A Fuzzy Anomaly Detection Algorithm for IPv6

Authors:
Li Yao;Li ZhiTang;Liu Shuyu
Affiliations:
Huazhong university of science and technology, China;Huazhong university of science and technology, China;Huazhong university of science and technology, China
Venue:
SKG '06 Proceedings of the Second International Conference on Semantics, Knowledge, and Grid
Year:
2006

Citing 0
Cited 1

Network intrusion detection: Evaluating cluster, discriminant, and logit analysis

Information Sciences: an International Journal

Quantified Score

Hi-index	0.00

Visualization

Abstract

To accomplish the anomaly detection based on IPv6, genetic algo-rithm can used as a efficacious rules generation technology. We developed a fuzzy anomaly detection model for IPv6, using fuzzy detection anomaly algorithm with negative selection inspired by biol-ogy and propose a fuzzy anomaly detec-tion rules generation technology for IPv6 using genetic algorithm. Using the CERNET2 backbone traffic, this paper tested the performance of the algorithm. The result shows that the proposed system can detect most of IPv6 attacks.