计算机技术与发展Issue(12)：138-141,4.DOI:10.3969/j.issn.1673-629X.2014.12.032
粒子群模糊聚类算法在入侵检测中的研究
Research on Fuzzy Clustering Algorithm Based on PSO in IDS
摘要
Abstract
Fuzzy C-means clustering algorithm is widely used in intrusion detection currently.But this algorithm has some shortcomings that is difficult to determine the clustering number and easy to fall into the local minimum when iterating,which can affect the accuracy of intrusion detection system.In view of this,propose a fuzzy clustering algorithm based on PSO algorithm,through introducing the PSO global search ability and particle inverting operation,avoid the problem of falling into local minimum and premature convergence.Final-ly,the experimental results show that the new algorithm has higher detection rate than the C-mean clustering algorithm,which can be well applied to intrusion detection systems.关键词
模糊C均值聚类算法/粒子群算法/模糊聚类/入侵检测Key words
FCM algorithm/PSO algorithm/fuzzy cluster/IDS分类
信息技术与安全科学引用本文复制引用
李锋..粒子群模糊聚类算法在入侵检测中的研究[J].计算机技术与发展,2014,(12):138-141,4.基金项目
2012年广东省高等学校教学质量与教学改革工程省级精品资源共享课程（粤教高函[2013]13号）；2013年广东省高职教育教学指导委员会教学教改项目（xxjs-2013-2001）；2013年广东省高职高专校长联席会议教改项目 （）
