An Evaluation of Negative Selection in an Artificial Immune System for Network Intrusion Detection (2001)
| Venue: | Proceedings of the Genetic and Evolutionary Computation Conference (GECCO |
| Citations: | 49 - 1 self |
BibTeX
@INPROCEEDINGS{Kim01anevaluation,
author = {Jungwon Kim and Peter J. Bentley},
title = {An Evaluation of Negative Selection in an Artificial Immune System for Network Intrusion Detection},
booktitle = {Proceedings of the Genetic and Evolutionary Computation Conference (GECCO},
year = {2001},
pages = {1330--1337},
publisher = {Morgan Kaufmann}
}
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Abstract
This paper investigates the role of negative selection in an artificial immune system (AIS) for network intrusion detection. The work focuses on the use of negative selection as a network traffic anomaly detector. The results of the negative selection algorithm experiments show a severe scaling problem for handling real network traffic data. The paper concludes by suggesting that the most appropriate use of negative selection in the AIS is as a filter for invalid detectors, not the generation of competent detectors. 1
