An introduction to support Vector Machines: and other kernel-based learning methods
An introduction to support Vector Machines: and other kernel-based learning methods
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This paper presents a new network intrusion detection classification model based on the Support vector machine (SVM). In this model, the factor analysis (FA) algorithm converted a large number of related network behaviors features into concise integrated features, and the support vector decision function ranking method (SVDFRM) calculated the contribution of network behaviors features. Then some important network behaviors features were extracted and network behaviors were classified consequently. The experimental results show that the detection rate and the real-time of this classification model are satisfying.