detection	NOUN
cana-803	246	23	and	and	CCONJ
cana-803	246	24	better	well	ADJ
cana-803	246	25	integration	integration	NOUN
cana-803	246	26	of	of	ADP
cana-803	246	27	stochastic	stochastic	ADJ
cana-803	246	28	optimization	optimization	NOUN
cana-803	246	29	methods	method	NOUN
cana-803	246	30	for	for	ADP
cana-803	246	31	dynamic	dynamic	ADJ
cana-803	246	32	reaction	reaction	NOUN
cana-803	246	33	planning	planning	NOUN
cana-803	246	34	.	.	PUNCT
cana-803	247	1	basically	basically	ADV
cana-803	247	2	,	,	PUNCT
cana-803	247	3	using	use	VERB
cana-803	247	4	a	a	DET
cana-803	247	5	mathematical	mathematical	ADJ
cana-803	247	6	method	method	NOUN
cana-803	247	7	based	base	VERB
cana-803	247	8	on	on	ADP
cana-803	247	9	random	random	ADJ
cana-803	247	10	modeling	modeling	NOUN
cana-803	247	11	can	can	AUX
cana-803	247	12	help	help	VERB
cana-803	247	13	make	make	VERB
cana-803	247	14	intrusion	intrusion	NOUN
cana-803	247	15	detection	detection	NOUN
cana-803	247	16	systems	system	NOUN
cana-803	247	17	better	well	ADV
cana-803	247	18	at	at	ADP
cana-803	247	19	protecting	protect	VERB
cana-803	247	20	important	important	ADJ
cana-803	247	21	digital	digital	ADJ
cana-803	247	22	assets	asset	NOUN
cana-803	247	23	in	in	ADP
cana-803	247	24	a	a	DET
cana-803	247	25	comprehensive	comprehensive	ADJ
cana-803	247	26	and	and	CCONJ
cana-803	247	27	proactive	proactive	ADJ
cana-803	247	28	way	way	NOUN
cana-803	247	29	.	.	PUNCT
cana-803	248	1	we	we	PRON
cana-803	248	2	can	can	AUX
cana-803	248	3	help	help	VERB
cana-803	248	4	intrusion	intrusion	NOUN
cana-803	248	5	detection	detection	NOUN
cana-803	248	6	systems	system	NOUN
cana-803	248	7	(	(	PUNCT
cana-803	248	8	ids	id	NOUN
cana-803	248	9	)	)	PUNCT
cana-803	248	10	find	find	VERB
cana-803	248	11	,	,	PUNCT
cana-803	248	12	stop	stop	VERB
cana-803	248	13	,	,	PUNCT
cana-803	248	14	and	and	CCONJ
cana-803	248	15	react	react	VERB
cana-803	248	16	to	to	ADP
cana-803	248	17	cyber	cyber	PROPN
cana-803	248	18	threats	threat	NOUN
cana-803	248	19	more	more	ADV
cana-803	248	20	accurately	accurately	ADV
cana-803	248	21	,	,	PUNCT
cana-803	248	22	quickly	quickly	ADV
cana-803	248	23	,	,	PUNCT
cana-803	248	24	and	and	CCONJ
cana-803	248	25	reliably	reliably	ADV
cana-803	248	26	in	in	ADP
cana-803	248	27	a	a	DET
cana-803	248	28	threat	threat	NOUN
cana-803	248	29	world	world	NOUN
cana-803	248	30	that	that	PRON
cana-803	248	31	is	be	AUX
cana-803	248	32	always	always	ADV
cana-803	248	33	changing	change	VERB
cana-803	248	34	by	by	ADP
cana-803	248	35	accepting	accept	VERB
cana-803	248	36	that	that	DET
cana-803	248	37	network	network	NOUN
cana-803	248	38	traffic	traffic	NOUN
cana-803	248	39	data	datum	NOUN
cana-803	248	40	is	be	AUX
cana-803	248	41	unclear	unclear	ADJ
cana-803	248	42	and	and	CCONJ
cana-803	248	43	can	can	AUX
cana-803	248	44	change	change	VERB
cana-803	248	45	.	.	PUNCT
cana-803	249	1	communications	communication	NOUN
cana-803	249	2	on	on	ADP
cana-803	249	3	applied	apply	VERB
cana-803	249	4	nonlinear	nonlinear	ADJ
cana-803	249	5	analysis	analysis	NOUN
cana-803	249	6	issn	issn	NOUN
cana-803	249	7	:	:	PUNCT
cana-803	249	8	1074	1074	NUM
cana-803	249	9	-	-	PUNCT
cana-803	249	10	133x	133x	NUM
cana-803	249	11	vol	vol	NOUN
cana-803	249	12	31	31	NUM
cana-803	249	13	no	no	NOUN
cana-803	249	14	.	.	PUNCT
cana-803	250	1	3s	3s	NUM
cana-803	250	2	(	(	PUNCT
cana-803	250	3	2024	2024	NUM
cana-803	250	4	)	)	PUNCT
cana-803	250	5	501	501	NUM
cana-803	250	6	https://internationalpubls.com	https://internationalpubls.com	NUM
cana-803	250	7	references	reference	NOUN
cana-803	250	8	[	[	X
cana-803	250	9	1	1	NUM
cana-803	250	10	]	]	PUNCT
cana-803	250	11	a.	a.	NOUN
cana-803	250	12	yulianto	yulianto	NOUN
cana-803	250	13	,	,	PUNCT
cana-803	250	14	p.	p.	PROPN
cana-803	250	15	sukarno	sukarno	PROPN
cana-803	250	16	and	and	CCONJ
cana-803	250	17	n.	n.	PROPN
cana-803	250	18	a.	a.	NOUN
cana-803	250	19	suwastika	suwastika	PROPN
cana-803	250	20	,	,	PUNCT
cana-803	250	21	"	"	PUNCT
cana-803	250	22	improving	improve	VERB
cana-803	250	23	adaboost	adaboost	ADV
cana-803	250	24	-	-	PUNCT
cana-803	250	25	based	base	VERB
cana-803	250	26	intrusion	intrusion	NOUN
cana-803	250	27	detection	detection	NOUN
cana-803	250	28	system	system	NOUN
cana-803	250	29	(	(	PUNCT
cana-803	250	30	ids	id	NOUN
cana-803	250	31	)	)	PUNCT
cana-803	250	32	performance	performance	NOUN
cana-803	250	33	on	on	ADP
cana-803	250	34	cic	cic	PROPN
cana-803	250	35	ids	ids	PROPN
cana-803	250	36	2017	2017	NUM
cana-803	250	37	dataset	dataset	NOUN
cana-803	250	38	"	"	PUNCT
cana-803	250	39	,	,	PUNCT
cana-803	250	40	j.	j.	PROPN
cana-803	250	41	phys	phys	PROPN
cana-803	250	42	.	.	PUNCT
cana-803	251	1	conf	conf	PROPN
cana-803	251	2	.	.	PUNCT
cana-803	252	1	ser	ser	PROPN
cana-803	252	2	.	.	PROPN
cana-803	252	3	,	,	PUNCT
cana-803	252	4	vol	vol	NOUN
cana-803	252	5	.	.	PROPN
cana-803	252	6	1192	1192	NUM
cana-803	252	7	,	,	PUNCT
cana-803	252	8	no	no	INTJ
cana-803	252	9	.	.	NOUN
cana-803	252	10	1	1	NUM
cana-803	252	11	,	,	PUNCT
cana-803	252	12	2019	2019	NUM
cana-803	252	13	.	.	PUNCT
cana-803	253	1	[	[	X
cana-803	253	2	2	2	NUM
cana-803	253	3	]	]	SYM
cana-803	253	4	3	3	NUM
cana-803	253	5	.	.	PUNCT
cana-803	253	6	a.	a.	PROPN
cana-803	253	7	h.	h.	PROPN
cana-803	253	8	l	l	PROPN
cana-803	253	9	and	and	CCONJ
cana-803	253	10	a.	a.	NOUN
cana-803	253	11	a.	a.	PROPN
cana-803	253	12	g.	g.	PROPN
cana-803	253	13	iman	iman	PROPN
cana-803	253	14	sharafaldin	sharafaldin	PROPN
cana-803	253	15	,	,	PUNCT
cana-803	253	16	"	"	PUNCT
cana-803	253	17	toward	toward	ADP
cana-803	253	18	generating	generate	VERB
cana-803	253	19	a	a	DET
cana-803	253	20	new	new	ADJ
cana-803	253	21	intrusion	intrusion	NOUN
cana-803	253	22	detection	detection	NOUN
cana-803	253	23	dataset	dataset	NOUN
cana-803	253	24	and	and	CCONJ
cana-803	253	25	intrusion	intrusion	NOUN
