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