计算技术与自动化Issue(2)：95-99,5.
改进蚁群算法优化支持向量机的网络入侵检测
Network Intrusion Detection Model Based on Support Vector Machine and Improved and Colony Optimiza Tion Algorithm
摘要
Abstract
In order to solve parameters optimization problem for support vector machine in network intrusion detection, this paper proposed a network intrusion detection model based on support vector machine,whose parameters were optimized by the improved ant colony optimization algorithm.Firstly,the node of ant colony search path represented the parameters of support vector machine,network intrusion detection rate was taken as the goal function,and then global optimization and feedback mechanism of ant colony optimization algorithm were used to find the optimal path,and Gauss mutation was intro-duced to overcome local minima,and the nodes of the optimal path were connected to form the optimal parameters of support vector machine and to establish the optimal network intrusion detection model,and the simulation experiments were carried out on the KDD9 9 dataset.The simulation results show that the proposed model not only accelerates network intrusion de-tection rate,but also improves intrusion detection rate,compared with reference models.关键词
网络入侵/蚁群优化算法/支持向量机/参数优化Key words
intrusion detection/ant colony optimization algorithm/support vector machine/parameters opti-mization分类
信息技术与安全科学引用本文复制引用
王雪松,梁昔明..改进蚁群算法优化支持向量机的网络入侵检测[J].计算技术与自动化,2015,(2):95-99,5.基金项目
国家自然科学基金资助项目(60874070) （60874070）
广东省教育厅项目(2010tjk446) （2010tjk446）
