论文库
Intrusion detection algorithm based on OCSVM in industrial control system
论文编号:
第一作者: Shang WL(尚文利);Zeng P(曾鹏);Wan M(万明);Li L(李琳);An PF(安攀峰)
联系作者:
发表年度: 2016
期: 10
卷: 9
页: 1014-1049
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.
英文摘要:
刊物名称: Security and Communication Networks
学科:
论文出处:
论文类别:
参与作者:
影响因子:
全文链接: