Improved realtime intrusion detection system

Authors:
Byung-Joo Kim;Kon Kim
Affiliations:
Youngsan University Dept. of Information and Communication Engineering, Yangsan-si, Kyoungnam, Korea;Kyungpook National University Department of Computer Science, Korea
Venue:
ICONIP'06 Proceedings of the 13th international conference on Neural information processing - Volume Part III
Year:
2006

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Abstract

We developed earlier version of realtime intrusion detection system using emperical kernel map combining least squares SVM(LSSVM). I consists of two parts. One part is feature extraction by empirical kernel map and the other one is classification by LS-SVM. The main problem of earlier system is that it is not operated realtime because LSSVM is executed in batch way. In this paper we propose an improved real time intrusion detection system incorporating earlier developed system with incremental LS-SVM. Applying the proposed system to KDD CUP 99 data, experimental results show that it has a remarkable feature feature extraction, classification performance and reducing detection time compared to earlier version of realtime ntrusion detection system.