DocumentCode :
3755406
Title :
Industrial communication intrusion detection algorithm based on improved one-class SVM
Author :
Wenli Shang; Lin Li; Ming Wan; Peng Zeng
Author_Institution :
Shenyang Institute of Automation Chinese Academy of Science, 110016, China
fYear :
2015
Firstpage :
21
Lastpage :
25
Abstract :
Anomaly detection based on communication behavior is one of difficult problems of industrial control systems for intrusion detection. A normal communication behavior control model is established by using improved one-class SVM and a PSO-OCSVM algorithm based on particle swarm algorithm is designed to optimize parameters in this paper. This method established an intrusion detection model to identify abnormal Modbus TCP traffic according to the normal Modbus function code sequence. And the efficiency, reliability and real-time of the proposed method met the industrial control system for anomaly detection are proved by simulation results.
Keywords :
"Support vector machines","Stochastic processes","Rain","Optimization"
Publisher :
ieee
Conference_Titel :
Industrial Control Systems Security (WCICSS), 2015 World Congress on
Type :
conf
DOI :
10.1109/WCICSS.2015.7420317
Filename :
7420317
Link To Document :
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