燕山大学学报Issue(2)：124-128,147,6.DOI:10.3969/j.issn.1007-791X.2013.02.006
一种改进粒子群优化算法在入侵检测中的应用
Application of improved particle swarm optimization algorithm in intrusion detection
卢辉斌 1周绯菲 2孙金伟1
作者信息
- 1. 燕山大学 信息科学与工程学院，河北 秦皇岛066004
- 2. 交通运输部管理干部学院 计算机系，北京101601
- 折叠
摘要
Abstract
Aiming at the problems of premature convergence and easy to fall into local optimum value of existing particle swarm optimization (PSO) algorithms, a new collaborative particle swarm optimization (CPSO) algorithm is proposed. CPSO algorithm has two subgroups, one subgroup is used for global search always keep particle diversity, the other one is used for local search guarantee search precision. So precise search is realized nearly the global optimal value by mutual cooperation. Finally, the proposed algorithm applied to intrusion detection based on dynamic cluster. Through the optimization of clustering radius and clustering threshold , the training data is classified as normal and abnormal clustering. Then test data is used to attack detection. The results show that CPSO algorithm has a marked improvement in performance over the traditional PSO algorithm and improved mutation particle swarm (MPSO) algorithm.关键词
粒子群优化/协同粒子群/动态聚类/入侵检测Key words
PSO/premature convergence/collaborative particle swarm/dynamic cluster/intrusion detection分类
信息技术与安全科学引用本文复制引用
卢辉斌,周绯菲,孙金伟..一种改进粒子群优化算法在入侵检测中的应用[J].燕山大学学报,2013,(2):124-128,147,6.
