Fuzzy Multi-class Support Vector Machine Based on Binary Tree in Network Intrusion Detection

Support vector machine(SVM) is sensitive to the noises and outliers in the training samples, so fuzzy support vector machine(FSVM) precede support vector machine in solving the problem of non-linearity high dimension and uncertainty. At the same time, for the practicability, the multi-class support vector machine is a good choice. In this paper, we combine the fuzzy support vector machine and multi-class support vector machine based on binary tree together, and apply it to network intrusion detection system. The experiment shows that the method improves the detection accuracy and reduces the training time.