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Volume 32 Issue 11
Dec.  2010
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Zhang Xiong-Mei, Yi Zhao-Xiang, Song Jian-She, Li Jun-Shan. Research on Negative Selection Algorithm Based on Matrix Representation[J]. Journal of Electronics & Information Technology, 2010, 32(11): 2701-2706. doi: 10.3724/SP.J.1146.2009.01489
Citation: Zhang Xiong-Mei, Yi Zhao-Xiang, Song Jian-She, Li Jun-Shan. Research on Negative Selection Algorithm Based on Matrix Representation[J]. Journal of Electronics & Information Technology, 2010, 32(11): 2701-2706. doi: 10.3724/SP.J.1146.2009.01489

Research on Negative Selection Algorithm Based on Matrix Representation

doi: 10.3724/SP.J.1146.2009.01489
  • Received Date: 2009-11-20
  • Rev Recd Date: 2010-04-28
  • Publish Date: 2010-11-19
  • Due to the bottleneck of the current representation of the state space and match rule in the negative selection algorithm, a negative selection algorithm based on the matrix representation is presented, which extends the state space from the vector to the matrix. The elemental match distance is defined by introducing the matrix to denote self and nonself space, the bi-directional match rule is established. Moreover, a detector generating algorithm based on coverage rate testing is developed according to the characteristics of state space. The experimental results show that the proposed algorithm achieves better performance than the real-valued negative selection algorithm, and solves effectively the problem of the linkage of the detection rate and false rate. Furthermore, it is verified to generate more effective detectors.
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  • Forrest S, Perelson A S, Allen L, and Cherukuri R. Self-nonself discrimination in a computer[C]. Proceedings of the IEEE Symposium on Research in Security and Privacy, Los Alamos, CA, May 16-18, 1994: 202-212.[2]Ji Zhou and Dasgupta D. Applicability issues of the real-valued negative selection algorithms[C]. Proceedings of the 2006 Conference on Genetic and Evolutionary Computation Conference, Seattle, Washington, USA, July 8-12, 2006: 111-118.[3]Sarafijanovic S, Perez S, and Le Boudec J Y. Resolving FP-TP conflicting in digest-based collaborative spam detection by use of negative selection algorithm[C]. Proceedings of the Fifth Conference on Email and AntiSpam, Mountain View, California, USA, Aug. 21-22, 2008.Yi Zhao-xiang, Mu Xiao-dong, Zhang Li, and Zhao Peng. A matrix negative selection algorithm for anomaly detection[C]. Proceedings of 2008 IEEE Congress on Evolutionary Computation, Hong Kong, China, June 1-6, 2008: 978-983.[4]Ji Zhou and Dasgupta D. Revisiting negative selection algorithms[J].Evolutionary Computation.2007, 15(2):223-251[5]Gonzalez F, Dasgupta D, and Kozma R. Combining negative selection and classification techniques for anomaly detection[C]. Proceedings of 2002 IEEE Congress on Evolutionary Computation, Honolulu, May 12-17, 2002: 705-710.[6]Gonzalez F, Dasgupta D, and Gomez J. The effect of binary matching rules in negative selection[C]. Proceedings of the Conference on Genetic and Evolutionary Computation Conference(GECCO'2003), Chicago, USA, July 12-16, 2003: 195-206.Gonzalez F, Dasgupta D, and Nino L F. A randomized real-valued negative selection algorithm[C]. Proceedings of the Second International Conference on Artificial Immune Systems, Edinburgh, UK, September 1-3, 2003: 261-272.[7]Gao X Z, Ovaska S J, and Wang X. A GA-based negative selection algorithm[J]. International Journal of Innovative Computing, Information and Control, 2008, 4(4): 971-979.[8]Balthrop J, Forrest S, and Glickman M R. Revisiting LISYS: parameters and normal behavior[C]. Proceedings of the Conference on Genetic and Evolutionary Computation (GECCO'2002), New York City, USA, July 9-13, 2002: 1045-1050.[9]Ji Zhou and Dasgupta D. Augmented negative selection algorithm with variable-coverage detectors[C]. Proceedings of the Congress on Evolutionary Computation, San Diego, CA, USA. July 6-9, 2004: 1081-1088.[10]Ji Zhou and Dasgupta D. Estimating the detector coverage in a negative selection algorithm[C]. Proceedings of the Conference on Genetic and Evolutionary Computation (GECCO'2005), Washington DC, USA, June 25-29, 2005: 88-97.[11]Ji Zhou and Dasgupta D. V-detector: an efficient negative selection algorithm with probably adequate detector coverage[J].Information Sciences.2009, 179(10):1390-1406
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