计算机工程与应用 ›› 2008, Vol. 44 ›› Issue (14): 122-126.

• 网络、通信、安全 • 上一篇    下一篇

一种基于SVM的P2P网络流量分类方法

邓 河1,阳爱民1,2,刘永定1   

  1. 1.湖南工业大学 计算机与通信学院,湖南 株洲 412008
    2.国防科技大学 计算机学院,长沙 410073
  • 收稿日期:2007-08-27 修回日期:2007-10-25 出版日期:2008-05-11 发布日期:2008-05-11
  • 通讯作者: 邓 河

P2P traffic classification method based on SVM

DENG He1,YANG Ai-min1,2,LIU Yong-ding1   

  1. 1.School of Computer and Communication,Hunan Industry University,Zhuzhou,Hunan 412008,China
    2.School of Computer,National University of Defense Technology,Changsha 410073,China
  • Received:2007-08-27 Revised:2007-10-25 Online:2008-05-11 Published:2008-05-11
  • Contact: DENG He

摘要: 提出一种基于SVM的P2P网络流量分类的方法。这种方法利用网络流量的统计特征和基于统计理论的SVM方法,对不同应用类型的P2P网络流量进行分类研究。主要对文件共享中的BitTorrent,流媒体中的PPLive,网络电话中的Skype,即时通讯中的MSN 4种P2P网络流量进行分类研究。介绍了基于SVM的P2P流量分类的整体框架,描述了流量样本的获取及处理方法,并对分类器的构建及实验结果进行了介绍。实验结果验证了提出方法的有效性,平均分类精确率为92.38%。

关键词: 网络流量分类, 流量特征, SVM, P2P

Abstract: A method to realize the P2P network traffic classification based on the SVM is proposed.This method uses the network traffic statistical characteristic and SVM method based on the statistical theory to classify the different P2P traffic application.Mainly research focus on four kinds of network traffic classification,which are document sharing BitTorrent,media flows PPLive,network telephone Skype and immediate communication MSN.Introduce P2P traffic classification overall framework based on the SVM,describe how gain the traffic sample and the processing method,introduce the experimental result and construct the traffic classifier.The experimental results confirm the validity of proposed method,the average precise rate is 92.38%.

Key words: network traffic classification, traffic feature, Support Vector Machine(SVM), P2P