A self-adaptive negative selection approach for anomaly detection

Proceedings of the 2004 Congress on Evolutionary Computation, CEC2004

Volumn 2, Issue , 2004, Pages 1561-1568

  Gonzalez, Luis J ^a   Cannady, James ^a  

^a NOVA SOUTHEASTERN UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AFFINITY EVOLUTION; ALTERNATIVE HYPOTHESIS; NSMUTATION; SELF-ADAPTIVE NEGATIVE SELECTION ALGORITHM;

COMPUTATIONAL COMPLEXITY; COMPUTER SCIENCE; EVOLUTIONARY ALGORITHMS; INFORMATION TECHNOLOGY; PARAMETER ESTIMATION; PATTERN RECOGNITION; PROBABILITY DISTRIBUTIONS; RANDOM PROCESSES;

ADAPTIVE SYSTEMS;

EID: 4344698935     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (10)

1. Ayara, Timmis, de Lemos, de Castro, L., & Duncan, R. (2002). Negative selection: How to generate detectors. In Proceedings of ICARIS (International Conference on Artificial Immune Systems) pp. 89-98.
2. Chellapilla, K., & Fogel, D. B. (1997). Exploring self-adaptive methods to improve the efficiency of generating approximate solutions to traveling salesman problems using evolutionary programming. Proceedings of the 6th International Conference on Evolutionary Programming pp. 361 - 371. Indianapolis, Indiana: Springer.
3. D'haeseleer, P., Forrest, S., & Helman, P. (1996). An immunological approach to change detection: Algorithms, analysis and implications. IEEE Symposium on Security and Privacy.
4. Eiben, A., Hinterding, R., & Michalewicz, Z. (1999). Parameter control in evolutionary algorithms. IEEE Transactions on Evolutionary Computation, 3, pp. 124-141.
5. Forrest, S., Hofmeyr, S. A., & Somayi, A. (1997). Computer immunology. Communications of the ACM, 40, (10), pp. 88-96.
6. Forrest, S., Perelson, A. S., Allen, L., & Cherukuri, R. (1994). Self-nonself discrimination in a computer. In Proceedings of the 1994 IEEE Symposium on Research in Security and Privacy pp. 202-212.
7. Gonzalez, F., & Dasgupta, D. (2002). An immunogenetic technique to detect anomalies in network traffic. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO) pp. 1081-1088.
8. Hinterding, R., Michalewicz, Z., & Peachey, T. C. (1996). Self-adaptive genetic algorithm for numeric functions. Parallel Problem Solving from Nature pp. 420-429. Springer.
9. Kim, J., & Bentley, P. J. (2001). Evaluating negative selection in an artificial immune system for network intrusion detection. Genetic and Evolutionary Computation Conference 2001 (GECCO - 2001), San Francisco pp. 1330-1337.
10. Wierzchon, S. (2000). Generating optimal repertoire of antibody strings in an artificial immune system. Intelligent Information Systems pp. 119-133. Advances in Soft Computing Series of Physica-Verlag/Springer Verla.