Parameters of support vector machine directly affect the effect of network intrusion detection.In order to improve correct rate of network intrusion detection,a network intrusion detection model based on support vector machine optimized by artificial bee colony algorithm is proposed.Firstly,the parameters of support vector machine are combined together and encoded to be a source of artificial bee colony algorithm.Secondly the highest network intrusion detection rate is taken as search direction of bee colony,and optimum parameters are obtained by simulating bee colony searching nectar source.Network intrusion detection classifier is designed according to the optimal parameters.Finally,KDD CUP 99 data set is used as research object and the simulation experiment is carried out.The results show that the proposed model can improve the correct rate of network intrusion detection and reduce false detection rate,so it can obtain better network intrusion detection effect.%支持向量机参数直接影响网络入侵检测效果,为了提高入侵检测的正确率,提出了基于人工蜂群算法优化支持向量机的网络入侵检测模型.将支持向量机参数组合在一起,编码成为人工蜂群算法的蜜源,并将最高网络入侵检测率作为蜂群的搜索方向,不断模拟蜂群寻找最优蜜源的过程实现参数优化,并根据最优参数设计网络入侵检测的分类器,选择KDD CUP99数据集作为实验对象,结果表明,模型可以提高网络入侵检测的正确率,降低误报率,获得较优的网络入侵检测效果.
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