SVM Intrusion Detection Classification Model with FA, SVDFRM

A new network intrusion detection classification model is presented, a support vector machine (SVM) based classifier is given. A factor analysis (FA) algorithm is utilized to fuse numerous related network behavior features into concise integrated features so as to reduce network data dimensions. A support vector decision function ranking method (SVDFRM) is used to calculate the contribution of network behaviors features,and then important network behaviors features are extracted. The experimental results demonstrate that this model has good dimension reduction performance, real time performance,and satisfied detection rate.