%0 Journal Article
%T Principal component analysis andsupport vector machine based anomaly detection<br>基于主元分析和支持向量机的异常检测*
%A REN Xun-yi
%A WANG Ru-chuan
%A KONG Qiang
%A <br>任勋益
%A 王汝传
%A 孔强
%J 计算机应用研究
%D 2009
%I 
%X To improve the efficiency of anomaly detection,this paper proposed one principal component analysis (PCA) and support vector machine (SVM) based intrusion detection method. Employed PCA to reduce intrusion data,SVM train the reduced data,and constructed one anomaly detection model to detect the test data. Kddcup'99 data based experiments,40 features is reduced to 15,and 22 features is reduced to 5 features. Experimental results on these data show presented method have strong general ability and spend less t...
%K principal component analysis
%K support vector machine
%K anomaly detection<br>主元分析
%K 支持向量机
%K 异常检测
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=681B04E020C66F9EB6E0E307606CFE12&yid=DE12191FBD62783C&vid=96C778EE049EE47D&iid=DF92D298D3FF1E6E&sid=3145500BBCE659D1&eid=2ECC9FC4A0E59C00&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=12