计算机工程与应用2011，Vol.47Issue(12)：90-92,96,4.DOI:10.3778/j.issn.1002-8331.2011.12.027
基于自适应蚁群聚类的入侵检测
Adaptive ant colony clustering method for intrusion detection
摘要
Abstract
For the problem that partial data partition is not accurate enough in clustering results of ant colony clustering algorithm, an improved adaptive chaotic ant colony clustering algorithm based on information entropy is proposed. The algorithm measures the evolutive degree by optimizing the population information entropy,and adjusts the pheromone update strategy adaptively. It uses the chaotic search operator to search better solution near current global optimal solution at the end of each iteration.With progress of the algorithm,search range of the chaotic operator is gradually reduced so that chaotic operator avoids falling into local optimum in the initial period and improves search precision in the later period of ant colony search. This leads to better clustering results.Using the KDD Cup 1999 intrusion detection data, simulation results show that the clustering effect improves significantly,and can effectively improve the detection rate of intrusion detection and reduce the false detection rate.关键词
蚁群聚类/聚类分析/入侵检测/网络安全Key words
ant colony clustering/cluster analysis/intrusion detection/network security分类
信息技术与安全科学引用本文复制引用
杨照峰,樊爱京,樊爱宛..基于自适应蚁群聚类的入侵检测[J].计算机工程与应用,2011,47(12):90-92,96,4.基金项目
平顶山学院青年科研基金项目(No.2008041). （No.2008041）