cana-803	253	26	traffic	traffic	NOUN
cana-803	253	27	characterization	characterization	NOUN
cana-803	253	28	"	"	PUNCT
cana-803	253	29	,	,	PUNCT
cana-803	253	30	proc	proc	NOUN
cana-803	253	31	.	.	PUNCT
cana-803	254	1	4th	4th	ADJ
cana-803	254	2	int	int	PROPN
cana-803	254	3	.	.	PUNCT
cana-803	255	1	conf	conf	PROPN
cana-803	255	2	.	.	PUNCT
cana-803	256	1	inf	inf	PROPN
cana-803	256	2	.	.	PUNCT
cana-803	256	3	syst	syst	PROPN
cana-803	256	4	.	.	PUNCT
cana-803	256	5	secur	secur	PROPN
cana-803	256	6	.	.	PUNCT
cana-803	257	1	priv	priv	PROPN
cana-803	257	2	.	.	PROPN
cana-803	257	3	,	,	PUNCT
cana-803	257	4	no	no	INTJ
cana-803	257	5	.	.	PUNCT
cana-803	258	1	cic	cic	PROPN
cana-803	258	2	,	,	PUNCT
cana-803	258	3	pp	pp	PROPN
cana-803	258	4	.	.	PUNCT
cana-803	259	1	108	108	NUM
cana-803	259	2	-	-	SYM
cana-803	259	3	116	116	NUM
cana-803	259	4	,	,	PUNCT
cana-803	259	5	2018	2018	NUM
cana-803	259	6	.	.	PUNCT
cana-803	260	1	[	[	X
cana-803	260	2	3	3	NUM
cana-803	260	3	]	]	SYM
cana-803	260	4	4	4	NUM
cana-803	260	5	.	.	PUNCT
cana-803	261	1	v.	v.	ADP
cana-803	261	2	hajisalem	hajisalem	NOUN
cana-803	261	3	and	and	CCONJ
cana-803	261	4	s.	s.	PROPN
cana-803	261	5	babaie	babaie	PROPN
cana-803	261	6	,	,	PUNCT
cana-803	261	7	"	"	PUNCT
cana-803	261	8	a	a	DET
cana-803	261	9	hybrid	hybrid	ADJ
cana-803	261	10	intrusion	intrusion	NOUN
cana-803	261	11	detection	detection	NOUN
cana-803	261	12	system	system	NOUN
cana-803	261	13	based	base	VERB
cana-803	261	14	on	on	ADP
cana-803	261	15	abc	abc	PROPN
cana-803	261	16	-	-	PUNCT
cana-803	261	17	afs	afs	NOUN
cana-803	261	18	algorithm	algorithm	NOUN
cana-803	261	19	for	for	ADP
cana-803	261	20	misuse	misuse	NOUN
cana-803	261	21	and	and	CCONJ
cana-803	261	22	anomaly	anomaly	NOUN
cana-803	261	23	detection	detection	NOUN
cana-803	261	24	"	"	PUNCT
cana-803	261	25	,	,	PUNCT
cana-803	261	26	comput	comput	NOUN
cana-803	261	27	.	.	PUNCT
cana-803	262	1	networks	network	NOUN
cana-803	262	2	,	,	PUNCT
cana-803	262	3	vol	vol	NOUN
cana-803	262	4	.	.	PROPN
cana-803	262	5	136	136	NUM
cana-803	262	6	,	,	PUNCT
cana-803	262	7	pp	pp	ADJ
cana-803	262	8	.	.	PUNCT
cana-803	263	1	37	37	NUM
cana-803	263	2	-	-	SYM
cana-803	263	3	50	50	NUM
cana-803	263	4	,	,	PUNCT
cana-803	263	5	2018	2018	NUM
cana-803	263	6	.	.	PUNCT
cana-803	264	1	[	[	X
cana-803	264	2	4	4	NUM
cana-803	264	3	]	]	SYM
cana-803	264	4	9	9	NUM
cana-803	264	5	.	.	PUNCT
cana-803	265	1	p.	p.	NOUN
cana-803	265	2	maniriho	maniriho	PROPN
cana-803	265	3	,	,	PUNCT
cana-803	265	4	detecting	detect	VERB
cana-803	265	5	intrusions	intrusion	NOUN
cana-803	265	6	in	in	ADP
cana-803	265	7	computer	computer	NOUN
cana-803	265	8	network	network	NOUN
cana-803	265	9	traffic	traffic	NOUN
cana-803	265	10	with	with	ADP
cana-803	265	11	machine	machine	NOUN
cana-803	265	12	learning	learn	VERB
cana-803	265	13	approaches	approach	VERB
cana-803	265	14	detecting	detect	VERB
cana-803	265	15	intrusions	intrusion	NOUN
cana-803	265	16	in	in	ADP
cana-803	265	17	computer	computer	NOUN
cana-803	265	18	network	network	NOUN
cana-803	265	19	traffic	traffic	NOUN
cana-803	265	20	with	with	ADP
cana-803	265	21	machine	machine	NOUN
cana-803	265	22	learning	learning	NOUN
cana-803	265	23	approaches	approach	NOUN
cana-803	265	24	,	,	PUNCT
cana-803	265	25	no	no	INTJ
cana-803	265	26	.	.	PUNCT
cana-803	266	1	april	april	PROPN
cana-803	266	2	,	,	PUNCT
cana-803	266	3	2020	2020	NUM
cana-803	266	4	.	.	PUNCT
cana-803	267	1	[	[	X
cana-803	267	2	5	5	NUM
cana-803	267	3	]	]	SYM
cana-803	267	4	10	10	NUM
cana-803	267	5	.	.	PUNCT
cana-803	267	6	k.	k.	PROPN
cana-803	267	7	m.	m.	PROPN
cana-803	267	8	sudar	sudar	PROPN
cana-803	267	9	,	,	PUNCT
cana-803	267	10	p.	p.	PROPN
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cana-803	267	13	p.	p.	NOUN
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cana-803	267	16	p.	p.	NOUN
cana-803	267	17	chinnasamy	chinnasamy	NOUN
cana-803	267	18	,	,	PUNCT
cana-803	267	19	"	"	PUNCT
cana-803	267	20	analysis	analysis	NOUN
cana-803	267	21	of	of	ADP
cana-803	267	22	intruder	intruder	NOUN
cana-803	267	23	detection	detection	NOUN
cana-803	267	24	in	in	ADP
cana-803	267	25	big	big	ADJ
cana-803	267	26	data	datum	NOUN
cana-803	267	27	analytics	analytic	NOUN
cana-803	267	28	"	"	PUNCT
cana-803	267	29	,	,	PUNCT
cana-803	267	30	2021	2021	NUM
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cana-803	267	32	conference	conference	NOUN
cana-803	267	33	on	on	ADP
cana-803	267	34	computer	computer	NOUN
cana-803	267	35	communication	communication	NOUN
cana-803	267	36	and	and	CCONJ
cana-803	267	37	informatics	informatic	NOUN
cana-803	267	38	(	(	PUNCT
cana-803	267	39	iccci	iccci	NOUN
cana-803	267	40	)	)	PUNCT
cana-803	267	41	,	,	PUNCT
cana-803	267	42	pp	pp	ADJ
cana-803	267	43	.	.	PUNCT
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cana-803	268	2	-	-	SYM
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cana-803	268	4	,	,	PUNCT
cana-803	268	5	2021	2021	NUM
cana-803	268	6	.	.	PUNCT
cana-803	269	1	[	[	X
cana-803	269	2	6	6	NUM
cana-803	269	3	]	]	SYM
cana-803	269	4	11	11	NUM
cana-803	269	5	.	.	PUNCT
cana-803	269	6	k.	k.	PROPN
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cana-803	269	10	m.	m.	NOUN
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cana-803	269	16	p.	p.	PROPN
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cana-803	269	19	p.	p.	PROPN
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cana-803	269	27	of	of	ADP
cana-803	269	28	service	service	NOUN
cana-803	269	29	attacks	attack	NOUN
cana-803	269	30	in	in	ADP
cana-803	269	31	sdn	sdn	NOUN
cana-803	269	32	using	use	VERB
cana-803	269	33	machine	machine	NOUN
cana-803	269	34	learning	learn	VERB
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cana-803	269	36	"	"	PUNCT
cana-803	269	37	,	,	PUNCT
