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Proceedings Paper

Distributed intrusion detection system based on fuzzy rules
Author(s): Peili Qiao; Jie Su; Yahui Liu
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Paper Abstract

Computational Intelligence is the theory and method solving problems by simulating the intelligence of human using computer and it is the development of Artificial Intelligence. Fuzzy Technique is one of the most important theories of computational Intelligence. Genetic Fuzzy Technique and Neuro-Fuzzy Technique are the combination of Fuzzy Technique and novel techniques. This paper gives a distributed intrusion detection system based on fuzzy rules that has the characters of distributed parallel processing, self-organization, self-learning and self-adaptation by the using of Neuro-Fuzzy Technique and Genetic Fuzzy Technique. Specially, fuzzy decision technique can be used to reduce false detection. The results of the simulation experiment show that this intrusion detection system model has the characteristics of distributed, error tolerance, dynamic learning, and adaptation. It solves the problem of low identifying rate to new attacks and hidden attacks. The false detection rate is low. This approach is efficient to the distributed intrusion detection.

Paper Details

Date Published: 17 April 2006
PDF: 7 pages
Proc. SPIE 6241, Data Mining, Intrusion Detection, Information Assurance, and Data Networks Security 2006, 62410F (17 April 2006); doi: 10.1117/12.665177
Show Author Affiliations
Peili Qiao, Harbin Univ. of Science and Technology (China)
Beijing Univ. of Information and Technology (China)
Jie Su, Harbin Univ. of Science and Technology (China)
Beijing Univ. of Information and Technology (China)
Yahui Liu, Harbin Univ. of Science and Technology (China)
Beijing Univ. of Information and Technology (China)


Published in SPIE Proceedings Vol. 6241:
Data Mining, Intrusion Detection, Information Assurance, and Data Networks Security 2006
Belur V. Dasarathy, Editor(s)

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