Proceedings of the Korean Institute of Intelligent Systems Conference (한국지능시스템학회:학술대회논문집)

Korean Institute of Intelligent Systems (한국지능시스템학회)
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Intrusion detection algorithm based on clustering : Kernel-ART

  • Lee, Hansung (Computer Science, Korea University) ;
  • Younghee Im (Computer and Communications Engineering, Daejeon University) ;
  • Park, Jooyoung (Control and Instrumentation Engineering, Korea University) ;
  • Park, Daihee (Computer Science, Korea University)
  • Published : 2002.05.01
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Abstract

In this paper, we propose a new intrusion detection algorithm based on clustering: Kernel-ART, which is composed of the on-line clustering algorithm, ART (adaptive resonance theory), combining with mercer-kernel and concept vector. Kernel-ART is not only satisfying all desirable characteristics in the context of clustering-based 105 but also alleviating drawbacks associated with the supervised learning IDS. It is able to detect various types of intrusions in real-time by means of generating clusters incrementally.

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