cana-803	269	38	2021	2021	NUM
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cana-803	269	41	on	on	ADP
cana-803	269	42	computer	computer	NOUN
cana-803	269	43	communication	communication	NOUN
cana-803	269	44	and	and	CCONJ
cana-803	269	45	informatics	informatic	NOUN
cana-803	269	46	(	(	PUNCT
cana-803	269	47	iccci	iccci	NOUN
cana-803	269	48	)	)	PUNCT
cana-803	269	49	,	,	PUNCT
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cana-803	270	4	,	,	PUNCT
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cana-803	271	1	[	[	X
cana-803	271	2	7	7	NUM
cana-803	271	3	]	]	SYM
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cana-803	271	5	.	.	PUNCT
cana-803	272	1	v.	v.	ADP
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cana-803	272	9	,	,	PUNCT
cana-803	272	10	i.	i.	PROPN
cana-803	272	11	ali	ali	PROPN
cana-803	272	12	,	,	PUNCT
cana-803	272	13	r.	r.	PROPN
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cana-803	272	23	learning	learning	NOUN
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cana-803	272	25	intrusion	intrusion	NOUN
cana-803	272	26	detection	detection	NOUN
cana-803	272	27	in	in	ADP
cana-803	272	28	uavs	uavs	PROPN
cana-803	272	29	"	"	PUNCT
cana-803	272	30	,	,	PUNCT
cana-803	272	31	cmc	cmc	NOUN
cana-803	272	32	-	-	PUNCT
cana-803	272	33	computers	computer	NOUN
cana-803	272	34	materials	material	NOUN
cana-803	272	35	&	&	CCONJ
cana-803	272	36	continua	continua	PROPN
cana-803	272	37	,	,	PUNCT
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cana-803	272	39	.	.	PROPN
cana-803	273	1	70	70	NUM
cana-803	273	2	,	,	PUNCT
cana-803	273	3	no	no	INTJ
cana-803	273	4	.	.	NOUN
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cana-803	273	6	,	,	PUNCT
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cana-803	274	1	26392653	26392653	NUM
cana-803	274	2	,	,	PUNCT
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cana-803	275	3	]	]	PUNCT
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cana-803	275	5	,	,	PUNCT
cana-803	275	6	s.	s.	PROPN
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cana-803	275	8	amdani	amdani	PROPN
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cana-803	275	10	s.y	s.y	PROPN
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cana-803	276	3	)	)	PUNCT
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cana-803	277	4	model	model	NOUN
cana-803	277	5	for	for	ADP
cana-803	277	6	path	path	NOUN
cana-803	277	7	planning	planning	NOUN
cana-803	277	8	using	use	VERB
cana-803	277	9	obstacle	obstacle	NOUN
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cana-803	277	12	.	.	PUNCT
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cana-803	278	9	sl	sl	PROPN
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cana-803	278	33	.	.	PUNCT
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cana-803	279	3	in	in	ADP
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cana-803	279	6	,	,	PUNCT
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cana-803	280	20	"	"	PUNCT
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cana-803	280	22	attack	attack	NOUN
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cana-803	280	24	:	:	PUNCT
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cana-803	280	33	conference	conference	NOUN
cana-803	280	34	on	on	ADP
cana-803	280	35	security	security	NOUN
cana-803	280	36	of	of	ADP
cana-803	280	37	information	information	NOUN
cana-803	280	38	and	and	CCONJ
cana-803	280	39	networks	network	NOUN
cana-803	280	40	,	,	PUNCT
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cana-803	282	17	t.	t.	PROPN
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cana-803	282	30	using	use	VERB
cana-803	282	31	internet	internet	NOUN
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cana-803	282	39	conference	conference	NOUN
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cana-803	282	41	i	i	PROPN
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cana-803	282	57	-	-	PUNCT
cana-803	282	58	smac	smac	PROPN
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cana-803	282	60	,	,	PUNCT
cana-803	282	61	dharan	dharan	PROPN
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cana-803	283	2	-	-	SYM
cana-803	283	3	48	48	NUM
cana-803	283	4	,	,	PUNCT
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cana-803	283	6	:	:	PUNCT
cana-803	283	7	10.1109	10.1109	NUM
cana-803	283	8	/	/	SYM
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cana-803	283	10	.	.	PUNCT
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cana-803	284	2	11	11	NUM
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cana-803	284	8	m.	m.	NOUN
cana-803	284	9	alshurideh	alshurideh	PROPN
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cana-803	284	11	a.	a.	PROPN
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cana-803	284	14	k.	k.	PROPN
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cana-803	284	24	learning	learning	NOUN
cana-803	284	25	techniques	technique	NOUN
cana-803	284	26	for	for	ADP
cana-803	284	27	cybersecurity	cybersecurity	NOUN
cana-803	284	28	:	:	PUNCT
cana-803	284	29	a	a	DET
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cana-803	284	31	"	"	PUNCT
cana-803	284	32	,	,	PUNCT
cana-803	284	33	the	the	DET
cana-803	284	34	international	international	ADJ
cana-803	284	35	conference	conference	NOUN
cana-803	284	36	on	on	ADP
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cana-803	284	38	intelligence	intelligence	NOUN
cana-803	284	39	and	and	CCONJ
cana-803	284	40	computer	computer	NOUN
cana-803	284	41	vision	vision	NOUN
cana-803	284	42	,	,	PUNCT
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cana-803	285	2	-	-	SYM
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cana-803	285	4	,	,	PUNCT
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cana-803	286	14	j.	j.	PROPN
