摘要
针对蚁群聚类算法存在容易出现停滞现象和过早地收敛于局部最优解的问题,提出一种改进的蚁群聚类入侵检测算法.通过改进蚂蚁搜索解的方法,来改善蚁群算法易于过早地收敛于非最优解的缺陷.使用KDD99作为入侵检测数据集进行仿真实验,结果表明,改进的蚁群聚类算法能有效提高入侵检测的检测率和降低误检率.
Aimed at the problems in ant colony clustering such as ready at stagnation phenomenon and early converging to local optima, an intrusion detection algorithm was presented based on improved ant colony clustering. By means of improving the method for ant searching solution, the early converging to local optimum solution was avoided. The KDD 99 intrusion detection data were used to conduct simulation experiment and the simulation results show that the improved ant colony clustering could effectively improve the detection rate of intrusion detection and reduce the false detection rate.
出处
《兰州理工大学学报》
CAS
北大核心
2013年第5期85-88,共4页
Journal of Lanzhou University of Technology
关键词
聚类分析
蚁群聚类算法
信息素
检测率
误检率
clustering analysis
ant colony clustering algorithm
pheromone
detection rate
false alarm rate
