2009 International Conference on Computational Intelligence and Security A Preliminary Study on Why Using the Nonself Detector Set for Anomaly Detection in Artificial Immune Systems Beijing, China December 11-December 14 ISBN: 978-0-7695-3931-7
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CIS.2009.165
In artificial immune systems, the detectors in the nonself space are often adopted to detect anomaly changes, such as the negative selection algorithm and its improvements. Since the detectors in the self space can also be used to detect anomaly changes, a frequently asked question is which kind of detector sets is more efficient for a specific problem. In this paper, firstly, the advantages and disadvantages of the self detector set and the nonself detector set are briefly reviewed. Secondly, when the complete matching rule is adopted, the average time costs of employing the nonself detector set and the self detector set for anomaly detection are compared theoretically. Thirdly, simulated experiments are done, and experimental results demonstrate that the theoretical conclusion is essentially correct.
Index Terms:
self, nonself, negative selection algorithm, evolutionary negative selection algorithm
Citation:
Baoliang Xu, Wenjian Luo, Xufa Wang, "A Preliminary Study on Why Using the Nonself Detector Set for Anomaly Detection in Artificial Immune Systems," cis, vol. 1, pp.559-564, 2009 International Conference on Computational Intelligence and Security, 2009 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||