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cana-803	286	17	f.	f.	PROPN
cana-803	286	18	ahmad	ahmad	PROPN
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cana-803	286	20	"	"	PUNCT
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cana-803	286	45	.	.	PROPN
cana-803	287	1	32	32	NUM
cana-803	287	2	,	,	PUNCT
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cana-803	287	4	.	.	NOUN
cana-803	287	5	1	1	NUM
cana-803	287	6	,	,	PUNCT
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cana-803	287	8	.	.	PUNCT
cana-803	288	1	e4150	e4150	NOUN
cana-803	288	2	,	,	PUNCT
cana-803	288	3	2021	2021	NUM
cana-803	288	4	.	.	PUNCT
cana-803	289	1	[	[	X
cana-803	289	2	13	13	NUM
cana-803	289	3	]	]	PUNCT
cana-803	289	4	v.	v.	CCONJ
cana-803	289	5	ramachandran	ramachandran	PROPN
cana-803	289	6	and	and	CCONJ
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cana-803	289	9	,	,	PUNCT
cana-803	289	10	"	"	PUNCT
cana-803	289	11	a	a	DET
cana-803	289	12	tristate	tristate	ADJ
cana-803	289	13	filter	filter	NOUN
cana-803	289	14	for	for	ADP
cana-803	289	15	the	the	DET
cana-803	289	16	removal	removal	NOUN
cana-803	289	17	of	of	ADP
cana-803	289	18	salt	salt	NOUN
cana-803	289	19	and	and	CCONJ
cana-803	289	20	pepper	pepper	NOUN
cana-803	289	21	noise	noise	NOUN
cana-803	289	22	in	in	ADP
cana-803	289	23	mammogram	mammogram	NOUN
cana-803	289	24	images	image	NOUN
cana-803	289	25	"	"	PUNCT
cana-803	289	26	,	,	PUNCT
cana-803	289	27	j	j	PROPN
cana-803	289	28	med	med	PROPN
cana-803	289	29	syst	syst	PROPN
cana-803	289	30	,	,	PUNCT
cana-803	289	31	vol	vol	NOUN
cana-803	289	32	.	.	PROPN
cana-803	290	1	43	43	NUM
cana-803	290	2	,	,	PUNCT
cana-803	290	3	no	no	INTJ
cana-803	290	4	.	.	NOUN
cana-803	290	5	40	40	NUM
cana-803	290	6	,	,	PUNCT
cana-803	290	7	2019	2019	NUM
cana-803	290	8	,	,	PUNCT
cana-803	291	1	[	[	X
cana-803	291	2	online	online	X
cana-803	291	3	]	]	X
cana-803	291	4	available	available	ADJ
cana-803	291	5	:	:	PUNCT
cana-803	291	6	https://doi.org/10.1007/s109160181133-0	https://doi.org/10.1007/s109160181133-0	X
cana-803	291	7	.	.	PUNCT
cana-803	292	1	[	[	X
cana-803	292	2	14	14	NUM
cana-803	292	3	]	]	X
cana-803	292	4	r.	r.	PROPN
cana-803	292	5	t.	t.	PROPN
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cana-803	292	8	p.	p.	PROPN
cana-803	292	9	khobragade	khobragade	PROPN
cana-803	292	10	,	,	PUNCT
cana-803	292	11	"	"	PUNCT
cana-803	292	12	an	an	DET
cana-803	292	13	approach	approach	NOUN
cana-803	292	14	for	for	ADP
cana-803	292	15	class	class	NOUN
cana-803	292	16	imbalance	imbalance	NOUN
cana-803	292	17	using	use	VERB
cana-803	292	18	oversampling	oversample	VERB
cana-803	292	19	technique	technique	NOUN
cana-803	292	20	"	"	PUNCT
cana-803	292	21	,	,	PUNCT
cana-803	292	22	int	int	PROPN
cana-803	292	23	.	.	PUNCT
cana-803	293	1	j.	j.	PROPN
cana-803	293	2	innov	innov	PROPN
cana-803	293	3	.	.	PUNCT
cana-803	294	1	res	re	NOUN
cana-803	294	2	.	.	PUNCT
cana-803	295	1	comput	comput	NOUN
cana-803	295	2	.	.	PUNCT
cana-803	296	1	commun	commun	PROPN
cana-803	296	2	.	.	PUNCT
cana-803	297	1	eng	eng	PROPN
cana-803	297	2	.	.	PROPN
cana-803	297	3	,	,	PUNCT
cana-803	297	4	vol	vol	NOUN
cana-803	297	5	.	.	PROPN
cana-803	298	1	3	3	NUM
cana-803	298	2	,	,	PUNCT
cana-803	298	3	no	no	INTJ
cana-803	298	4	.	.	NOUN
cana-803	298	5	11	11	NUM
cana-803	298	6	,	,	PUNCT
cana-803	298	7	pp	pp	ADJ
cana-803	298	8	.	.	PUNCT
cana-803	299	1	11451	11451	NUM
cana-803	299	2	-	-	SYM
cana-803	299	3	11455	11455	NUM
cana-803	299	4	,	,	PUNCT
cana-803	299	5	2015	2015	NUM
cana-803	299	6	.	.	PUNCT
cana-803	300	1	[	[	X
cana-803	300	2	15	15	NUM
cana-803	300	3	]	]	X
cana-803	300	4	m.a	m.a	PROPN
cana-803	300	5	.	.	PROPN
cana-803	300	6	ferrag	ferrag	PROPN
cana-803	300	7	,	,	PUNCT
cana-803	300	8	o.	o.	PROPN
cana-803	300	9	friha	friha	PROPN
cana-803	300	10	,	,	PUNCT
cana-803	300	11	l.	l.	PROPN
cana-803	300	12	maglaras	maglaras	PROPN
cana-803	300	13	,	,	PUNCT
cana-803	300	14	h.	h.	PROPN
cana-803	300	15	janicke	janicke	PROPN
cana-803	300	16	and	and	CCONJ
cana-803	300	17	l.	l.	PROPN
cana-803	300	18	shu	shu	PROPN
cana-803	300	19	,	,	PUNCT
cana-803	300	20	"	"	PUNCT
cana-803	300	21	federated	federate	VERB
cana-803	300	22	deep	deep	ADJ
cana-803	300	23	learning	learning	NOUN
cana-803	300	24	for	for	ADP
cana-803	300	25	cyber	cyber	ADJ
cana-803	300	26	security	security	NOUN
cana-803	300	27	in	in	ADP
cana-803	300	28	the	the	DET
cana-803	300	29	internet	internet	NOUN
cana-803	300	30	of	of	ADP
cana-803	300	31	things	thing	NOUN
cana-803	300	32	:	:	PUNCT
cana-803	300	33	concepts	concept	VERB
cana-803	300	34	applications	application	NOUN
cana-803	300	35	and	and	CCONJ
cana-803	300	36	experimental	experimental	ADJ
cana-803	300	37	analysis	analysis	NOUN
cana-803	300	38	"	"	PUNCT
cana-803	300	39	,	,	PUNCT
cana-803	300	40	ieee	ieee	NOUN
cana-803	300	41	access	access	NOUN
cana-803	300	42	,	,	PUNCT
cana-803	300	43	vol	vol	NOUN
cana-803	300	44	.	.	NOUN
cana-803	300	45	9	9	NUM
cana-803	300	46	,	,	PUNCT
cana-803	300	47	pp	pp	ADJ
cana-803	300	48	.	.	PUNCT
cana-803	301	1	138509	138509	NUM
cana-803	301	2	-	-	SYM
cana-803	301	3	138542	138542	NUM
cana-803	301	4	,	,	PUNCT
cana-803	301	5	2021	2021	NUM
cana-803	301	6	.	.	PUNCT
cana-803	302	1	[	[	X
cana-803	302	2	16	16	NUM
cana-803	302	3	]	]	PUNCT
cana-803	302	4	j.	j.	PROPN
cana-803	302	5	zhang	zhang	PROPN
cana-803	302	6	,	,	PUNCT
cana-803	302	7	l.	l.	PROPN
cana-803	302	8	pan	pan	PROPN
cana-803	302	9	,	,	PUNCT
cana-803	302	10	q.l	q.l	PROPN
cana-803	302	11	.	.	PROPN
cana-803	302	12	han	han	PROPN
cana-803	302	13	,	,	PUNCT
cana-803	302	14	c.	c.	PROPN
cana-803	302	15	chen	chen	PROPN
cana-803	302	16	,	,	PUNCT
cana-803	302	17	s.	s.	PROPN
cana-803	302	18	wen	wen	PROPN
cana-803	302	19	and	and	CCONJ
cana-803	302	20	y.	y.	PROPN
