Abnormal Traffic Detection of Industrial Edge Network Based on Deep Nature Learning

CORC > 沈阳自动化研究所 > 中国科学院沈阳自动化研究所 > 工业控制网络与系统研究室

	Abnormal Traffic Detection of Industrial Edge Network Based on Deep Nature Learning
	Liu Q(刘琦)3,4; Zhang BW(张博文)1,4; Zhao JM(赵剑明)1,4; Zang CZ(臧传治)1,4; Wang, Xibo 3; Li, Tong 2
	2021
会议日期	July 19-23, 2021
会议地点	Dublin, Ireland
关键词	Industrial edge network Abnormal flow detection Deep learning Convolutional Neural Network
页码	622-632
英文摘要	In view of the network and application security risks in the field of industrial Internet edge computing, a method for classifying abnormal traffic of industrial edge network based on Convolution Neural Network (CNN) is presented, which is designed by using feature self-learning through analyzing the substantial flow content and protocol hierarchy characteristics of edge network packets. Authors present an abnormal traffic detection model for industrial edge network based on CNN, by using the preprocessed raw traffic data as sample data to directly learn features. The experimental results show that the average accuracy of the trained and optimized model is 98.76%, which can meet the practical application standard of the industrial edge network anomaly traffic detection task.
产权排序	1
会议录	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
会议录出版者	Springer Science and Business Media Deutschland GmbH
会议录出版地	Berlin
语种	英语
ISSN号	0302-9743
ISBN号	978-3-030-78611-3
内容类型	会议论文
源URL	[http://ir.sia.cn/handle/173321/29413]
专题	沈阳自动化研究所_工业控制网络与系统研究室
通讯作者	Zang CZ(臧传治)
作者单位	1.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China 2.State Grid Liaoning Electric Power Research Institute, Shenyang 110004, China 3.School of Information Science and Engineering, Shenyang University of Technology, Shenyang 110870, China 4.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
推荐引用方式 GB/T 7714	Liu Q,Zhang BW,Zhao JM,et al. Abnormal Traffic Detection of Industrial Edge Network Based on Deep Nature Learning[C]. 见:. Dublin, Ireland. July 19-23, 2021.