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Anomaly Detection Mechanism based on the Session Patterns and Fuzzy Cognitive Maps

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2005, 10(6), pp.9-16
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science

Ryu Dae Hee 1 Se-Yul Lee 1 Kim, Hyeock-Jin 1 송영덕 2

1청운대학교
2한서대학교

Candidate

ABSTRACT

Recently, since the number of internet users is increasing rapidly and, by using the public hacking tools, general network users can intrude computer systems easily, the hacking problem is getting more serious. In order to prevent the intrusion, it is needed to detect the sign in advance of intrusion in a positive prevention by detecting the various forms of hackers intrusion trials to know the vulnerability of systems. The existing network-based anomaly detection algorithms that cope with port-scanning and the network vulnerability scans have some weakness in intrusion detection. they can not detect slow scans and coordinated scans. therefore, the new concept of algorithm is needed to detect effectively the various. In this paper, we propose a detection algorithm for session patterns and FCM.

Citation status

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