• 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