关键词: 遗传算法, 粒子群算法, 入侵检测, 聚类, 进化, 最优化

Abstract: Concerning the clustering optimization in intrusion detection, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) were used to optimize clustering and comparative analysis was also completed. In this analysis, binary code was adopted and elimination criterion took the account of the maximum number of iteration and the quality of convergence. Fitness function which combines the characteristic of jnter-cluster distance and intra-cluster distance was defined. Finally, the experiments with KDDCUP 1999 data set using Matlab 6.5 tools show that PSO is superior to GA in the value and speed of fitness function convergence.

Key words: genetic algorithm, particle swarm optimization, intrusion detection, clustering, evolution, optimization