TY - GEN
T1 - Generating an approximately optimal detector set by evolving random seeds
AU - Zhang, Jie
AU - Luo, Wenjian
AU - Xu, Baoliang
PY - 2009
Y1 - 2009
N2 - 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.
AB - 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.
KW - Detector generation algorithm
KW - Genetic algorithm
KW - Negative selection algorithm
KW - Random seed
UR - https://www.scopus.com/pages/publications/77950549277
U2 - 10.1109/DASC.2009.117
DO - 10.1109/DASC.2009.117
M3 - 会议稿件
AN - SCOPUS:77950549277
SN - 9780769539294
T3 - 8th IEEE International Symposium on Dependable, Autonomic and Secure Computing, DASC 2009
SP - 162
EP - 168
BT - 8th IEEE International Symposium on Dependable, Autonomic and Secure Computing, DASC 2009
T2 - 8th IEEE International Symposium on Dependable, Autonomic and Secure Computing, DASC 2009
Y2 - 12 December 2009 through 14 December 2009
ER -