cana-803	302	21	xiang	xiang	PROPN
cana-803	302	22	,	,	PUNCT
cana-803	302	23	"	"	PUNCT
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cana-803	302	25	learning	learning	NOUN
cana-803	302	26	based	base	VERB
cana-803	302	27	attack	attack	NOUN
cana-803	302	28	detection	detection	NOUN
cana-803	302	29	for	for	ADP
cana-803	302	30	cyberphysical	cyberphysical	ADJ
cana-803	302	31	system	system	NOUN
cana-803	302	32	cybersecurity	cybersecurity	NOUN
cana-803	302	33	:	:	PUNCT
cana-803	302	34	a	a	DET
cana-803	302	35	survey	survey	NOUN
cana-803	302	36	"	"	PUNCT
cana-803	302	37	,	,	PUNCT
cana-803	302	38	ieee	ieee	NOUN
cana-803	302	39	/	/	SYM
cana-803	302	40	caa	caa	PROPN
cana-803	302	41	journal	journal	PROPN
cana-803	302	42	of	of	ADP
cana-803	302	43	automatica	automatica	PROPN
cana-803	302	44	sinica	sinica	PROPN
cana-803	302	45	,	,	PUNCT
cana-803	302	46	vol	vol	NOUN
cana-803	302	47	.	.	PROPN
cana-803	302	48	9	9	NUM
cana-803	302	49	,	,	PUNCT
cana-803	302	50	no	no	INTJ
cana-803	302	51	.	.	NOUN
cana-803	302	52	3	3	NUM
cana-803	302	53	,	,	PUNCT
cana-803	302	54	pp	pp	ADJ
cana-803	302	55	.	.	PUNCT
cana-803	303	1	377	377	NUM
cana-803	303	2	-	-	SYM
cana-803	303	3	391	391	NUM
cana-803	303	4	,	,	PUNCT
cana-803	303	5	2021	2021	NUM
cana-803	303	6	.	.	PUNCT
cana-803	304	1	[	[	X
cana-803	304	2	17	17	NUM
cana-803	304	3	]	]	X
cana-803	304	4	d.	d.	PROPN
cana-803	304	5	l.	l.	PROPN
cana-803	304	6	marino	marino	PROPN
cana-803	304	7	,	,	PUNCT
cana-803	304	8	c.	c.	PROPN
cana-803	304	9	s.	s.	PROPN
cana-803	304	10	wickramasinghe	wickramasinghe	PROPN
cana-803	304	11	,	,	PUNCT
cana-803	304	12	c.	c.	PROPN
cana-803	304	13	rieger	rieger	PROPN
cana-803	304	14	and	and	CCONJ
cana-803	304	15	m.	m.	NOUN
cana-803	304	16	manic	manic	ADJ
cana-803	304	17	,	,	PUNCT
cana-803	304	18	"	"	PUNCT
cana-803	304	19	data	data	NOUN
cana-803	304	20	-	-	PUNCT
cana-803	304	21	driven	drive	VERB
cana-803	304	22	stochastic	stochastic	ADJ
cana-803	304	23	anomaly	anomaly	NOUN
cana-803	304	24	detection	detection	NOUN
cana-803	304	25	on	on	ADP
cana-803	304	26	smart	smart	ADJ
cana-803	304	27	-	-	PUNCT
cana-803	304	28	grid	grid	NOUN
cana-803	304	29	communications	communication	NOUN
cana-803	304	30	using	use	VERB
cana-803	304	31	mixture	mixture	NOUN
cana-803	304	32	poisson	poisson	NOUN
cana-803	304	33	distributions	distribution	NOUN
cana-803	304	34	,	,	PUNCT
cana-803	304	35	"	"	PUNCT
cana-803	304	36	iecon	iecon	NOUN
cana-803	304	37	2019	2019	NUM
cana-803	304	38	45th	45th	ADJ
cana-803	304	39	annual	annual	ADJ
cana-803	304	40	conference	conference	NOUN
cana-803	304	41	of	of	ADP
cana-803	304	42	the	the	DET
cana-803	304	43	ieee	ieee	NOUN
cana-803	304	44	industrial	industrial	PROPN
cana-803	304	45	electronics	electronic	NOUN
cana-803	304	46	society	society	NOUN
cana-803	304	47	,	,	PUNCT
cana-803	304	48	lisbon	lisbon	PROPN
cana-803	304	49	,	,	PUNCT
cana-803	304	50	portugal	portugal	PROPN
cana-803	304	51	,	,	PUNCT
cana-803	304	52	2019	2019	NUM
cana-803	304	53	,	,	PUNCT
cana-803	304	54	pp	pp	ADJ
cana-803	304	55	.	.	PUNCT
cana-803	305	1	5855	5855	NUM
cana-803	305	2	-	-	SYM
cana-803	305	3	5861	5861	NUM
cana-803	305	4	https://doi.org/10.1007/s10916-0181133-0	https://doi.org/10.1007/s10916-0181133-0	PROPN
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cana-803	305	6	communications	communication	NOUN
cana-803	305	7	on	on	ADP
cana-803	305	8	applied	apply	VERB
cana-803	305	9	nonlinear	nonlinear	ADJ
cana-803	305	10	analysis	analysis	NOUN
cana-803	305	11	issn	issn	NOUN
cana-803	305	12	:	:	PUNCT
cana-803	305	13	1074	1074	NUM
cana-803	305	14	-	-	PUNCT
cana-803	305	15	133x	133x	NUM
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cana-803	305	17	31	31	NUM
cana-803	305	18	no	no	NOUN
cana-803	305	19	.	.	PUNCT
cana-803	306	1	3s	3s	NUM
cana-803	306	2	(	(	PUNCT
cana-803	306	3	2024	2024	NUM
cana-803	306	4	)	)	PUNCT
cana-803	306	5	502	502	NUM
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cana-803	307	1	[	[	X
cana-803	307	2	18	18	NUM
cana-803	307	3	]	]	X
cana-803	307	4	r.	r.	PROPN
cana-803	307	5	sharma	sharma	PROPN
cana-803	307	6	,	,	PUNCT
cana-803	307	7	c.	c.	PROPN
cana-803	307	8	a.	a.	PROPN
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cana-803	307	10	and	and	CCONJ
cana-803	307	11	c.	c.	PROPN
cana-803	307	12	leckie	leckie	PROPN
cana-803	307	13	,	,	PUNCT
cana-803	307	14	"	"	PUNCT
cana-803	307	15	evaluation	evaluation	NOUN
cana-803	307	16	of	of	ADP
cana-803	307	17	centralised	centralised	ADJ
cana-803	307	18	vs	vs	ADP
cana-803	307	19	distributed	distribute	VERB
cana-803	307	20	collaborative	collaborative	ADJ
cana-803	307	21	intrusion	intrusion	NOUN
cana-803	307	22	detection	detection	NOUN
cana-803	307	23	systems	system	NOUN
cana-803	307	24	in	in	ADP
cana-803	307	25	multi	multi	ADJ
cana-803	307	26	-	-	ADJ
cana-803	307	27	access	access	ADJ
cana-803	307	28	edge	edge	NOUN
cana-803	307	29	computing	computing	NOUN
cana-803	307	30	,	,	PUNCT
cana-803	307	31	"	"	PUNCT
cana-803	307	32	2020	2020	NUM
cana-803	307	33	ifip	ifip	NOUN
cana-803	307	34	networking	network	VERB
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cana-803	307	36	(	(	PUNCT
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cana-803	307	38	)	)	PUNCT
cana-803	307	39	,	,	PUNCT
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cana-803	307	43	,	,	PUNCT
cana-803	307	44	2020	2020	NUM
cana-803	307	45	,	,	PUNCT
cana-803	307	46	pp	pp	ADV
cana-803	307	47	.	.	PUNCT
cana-803	308	1	343	343	NUM
cana-803	308	2	-	-	SYM
cana-803	308	3	351	351	NUM
cana-803	308	4	.	.	PUNCT
cana-803	309	1	[	[	X
cana-803	309	2	19	19	NUM
cana-803	309	3	]	]	X
cana-803	309	4	h.	h.	PROPN
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cana-803	309	6	,	,	PUNCT
cana-803	309	7	a.	a.	NOUN
cana-803	309	8	a.	a.	PROPN
cana-803	309	9	el	el	PROPN
