Traffic classification based on support vector machine
基于支持向量机的流量分类方法

In order to solve the problems in current work,such as low accuracy,limited application region or high computation complexity,support vector machine(SVM) was applied to categorize traffic by application.The work capitalized on public hand-classified network dataset and used it to train and tested the supervised SVM traffic classifier.The improved accuracy of refined variants of this classifier was further illustrated,and the variants included the size of training dataset,kernel functions and penalty factors.The results indicate that it can achieve over 98% accuracy on per-flow classification with the SVM classifier.