An Improved SVM Method for Internet Traffic Classification

摘要：

　　With the development of network technology,network traffic classification technology plays an increasingly important role in network service and management.In terms of classify traffic flows,Support vector machine(SVM)has shown that more effective than traditional methods.However,classification accuracy will have different performance due to different features.Therefore,we proposed a new method to choose the best combination of features.Moreover,a novel SVM is proposed,which can eliminate the influence of noise on classification accuracy.Experimental results show that the method proposed in this paper has a better and more stable performance.

关键词： support vector machine (SVM) features select network traffic classification classification accuracy

作者: Siyuan Wu Dengyin Zhang Fei Ding Min Zhang

作者单位: Institute of Internet of Things,Nanjing University of Posts and Telecommunications University,Xinmofan Road,Nanjing,China

会议类型: 国际会议

会议名称: 2018 2nd International Conference on Systems,Computing,and Applications (SYSTCA 2018) 2018第二届系统、计算和应用国际会议

会议地点: 深圳

会议语种:英文

页码: 432-437

在线出版日期: 2018-10-27（万方平台首次上网日期，不代表论文的发表时间）