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Probabilistic Models Based Intrusion Detection Using Sequence Characteristics in Control System Communication

  • Takashi Onoda
Part of the Communications in Computer and Information Science book series (CCIS, volume 459)

Abstract

The importance of cyber security has increased with the networked and highly complex structure of computer systems, and the increased value of information. In this paper, we compare Conditional Random Field based intrusion detection with the other probabilistic models based intrusion detection. Theses methods uses the sequence characteristics of network traffic in the control system communication. The learning only utilizes normal data, assuming that there is no prior knowledge on attacks in the system. We applied these two probabilistic models to intrusion detection in DARPA data and an experimental control system network, and compared the differences in the performance.

Keywords

CRF HMM Control System Communication Intrusion Detection Sequence 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Takashi Onoda
    • 1
  1. 1.System Engineering System Laboratory, Central Research Institute of Electric Power IndustryKomae-shiJapan

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