cana-803	309	10	kalam	kalam	PROPN
cana-803	309	11	and	and	CCONJ
cana-803	309	12	a.	a.	NOUN
cana-803	309	13	a.	a.	NOUN
cana-803	309	14	ouahman	ouahman	PROPN
cana-803	309	15	,	,	PUNCT
cana-803	309	16	"	"	PUNCT
cana-803	309	17	distributed	distribute	VERB
cana-803	309	18	intrusion	intrusion	NOUN
cana-803	309	19	detection	detection	NOUN
cana-803	309	20	system	system	NOUN
cana-803	309	21	based	base	VERB
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cana-803	309	23	anticipation	anticipation	NOUN
cana-803	309	24	and	and	CCONJ
cana-803	309	25	prediction	prediction	NOUN
cana-803	309	26	approach	approach	NOUN
cana-803	309	27	,	,	PUNCT
cana-803	309	28	"	"	PUNCT
cana-803	309	29	2015	2015	NUM
cana-803	309	30	12th	12th	NOUN
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cana-803	309	32	joint	joint	ADJ
cana-803	309	33	conference	conference	NOUN
cana-803	309	34	on	on	ADP
cana-803	309	35	e	e	NOUN
cana-803	309	36	-	-	NOUN
cana-803	309	37	business	business	NOUN
cana-803	309	38	and	and	CCONJ
cana-803	309	39	telecommunications	telecommunication	NOUN
cana-803	309	40	(	(	PUNCT
cana-803	309	41	icete	icete	ADJ
cana-803	309	42	)	)	PUNCT
cana-803	309	43	,	,	PUNCT
cana-803	309	44	colmar	colmar	PROPN
cana-803	309	45	,	,	PUNCT
cana-803	309	46	france	france	PROPN
cana-803	309	47	,	,	PUNCT
cana-803	309	48	2015	2015	NUM
cana-803	309	49	,	,	PUNCT
cana-803	309	50	pp	pp	ADJ
cana-803	309	51	.	.	PUNCT
cana-803	310	1	343	343	NUM
cana-803	310	2	-	-	SYM
cana-803	310	3	348	348	NUM
cana-803	310	4	.	.	PUNCT
cana-803	311	1	[	[	X
cana-803	311	2	20	20	NUM
cana-803	311	3	]	]	X
cana-803	311	4	prashant	prashant	PROPN
cana-803	311	5	khobragade	khobragade	PROPN
cana-803	311	6	,	,	PUNCT
cana-803	311	7	latesh	latesh	ADJ
cana-803	311	8	g.	g.	PROPN
cana-803	311	9	malik,“a	malik,“a	PROPN
cana-803	311	10	review	review	NOUN
cana-803	311	11	on	on	ADP
cana-803	311	12	data	datum	NOUN
cana-803	311	13	generation	generation	NOUN
cana-803	311	14	for	for	ADP
cana-803	311	15	digital	digital	ADJ
cana-803	311	16	forensic	forensic	ADJ
cana-803	311	17	investigation	investigation	NOUN
cana-803	311	18	using	use	VERB
cana-803	311	19	datamining	datamine	VERB
cana-803	311	20	”	"	PUNCT
cana-803	311	21	,	,	PUNCT
cana-803	311	22	ijcat	ijcat	PROPN
cana-803	311	23	international	international	ADJ
cana-803	311	24	journal	journal	NOUN
cana-803	311	25	of	of	ADP
cana-803	311	26	computing	computing	NOUN
cana-803	311	27	and	and	CCONJ
cana-803	311	28	technology	technology	NOUN
cana-803	311	29	,	,	PUNCT
cana-803	311	30	volume	volume	NOUN
cana-803	311	31	1	1	NUM
cana-803	311	32	,	,	PUNCT
cana-803	311	33	issue	issue	NOUN
cana-803	311	34	3	3	NUM
cana-803	311	35	,	,	PUNCT
cana-803	311	36	april	april	PROPN
cana-803	311	37	2014	2014	NUM
cana-803	311	38	.	.	PUNCT
cana-803	312	1	[	[	X
cana-803	312	2	21	21	NUM
cana-803	312	3	]	]	X
cana-803	312	4	s.	s.	PROPN
cana-803	312	5	i.	i.	PROPN
cana-803	312	6	popoola	popoola	PROPN
cana-803	312	7	,	,	PUNCT
cana-803	312	8	g.	g.	PROPN
cana-803	312	9	gui	gui	PROPN
cana-803	312	10	,	,	PUNCT
cana-803	312	11	b.	b.	PROPN
cana-803	312	12	adebisi	adebisi	PROPN
cana-803	312	13	,	,	PUNCT
cana-803	312	14	m.	m.	NOUN
cana-803	312	15	hammoudeh	hammoudeh	PROPN
cana-803	312	16	and	and	CCONJ
cana-803	312	17	h.	h.	PROPN
cana-803	312	18	gacanin	gacanin	PROPN
cana-803	312	19	,	,	PUNCT
cana-803	312	20	"	"	PUNCT
cana-803	312	21	federated	federate	VERB
cana-803	312	22	deep	deep	ADJ
cana-803	312	23	learning	learning	NOUN
cana-803	312	24	for	for	ADP
cana-803	312	25	collaborative	collaborative	ADJ
cana-803	312	26	intrusion	intrusion	NOUN
cana-803	312	27	detection	detection	NOUN
cana-803	312	28	in	in	ADP
cana-803	312	29	heterogeneous	heterogeneous	ADJ
cana-803	312	30	networks	network	NOUN
cana-803	312	31	,	,	PUNCT
cana-803	312	32	"	"	PUNCT
cana-803	312	33	2021	2021	NUM
cana-803	312	34	ieee	ieee	NOUN
cana-803	312	35	94th	94th	ADJ
cana-803	312	36	vehicular	vehicular	ADJ
cana-803	312	37	technology	technology	NOUN
cana-803	312	38	conference	conference	NOUN
cana-803	312	39	(	(	PUNCT
cana-803	312	40	vtc2021	vtc2021	NOUN
cana-803	312	41	-	-	PUNCT
cana-803	312	42	fall	fall	NOUN
cana-803	312	43	)	)	PUNCT
cana-803	312	44	,	,	PUNCT
cana-803	312	45	norman	norman	PROPN
cana-803	312	46	,	,	PUNCT
cana-803	312	47	ok	ok	PROPN
cana-803	312	48	,	,	PUNCT
cana-803	312	49	usa	usa	PROPN
cana-803	312	50	,	,	PUNCT
cana-803	312	51	2021	2021	NUM
cana-803	312	52	,	,	PUNCT
cana-803	312	53	pp	pp	ADJ
cana-803	312	54	.	.	PUNCT
cana-803	313	1	1	1	NUM
cana-803	313	2	-	-	SYM
cana-803	313	3	6	6	NUM
cana-803	313	4	[	[	SYM
cana-803	313	5	22	22	NUM
cana-803	313	6	]	]	X
cana-803	313	7	zha	zha	PROPN
cana-803	313	8	,	,	PUNCT
cana-803	313	9	l.	l.	PROPN
cana-803	313	10	;	;	PUNCT
cana-803	313	11	liao	liao	PROPN
cana-803	313	12	,	,	PUNCT
cana-803	313	13	r.	r.	PROPN
cana-803	313	14	;	;	PUNCT
cana-803	313	15	liu	liu	PROPN
cana-803	313	16	,	,	PUNCT
cana-803	313	17	j.	j.	PROPN
cana-803	313	18	;	;	PUNCT
cana-803	313	19	xie	xie	PROPN
cana-803	313	20	,	,	PUNCT
cana-803	313	21	x.	x.	PROPN
cana-803	313	22	;	;	PUNCT
cana-803	313	23	tian	tian	PROPN
cana-803	313	24	,	,	PUNCT
cana-803	313	25	e.	e.	PROPN
cana-803	313	26	;	;	PUNCT
cana-803	313	27	cao	cao	PROPN
cana-803	313	28	,	,	PUNCT
cana-803	313	29	j.	j.	PROPN
cana-803	313	30	dynamic	dynamic	PROPN
cana-803	313	31	event	event	NOUN
cana-803	313	32	-	-	PUNCT
cana-803	313	33	triggered	trigger	VERB
cana-803	313	34	output	output	NOUN
cana-803	313	35	feedback	feedback	NOUN
cana-803	313	36	control	control	NOUN
cana-803	313	37	for	for	ADP
cana-803	313	38	networked	networked	ADJ
cana-803	313	39	systems	system	NOUN
cana-803	313	40	subject	subject	ADJ
cana-803	313	41	to	to	ADP
cana-803	313	42	multiple	multiple	ADJ
cana-803	313	43	cyber	cyber	NOUN
cana-803	313	44	attacks	attack	NOUN
cana-803	313	45	.	.	PUNCT
