id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
fcis-10302	Wang, Zhaolian; Huang, Hong; Du, Rui; Li, Xing; Yuan, Guotao	IoT Intrusion Detection Model based on CNN-GRU	2023	6	.pdf	application/pdf	4251	256	54	In the exploration of IoT intrusion detection models, several methods and techniques have been proposed by researchers. To reduce data, feature redundancy during the identification process, this study proposes the use of Extreme Gradient Boosting (XGBoost) for feature selection to obtain an optimal feature subset.	cache/fcis-10302.pdf	txt/fcis-10302.txt