An immunity-based dynamic multilayer intrusion detection system

Authors:
Gang Liang;Tao Li;Jiancheng Ni;Yaping Jiang;Jin Yang;Xun Gong
Affiliations:
Department of Computer Science, Sichuan University, Chengdu, China;Department of Computer Science, Sichuan University, Chengdu, China;Department of Computer Science, Sichuan University, Chengdu, China;Department of Computer Science, Sichuan University, Chengdu, China;Department of Computer Science, Sichuan University, Chengdu, China;Department of Computer Science, Sichuan University, Chengdu, China
Venue:
ICIC'06 Proceedings of the 2006 international conference on Computational Intelligence and Bioinformatics - Volume Part III
Year:
2006

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Abstract

A real computer network produces new network traffic continuously in real time, thus the normal behaviors of network traffic are different in different time, but the self set of current network detection systems based on immunity are static. If the network environments change, the false negative rates and false positive rates will increase rapidly. So the traditional method can not adapt to changing network environments. In order to get over the limitation of the traditional means, an immunity-based dynamic intrusion detection system is proposed in this paper. In the proposed model, a dynamic renewal process of self set is described in detail. In addition, we establish a new set to improve the detection precision and shorten the training phase by adding the characters of the current known attacks to memory cell set. The experimental results show that the new model not only reduces the false negative rates and false positive rates effectively but also has the feature to adapt to continuous changing network environments.