Design and analysis of genetic fuzzy systems for intrusion detection in computer networks

Author:

Abadeh Mohammad Saniee,Mohamadi Hamid,Habibi Jafar

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference56 articles.

1. A method for fuzzy rules extraction directly from numerical data and its application to pattern classification;Abe;IEEE Transactions on Fuzzy Systems,1995

2. Ahmed, A. A. E., & Traore, L. (2005). Anomaly intrusion detection based on biometrics. In Proceedings of the 2005 IEEE workshop on information assurance and security united states military academy, West Point, NY.

3. Axelsson, S. (2000). Intrusion detection systems: A survey and taxonomy. Technical report no. 99-15. Department of Computer Engineering, Chalmers University of Technology, Sweden.

4. Bridges, S. M. S., & Vaughn, R. B. (2000). Fuzzy data mining and genetic algorithms applied to intrusion detection. In Proceedings of the national information systems security conference.

5. Cannady, J. (1998). Artificial neural networks for misuse detection. In National information systems security conference (pp. 368–381).

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