节点文献
基于粗粒度模型遗传算法在网络入侵检测系统中的应用研究
The apply research of genetic algorithm based on coarsegrained model in net-work intrusion setection system
【摘要】 网络的发展越来越迅速,各种智能型的网络入侵检测系统也越来越受到人们的重视.本文在分析了各种入侵检测系统的基础上提出了一种基于粗粒度模型遗传算法的网络入侵检测系统,让各个处理器能够并行地进行遗传算法的操作,重新合理地设计了适应度函数,使遗传“基因”的取舍和利用更加合理,使算法的性能和运行速度得到了提高,充分发挥了遗传算法在网络入侵检测系统中的应用.
【Abstract】 The development of the Internet is more and more fast, all kinds of intelligent net- work intrusion detection system(NIDS) are more recognized by people. This paper put forward a coarse-grained model genetic algorithm NIDS, let all processor can do genetic algorithm by attributed manner, at the same time, recommend an new operator, redesign a reasonable fitness function, let the use of "gene" is more reasonable, develop the performance and speed of the arithmetic, make full use of the genetic algorithm in NIDS.
【关键词】 网络入侵检测系统;
并行遗传算法;
智能;
粗粒度模型;
适应度函数;
【Key words】 net-work intrusion detection system (NIDS); collateral genetic algorithm (AG); intelligence; coarse-grained model; fitness function;
【Key words】 net-work intrusion detection system (NIDS); collateral genetic algorithm (AG); intelligence; coarse-grained model; fitness function;
【基金】 云南省教育厅应用基础研究重点项目(03Z180A)
- 【文献出处】 云南大学学报(自然科学版) ,Journal of Yunnan University(Natural Sciences Edition) , 编辑部邮箱 ,2006年S2期
- 【分类号】TP18;TP393.08
- 【被引频次】5
- 【下载频次】99