摘要
针对反向选择算法在面对大量的网络通信数据或具有多个分离特征区间网络通信数据时的无效性,提出了基于模糊控制及遗传算法的人工免疫入侵检测算法,利用模糊控制原理对抗体进行浓缩,并通过遗传算法进化种群,从而使得抗体的数量得到控制且检测效率较高。
In view of the ineffectivity of the negative selection algorithm when it faces the massive network correspondence data or the data with many separation characteristic sectors,intrusion detection algorithms of artificial immune system based on fuzzy control and genetic algo- rithm are proposed. The fuzzy control theory is ＇applied to control the quantity of the immune body, and the population is evolved by genetic algorithm for higher detection efficiency when the quantity is definite.
出处
《计算机应用与软件》
CSCD
北大核心
2008年第7期82-83,102,共3页
Computer Applications and Software
基金
湖北省教育厅重点科研项目基金(2004D006)
关键词
反向选择算法
模糊控制
遗传算法
Negative selection algorithm Fuzzy control Genetic algorithm
