Research on linear time detector generating algorithm based on negative selection model

According to negative selection model in artificial immune system, the paper mainly studies and improves initial linear time detector set generating algorithm. The algorithm constructs two arrays C and C' from two directions, then produces array D by cross product so that the detector can match more Nonself strings, and removes redundant detectors, reduces detector set scale, improves its method of design, performance analysis and testing. The results show that the improved algorithm reduces detector scale and probability of missed detection.

[1]  Dong-Wook Lee,et al.  Intrusion detection system using various detectors , 2003, SMC'03 Conference Proceedings. 2003 IEEE International Conference on Systems, Man and Cybernetics. Conference Theme - System Security and Assurance (Cat. No.03CH37483).

[2]  Alan S. Perelson,et al.  Self-nonself discrimination in a computer , 1994, Proceedings of 1994 IEEE Computer Society Symposium on Research in Security and Privacy.

[3]  Paul Helman,et al.  An immunological approach to change detection: algorithms, analysis and implications , 1996, Proceedings 1996 IEEE Symposium on Security and Privacy.

[4]  Simon M. Garrett,et al.  How Do We Evaluate Artificial Immune Systems? , 2005, Evolutionary Computation.

[5]  Peter J. Bentley,et al.  Immune Memory in the Dynamic Clonal Selection Algorithm , 2002 .

[6]  Leandro Nunes de Castro,et al.  The Clonal Selection Algorithm with Engineering Applications 1 , 2000 .