%0 Journal Article
%T Intrusion Detection Based on Hybrid CatfishPSO-LSSVM Feature Selection<br>基于混合CatfishPSO-LSSVM 特征选择的入侵检测
%A WANG Wei-Ping
%A TANG Zhi-Xu
%A <br>王卫平
%A 唐志煦
%J 计算机系统应用
%D 2012
%I 
%X The main issue of Intrusion detection systems is large computation,feature selection was introduced to solve the problem.According to the shortcomings of existing methods,this paper uses improved Particle Swarm Optimization to search optimal feature subset,proposes a feature selection method based on hybrid CatfishPSO and Least Square Support Vector Machine,uses combined CatfishBPSO and CatfishPSO to select feature subset and optimize the parameters of LSSVM simultaneously,and build a Intrusion detection model based on the feature selection method above.Experiments on KDD Cup 99 show that the model has a good detection performance.
%K feature selection
%K particle swarm optimization
%K least square support vector machine
%K intrusion detection<br>特征选择
%K 粒子群算法
%K 最小二乘支持向量机
%K 入侵检测
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=D4F6864C950C88FFCE5B6C948A639E39&aid=57C6AD9B0ADA05371E6A609D250DA158&yid=99E9153A83D4CB11&vid=659D3B06EBF534A7&iid=CA4FD0336C81A37A&sid=CD775AE9DDBD7B53&eid=CFAC5CB624A41AFD&journal_id=1003-3254&journal_name=计算机系统应用&referenced_num=0&reference_num=9