Proceedings of the Korean Institute of Intelligent Systems Conference (한국지능시스템학회:학술대회논문집)
- 2002.05a
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- Pages.109-113
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- 2002
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
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.