计算机工程与科学2018，Vol.40Issue(2)：261-267,7.DOI:10.3969/j.issn.1007-130X.2018.02.010
免疫入侵检测多目标优化克隆选择算法研究
A multi-objective optimization based clonal selection algorithm in immune invasion detection
摘要
Abstract
In immune invasion detection theory,clonal selection is the key todetectorevolution.The traditional clonal selection algorithm,which compares the cumulative value of affinitybetween samples to select samples,has lower time complexity,but also causes high overlap of detectors and affects the iterative efficiency.This paper transforms the selection and evolution of detector individuals into the solving process of pareto optimal solution,and proposes the detector clone selection algorithm based on multiobjective optimization theory.Experiments show that the algorithm can significantly improve the detection range of each population in the evolutionary process,reduce the number of memory detectors and improve the detection rate of the detection system.关键词
免疫入侵检测/多目标优化/记忆检测器/克隆选择Key words
immune intrusion detection/multi-objective optimization/memory detector/clonal selection分类
信息技术与安全科学引用本文复制引用
张凤斌,范学林,席亮..免疫入侵检测多目标优化克隆选择算法研究[J].计算机工程与科学,2018,40(2):261-267,7.基金项目
国家自然科学基金(.61172168) （.61172168）
黑龙江省教育厅科学技术研究项目(12541130) （12541130）
黑龙江省普通本科高等学校青年创新人才培养计划 （）
