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Intrusion detection algorithm based on OCSVM in industrial control system
Shang WL(尚文利); Zeng P(曾鹏); Wan M(万明); Li L(李琳); An PF(安攀峰)
作者部门工业控制网络与系统研究室
关键词Svm Intrusion Detection Pso
发表期刊Security and Communication Networks
ISSN1939-0114
2016
卷号9期号:10页码:1014-1049
收录类别SCI ; EI
EI收录号20160101756940
WOS记录号WOS:000379052200009
产权排序1
资助机构National Natural Science Foundation of China [61501447] ; Independent project of Key Laboratory of Networked Control System Chinese Academy of Sciences: Research on abnormal behavior modeling, online intrusion detection and self-learning method in industrial control network
摘要In order to detect abnormal communication behaviors efficiently in today's industrial control system, a new intrusion detection algorithm based on One-Class Support Vector Machine (OCSVM) is proposed in this paper. In this algorithm, a normal communication behavior model is established by using OCSVM, and the Particle Swarm Optimization algorithm is designed to optimize OCSVM model parameters. Furthermore, we adopt the normal Modbus function code sequence to train OCSVM model, and then use this model to detect abnormal Modbus TCP traffic. Our simulation results show that the proposed algorithm not only is efficient and reliable but also meets the real-time requirements of anomaly detection in industrial control system.
语种英语
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文献类型期刊论文
条目标识符http://ir.sia.cn/handle/173321/17603
专题工业控制网络与系统研究室
通讯作者Zeng P(曾鹏)
作者单位1.Industry Control Network and Systems Laboratory, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China
2.Shenyang Ligong University, Shenyang, China
推荐引用方式
GB/T 7714
Shang WL,Zeng P,Wan M,et al. Intrusion detection algorithm based on OCSVM in industrial control system[J]. Security and Communication Networks,2016,9(10):1014-1049.
APA Shang WL,Zeng P,Wan M,Li L,&An PF.(2016).Intrusion detection algorithm based on OCSVM in industrial control system.Security and Communication Networks,9(10),1014-1049.
MLA Shang WL,et al."Intrusion detection algorithm based on OCSVM in industrial control system".Security and Communication Networks 9.10(2016):1014-1049.
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