id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
hij-633	Aljabri, Malak; Shaahid, Afrah; Alnasser, Fatima; Saleh, Asalah; Alomari, Dorieh; Aboulnour, Menna; Al-Eidarous, Walla; Althubaity, Areej	IoT Attacks Detection Using Supervised Machine Learning Techniques	2024	17	.pdf	application/pdf	9080	549	50	IoT attack detection datasets often suffer from class imbalances. Despite this, we still obtained excellent results, further underscoring the importance of the three features: Fwd Pkts/s, Bwd Pkts/s, and Pkt Len Max in IoT device attack detection.	cache/hij-633.pdf	txt/hij-633.txt