计算机工程与应用 ›› 2008, Vol. 44 ›› Issue (2): 149-151.

• 网络、通信与安全 • 上一篇    下一篇

基于PSO模糊聚类算法的入侵检测研究

张凌杰1,褚学征2,张国辉2   

  1. 1.华北水利水电学院 水利职业学院 信息工程系,郑州 450008
    2.华中科技大学 数字制造装备与技术国家重点实验室,武汉 430074
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2008-01-11 发布日期:2008-01-11
  • 通讯作者: 张凌杰

Research intrusion detection based on PSO fuzzy clustering algorithm

ZHANG Ling-jie1,CHU Xue-zheng2,ZHANG Guo-hui2   

  1. 1.Dept. of Information Engineering,North China University of Water Conservancy and Electric Power,Zhengzhou 450008,China
    2.State Key Lab. of Digital Manufacturing Equipment and Tech.,Huazhong Univ. of Sci. and Tech.,Wuhan 430074,China
  • Received:1900-01-01 Revised:1900-01-01 Online:2008-01-11 Published:2008-01-11
  • Contact: ZHANG Ling-jie

摘要: 提出一种将粒子群优化(PSO)和FCM 相结合的聚类算法PSOFCA对入侵检测系统进行研究,克服FCM方法自身对初始值敏感、容易陷入局部最优等问题。最后对实验数据进行仿真实验,并将实验结果与其他算法结果相比较,结果表明PSOFCA算法在入侵检测中能获得较好的检测能力。

关键词: 入侵检测, 模糊均值算法, 粒子群优化算法

Abstract: A Particle Swarm Optimization-based Fuzzy Clustering Algorithms(PSOFCA) is proposed to improve some defects of sensitivity to the initial data,getting in the local optimization and so on about Fuzzy C-Means in intrusion detection system.Finally,the empirical datum is simulated,and the computational results compares with other algorithm results.The compared results show a better detective ability than other algorithms by the data obtained in experiment.

Key words: intrusion detection, FCM, PSO