摘要
本文提出了一种基于相似度聚类与免疫危险理论的入侵检测方法.该方法将相似度聚类分析方法应用在入侵检测的分类器产生阶段,既生成了用于免疫算法的检测器,又过滤了正常数据,减少了需检测的数据量,改进了检测方法,提高了系统的检测效率和检测能力.
A new method of intrusion detection based on the similarity cluster and the immune danger theory is presented. The similarity cluster will be applied to the stage of the intrusion detection classifier produced, the method has not only produced the detectors of the intrusion detection and filtered the normal data, but also reduced the amount of the detections, and improved the detection methods, efficiency and capability.
出处
《宁夏师范学院学报》
2008年第6期54-57,共4页
Journal of Ningxia Normal University
基金
宁夏教育厅高校项目(2006(237)号)
关键词
免疫危险理论
入侵检测
相似度聚类
Immune danger theory
Intrusion detection
Similarity cluster