cana-803	314	1	ieee	ieee	PROPN
cana-803	314	2	trans	trans	PROPN
cana-803	314	3	.	.	PUNCT
cana-803	315	1	cybern	cybern	PROPN
cana-803	315	2	.	.	PUNCT
cana-803	316	1	2021	2021	NUM
cana-803	316	2	,	,	PUNCT
cana-803	316	3	52	52	NUM
cana-803	316	4	,	,	PUNCT
cana-803	316	5	13800–13808	13800–13808	NUM
cana-803	316	6	.	.	PUNCT
cana-803	317	1	[	[	X
cana-803	317	2	23	23	NUM
cana-803	317	3	]	]	X
cana-803	317	4	qu	qu	PROPN
cana-803	317	5	,	,	PUNCT
cana-803	317	6	f.	f.	PROPN
cana-803	317	7	;	;	PUNCT
cana-803	317	8	tian	tian	PROPN
cana-803	317	9	,	,	PUNCT
cana-803	317	10	e.	e.	PROPN
cana-803	317	11	;	;	PUNCT
cana-803	317	12	zhao	zhao	PROPN
cana-803	317	13	,	,	PUNCT
cana-803	317	14	x.	x.	NOUN
cana-803	317	15	chance	chance	NOUN
cana-803	317	16	-	-	PUNCT
cana-803	317	17	constrained	constrain	VERB
cana-803	317	18	h	h	NOUN
cana-803	317	19	-	-	PUNCT
cana-803	317	20	infinity	infinity	NOUN
cana-803	317	21	state	state	NOUN
cana-803	317	22	estimation	estimation	NOUN
cana-803	317	23	for	for	ADP
cana-803	317	24	recursive	recursive	ADJ
cana-803	317	25	neural	neural	ADJ
cana-803	317	26	networks	network	NOUN
cana-803	317	27	under	under	ADP
cana-803	317	28	deception	deception	NOUN
cana-803	317	29	attacks	attack	NOUN
cana-803	317	30	and	and	CCONJ
cana-803	317	31	energy	energy	NOUN
cana-803	317	32	constraints	constraint	NOUN
cana-803	317	33	:	:	PUNCT
cana-803	317	34	the	the	DET
cana-803	317	35	finite	finite	ADJ
cana-803	317	36	-	-	ADJ
cana-803	317	37	horizon	horizon	NOUN
cana-803	317	38	case	case	NOUN
cana-803	317	39	.	.	PUNCT
cana-803	318	1	ieee	ieee	PROPN
cana-803	318	2	trans	trans	PROPN
cana-803	318	3	.	.	PUNCT
cana-803	318	4	neural	neural	ADJ
cana-803	318	5	netw	netw	NOUN
cana-803	318	6	.	.	PUNCT
cana-803	319	1	learn	learn	VERB
cana-803	319	2	.	.	PUNCT
cana-803	320	1	syst	syst	PROPN
cana-803	320	2	.	.	PUNCT
cana-803	320	3	2022	2022	NUM
cana-803	320	4	.	.	PUNCT
cana-803	320	5	2014	2014	NUM
cana-803	321	1	[	[	X
cana-803	321	2	24	24	NUM
cana-803	321	3	]	]	X
cana-803	321	4	khetani	khetani	X
cana-803	321	5	,	,	PUNCT
cana-803	321	6	v.	v.	PROPN
cana-803	321	7	(	(	PUNCT
cana-803	321	8	2022	2022	NUM
cana-803	321	9	)	)	PUNCT
cana-803	321	10	.	.	PUNCT
cana-803	322	1	advanced	advanced	ADJ
cana-803	322	2	numerical	numerical	ADJ
cana-803	322	3	methods	method	NOUN
cana-803	322	4	for	for	ADP
cana-803	322	5	solving	solve	VERB
cana-803	322	6	partial	partial	ADJ
cana-803	322	7	differential	differential	ADJ
cana-803	322	8	equations	equation	NOUN
cana-803	322	9	in	in	ADP
cana-803	322	10	structural	structural	ADJ
cana-803	322	11	engineering	engineering	NOUN
cana-803	322	12	.	.	PUNCT
cana-803	323	1	engimathica	engimathica	PROPN
cana-803	323	2	:	:	PUNCT
cana-803	323	3	journal	journal	PROPN
cana-803	323	4	of	of	ADP
cana-803	323	5	engineering	engineering	NOUN
cana-803	323	6	mathematics	mathematic	NOUN
cana-803	323	7	and	and	CCONJ
cana-803	323	8	applications	application	NOUN
cana-803	323	9	,	,	PUNCT
cana-803	323	10	1(1	1(1	NUM
cana-803	323	11	)	)	PUNCT
cana-803	323	12	.	.	PUNCT
cana-803	324	1	[	[	X
cana-803	324	2	25	25	NUM
cana-803	324	3	]	]	PUNCT
cana-803	324	4	rajawat	rajawat	PROPN
cana-803	324	5	,	,	PUNCT
cana-803	324	6	a.	a.	PROPN
cana-803	324	7	s.	s.	PROPN
cana-803	324	8	,	,	PUNCT
cana-803	324	9	goyal	goyal	PROPN
cana-803	324	10	,	,	PUNCT
cana-803	324	11	s.	s.	PROPN
cana-803	324	12	b.	b.	PROPN
cana-803	324	13	,	,	PUNCT
cana-803	324	14	solanki	solanki	PROPN
cana-803	324	15	,	,	PUNCT
cana-803	324	16	r.	r.	PROPN
cana-803	324	17	k.	k.	PROPN
cana-803	324	18	,	,	PUNCT
cana-803	324	19	gadekar	gadekar	PROPN
cana-803	324	20	,	,	PUNCT
cana-803	324	21	a.	a.	PROPN
cana-803	324	22	,	,	PUNCT
cana-803	324	23	&	&	CCONJ
cana-803	324	24	patil	patil	PROPN
cana-803	324	25	,	,	PUNCT
cana-803	324	26	d.	d.	PROPN
cana-803	324	27	(	(	PUNCT
cana-803	324	28	2024	2024	NUM
cana-803	324	29	)	)	PUNCT
cana-803	324	30	.	.	PUNCT
cana-803	325	1	dark	dark	PROPN
cana-803	325	2	web	web	PROPN
cana-803	325	3	financial	financial	PROPN
cana-803	325	4	fraud	fraud	NOUN
cana-803	325	5	identification	identification	NOUN
cana-803	325	6	using	use	VERB
cana-803	325	7	mathematical	mathematical	ADJ
cana-803	325	8	models	model	NOUN
cana-803	325	9	in	in	ADP
cana-803	325	10	healthcare	healthcare	NOUN
cana-803	325	11	domain	domain	NOUN
cana-803	325	12	.	.	PUNCT
cana-803	326	1	joiv	joiv	PROPN
cana-803	326	2	:	:	PUNCT
cana-803	326	3	international	international	ADJ
cana-803	326	4	journal	journal	NOUN
cana-803	326	5	on	on	ADP
cana-803	326	6	informatics	informatics	PROPN
cana-803	326	7	visualization	visualization	NOUN
cana-803	326	8	,	,	PUNCT
cana-803	326	9	8(1	8(1	NOUN
cana-803	326	10	)	)	PUNCT
cana-803	326	11	,	,	PUNCT
cana-803	326	12	107	107	NUM
cana-803	326	13	-	-	SYM
cana-803	326	14	114	114	NUM
cana-803	326	15	.	.	PUNCT
cana-803	327	1	[	[	X
cana-803	327	2	26	26	NUM
cana-803	327	3	]	]	X
cana-803	327	4	nemade	nemade	PROPN
cana-803	327	5	,	,	PUNCT
cana-803	327	6	b.	b.	PROPN
cana-803	327	7	,	,	PUNCT
cana-803	327	8	mishra	mishra	PROPN
cana-803	327	9	,	,	PUNCT
cana-803	327	10	r.	r.	PROPN
cana-803	327	11	,	,	PUNCT
cana-803	327	12	jangid	jangid	ADJ
cana-803	327	13	,	,	PUNCT
cana-803	327	14	p.	p.	NOUN
cana-803	327	15	,	,	PUNCT
cana-803	327	16	dubal	dubal	PROPN
cana-803	327	17	,	,	PUNCT
cana-803	327	18	s.	s.	PROPN
cana-803	327	19	,	,	PUNCT
cana-803	327	20	bharadi	bharadi	NOUN
cana-803	327	21	,	,	PUNCT
cana-803	327	22	v.	v.	PROPN
cana-803	327	23	,	,	PUNCT
cana-803	327	24	&	&	CCONJ
cana-803	327	25	kaul	kaul	PROPN
cana-803	327	26	,	,	PUNCT
cana-803	327	27	v.	v.	PROPN
cana-803	327	28	(	(	PUNCT
cana-803	327	29	2023	2023	NUM
cana-803	327	30	)	)	PUNCT
cana-803	327	31	.	.	PUNCT
cana-803	328	1	improving	improve	VERB
cana-803	328	2	rainfall	rainfall	NOUN
cana-803	328	3	prediction	prediction	NOUN
