Dynamic Clone Selection Algorithm Based on Genetic Algorithm for Intrusion Detection
Aimed at the problem of lower detection efficiency of detector set generated by traditional dynamic clone selection algorithm, a dynamic clone selection algorithm based on genetic algorithm is proposed. A new method of appetency calculation is introduced and the memory detector set is optimized based on genetic algorithm. An intrusion detection system based on this algorithm is designed. With KDD Cup 1999 dataset, it is proved that this algorithm achieves higher detection rate and lower missed detection rate.
intrusion detection dynamic clone selection fitness memory detector negative selection
Wang Baoyi Zhang Feng
School of Computer Science and Technology, North China Electric Power University (NCEPU) Baoding 071003, China
国际会议
重庆
英文
137-140
2009-12-25（万方平台首次上网日期，不代表论文的发表时间）