Network anomaly behavior detection using an adaptive multiplex detector

Authors:
Misun Kim;Minsoo Kim;JaeHyun Seo
Affiliations:
Dept. of Computer Engineering, Mokpo Nat'l Univ., Mokpo, Korea;Dept. of Information Security, Mokpo Nat'l Univ., Mokpo, Korea;Dept. of Information Security, Mokpo Nat'l Univ., Mokpo, Korea
Venue:
ICCSA'06 Proceedings of the 2006 international conference on Computational Science and Its Applications - Volume Part III
Year:
2006

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Abstract

Due to the diversified threat elements of resources and information in computer network system, the research on a biological immune system is becoming one way for network security. Inspired by adaptive immune system principles of artificial immune system, we proposed an anomaly detection algorithm using a multiplex detector. In this algorithm, the multiplex detector is created by applying negative selection, positive selection and clonal selection to detect anomaly behaviors in network. Also the multiplex detector gives an effective method and dynamic detection. In this paper, the detectors are classified by K-detector, memory detector, B-detector, and T-detector for achieving multi level detection. We apply this algorithm in intrusion detection and, to be sure, it has a good performance.