2009 Eighth IEEE International Conference on Dependable, Autonomic and Secure Computing Generating an Approximately Optimal Detector Set by Evolving Random Seeds Chengdu, China December 12-December 14 ISBN: 978-0-7695-3929-4
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/DASC.2009.117
The detector generation algorithm is the core of a Negative Selection Algorithm (NSA). In most previous work, the NSAs generate the detector set randomly, which cannot guarantee to obtain an efficient detector set. To generate an approximately optimal detector set, in this paper, a novel detector generation algorithm for the Real-Valued Negative Selection Algorithm (RNSA) is proposed. The proposed algorithm, named as the EvoSeedRNSA, adopts a genetic algorithm to evolve the random seeds to obtain an optimized detector set. The experimental results demonstrate that the EvoSeedRNSA has a better performance.
Index Terms:
Negative Selection Algorithm, Genetic Algorithm, Detector Generation Algorithm, Random Seed
Citation:
Jie Zhang, Wenjian Luo, Baoliang Xu, "Generating an Approximately Optimal Detector Set by Evolving Random Seeds," dasc, pp.162-168, 2009 Eighth IEEE International Conference on Dependable, Autonomic and Secure Computing, 2009 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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