Immune clonal selection wavelet network based intrusion detection

Authors:
Fang Liu;Lan Luo
Affiliations:
School of Computer Science and Engineering, Xidian University, Xi’an, China;School of Computer Science and Engineering, Xidian University, Xi’an, China
Venue:
ICANN'05 Proceedings of the 15th international conference on Artificial Neural Networks: biological Inspirations - Volume Part I
Year:
2005

Citing 2
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Review: The use of computational intelligence in intrusion detection systems: A review

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Abstract

The ICSA (Immune Clonal Selection Algorithm) based structure and parameter learning of wavelet network for intrusion detection is proposed. The hierarchical structure is used in the coding scheme, thus we can realize evolution of topologic structure and the parameter learning of the wavelet network meanwhile. The experimental results show that the method based on ICSA can get higher true rate of IDS (Intrusion Detection System) than advanced wavelet network and Immune wavelet network. At the same time, the method proposed can reduce the false rate of IDS and has faster convergence speed in experiment.