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MSN4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%。
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 fbeus 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%,
出处
《计算机工程与应用》
CSCD
北大核心
2008年第14期122-126,共5页
Computer Engineering and Applications
基金
中国博士后科学基金(the China Postdoctoral Science Foundation under Grant No.20070410299)
湖南省教育厅资助科研课题(the Research Project of Department of Education of Hunan Province,China under Grant No.07B014)
关键词
网络流量分类
流量特征
SVM
P2P
network traffic classification
traffic feature
Support Vector Machine（SVM）
P2P