cana-803	328	4	accuracy	accuracy	NOUN
cana-803	328	5	using	use	VERB
cana-803	328	6	an	an	DET
cana-803	328	7	lstm	lstm	NOUN
cana-803	328	8	-	-	PUNCT
cana-803	328	9	driven	drive	VERB
cana-803	328	10	model	model	NOUN
cana-803	328	11	enhanced	enhance	VERB
cana-803	328	12	by	by	ADP
cana-803	328	13	m	m	NOUN
cana-803	328	14	-	-	ADJ
cana-803	328	15	pso	pso	ADJ
cana-803	328	16	optimization	optimization	NOUN
cana-803	328	17	.	.	PUNCT
cana-803	329	1	journal	journal	NOUN
cana-803	329	2	of	of	ADP
cana-803	329	3	electrical	electrical	ADJ
cana-803	329	4	systems	system	NOUN
cana-803	329	5	,	,	PUNCT
cana-803	329	6	19(3	19(3	NUM
cana-803	329	7	)	)	PUNCT
cana-803	329	8	.	.	PUNCT
cana-803	330	1	[	[	X
cana-803	330	2	27	27	NUM
cana-803	330	3	]	]	X
cana-803	330	4	mishra	mishra	PROPN
cana-803	330	5	,	,	PUNCT
cana-803	330	6	r.	r.	PROPN
cana-803	330	7	,	,	PUNCT
cana-803	330	8	nemade	nemade	PROPN
cana-803	330	9	,	,	PUNCT
cana-803	330	10	b.	b.	PROPN
cana-803	330	11	,	,	PUNCT
cana-803	330	12	shah	shah	PROPN
cana-803	330	13	,	,	PUNCT
cana-803	330	14	k.	k.	PROPN
cana-803	330	15	,	,	PUNCT
cana-803	330	16	&	&	CCONJ
cana-803	330	17	jangid	jangid	PROPN
cana-803	330	18	,	,	PUNCT
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cana-803	330	20	(	(	PUNCT
cana-803	330	21	2023	2023	NUM
cana-803	330	22	)	)	PUNCT
cana-803	330	23	.	.	PUNCT
cana-803	331	1	improved	improve	VERB
cana-803	331	2	inductive	inductive	ADJ
cana-803	331	3	learning	learn	VERB
cana-803	331	4	approach-5	approach-5	PROPN
cana-803	331	5	(	(	PUNCT
cana-803	331	6	iila-5	iila-5	X
cana-803	331	7	)	)	PUNCT
cana-803	331	8	in	in	ADP
cana-803	331	9	distributed	distribute	VERB
cana-803	331	10	system	system	NOUN
cana-803	331	11	.	.	PUNCT
cana-803	332	1	international	international	ADJ
cana-803	332	2	journal	journal	NOUN
cana-803	332	3	of	of	ADP
cana-803	332	4	intelligent	intelligent	ADJ
cana-803	332	5	systems	system	NOUN
cana-803	332	6	and	and	CCONJ
cana-803	332	7	applications	application	NOUN
cana-803	332	8	in	in	ADP
cana-803	332	9	engineering	engineering	NOUN
cana-803	332	10	,	,	PUNCT
cana-803	332	11	11(10s	11(10s	NUM
cana-803	332	12	)	)	PUNCT
cana-803	332	13	,	,	PUNCT
cana-803	332	14	942953	942953	NUM
cana-803	332	15	.	.	PUNCT
cana-803	333	1	[	[	X
cana-803	333	2	28	28	NUM
cana-803	333	3	]	]	X
cana-803	333	4	gulhane	gulhane	NOUN
cana-803	333	5	,	,	PUNCT
cana-803	333	6	m.	m.	NOUN
cana-803	333	7	,	,	PUNCT
cana-803	333	8	kumar	kumar	PROPN
cana-803	333	9	,	,	PUNCT
cana-803	333	10	s.	s.	PROPN
cana-803	333	11	,	,	PUNCT
cana-803	333	12	&	&	CCONJ
cana-803	333	13	borkar	borkar	PROPN
cana-803	333	14	,	,	PUNCT
cana-803	333	15	p.	p.	NOUN
cana-803	333	16	(	(	PUNCT
cana-803	333	17	2023	2023	NUM
cana-803	333	18	,	,	PUNCT
cana-803	333	19	november	november	PROPN
cana-803	333	20	)	)	PUNCT
cana-803	333	21	.	.	PUNCT
cana-803	334	1	an	an	DET
cana-803	334	2	empirical	empirical	ADJ
cana-803	334	3	analysis	analysis	NOUN
cana-803	334	4	of	of	ADP
cana-803	334	5	machine	machine	NOUN
cana-803	334	6	learning	learning	NOUN
cana-803	334	7	models	model	NOUN
cana-803	334	8	with	with	ADP
cana-803	334	9	performance	performance	NOUN
cana-803	334	10	comparison	comparison	NOUN
cana-803	334	11	and	and	CCONJ
cana-803	334	12	insights	insight	NOUN
cana-803	334	13	for	for	ADP
cana-803	334	14	heart	heart	NOUN
cana-803	334	15	disease	disease	NOUN
cana-803	334	16	prediction	prediction	NOUN
cana-803	334	17	.	.	PUNCT
cana-803	335	1	in	in	ADP
cana-803	335	2	2023	2023	NUM
cana-803	335	3	3rd	3rd	ADJ
cana-803	335	4	international	international	ADJ
cana-803	335	5	conference	conference	NOUN
cana-803	335	6	on	on	ADP
cana-803	335	7	technological	technological	ADJ
cana-803	335	8	advancements	advancement	NOUN
cana-803	335	9	in	in	ADP
cana-803	335	10	computational	computational	ADJ
cana-803	335	11	sciences	science	NOUN
cana-803	335	12	(	(	PUNCT
cana-803	335	13	ictacs	ictac	NOUN
cana-803	335	14	)	)	PUNCT
cana-803	335	15	(	(	PUNCT
cana-803	335	16	pp	pp	X
cana-803	335	17	.	.	PUNCT
cana-803	336	1	374	374	NUM
cana-803	336	2	-	-	SYM
cana-803	336	3	381	381	NUM
cana-803	336	4	)	)	PUNCT
cana-803	336	5	.	.	PUNCT
cana-803	337	1	ieee	ieee	PROPN
cana-803	337	2	.	.	PUNCT
cana-803	338	1	[	[	X
cana-803	338	2	29	29	NUM
cana-803	338	3	]	]	X
cana-803	338	4	goyal	goyal	PROPN
cana-803	338	5	,	,	PUNCT
cana-803	338	6	dinesh	dinesh	PROPN
cana-803	338	7	,	,	PUNCT
cana-803	338	8	kumar	kumar	PROPN
cana-803	338	9	,	,	PUNCT
cana-803	338	10	anil	anil	PROPN
cana-803	338	11	,	,	PUNCT
cana-803	338	12	gandhi	gandhi	PROPN
cana-803	338	13	,	,	PUNCT
cana-803	338	14	yatin	yatin	NOUN
cana-803	338	15	&	&	CCONJ
cana-803	338	16	khetani	khetani	PROPN
cana-803	338	17	,	,	PUNCT
cana-803	338	18	vinit	vinit	NOUN
cana-803	338	19	(	(	PUNCT
cana-803	338	20	2024	2024	NUM
cana-803	338	21	)	)	PUNCT
cana-803	338	22	securing	secure	VERB
cana-803	338	23	wireless	wireless	ADJ
cana-803	338	24	sensor	sensor	NOUN
cana-803	338	25	networks	network	NOUN
cana-803	338	26	with	with	ADP
cana-803	338	27	novel	novel	ADJ
cana-803	338	28	hybrid	hybrid	ADJ
cana-803	338	29	lightweight	lightweight	ADJ
cana-803	338	30	cryptographic	cryptographic	ADJ
cana-803	338	31	protocols	protocol	NOUN
cana-803	338	32	,	,	PUNCT
cana-803	338	33	journal	journal	NOUN
cana-803	338	34	of	of	ADP
cana-803	338	35	discrete	discrete	ADJ
cana-803	338	36	mathematical	mathematical	ADJ
cana-803	338	37	sciences	science	NOUN
cana-803	338	38	and	and	CCONJ
cana-803	338	39	cryptography	cryptography	NOUN
cana-803	338	40	,	,	PUNCT
cana-803	338	41	27:2	27:2	NUM
cana-803	338	42	-	-	SYM
cana-803	338	43	b	b	NOUN
cana-803	338	44	,	,	PUNCT
cana-803	338	45	703–714	703–714	NUM
cana-803	338	46	,	,	PUNCT
cana-803	338	47	doi	doi	NOUN
cana-803	338	48	:	:	PUNCT
cana-803	338	49	10.47974	10.47974	NUM
cana-803	338	50	/	/	SYM
cana-803	338	51	jdmsc-1921	jdmsc-1921	NOUN