%0 Journal Article
%T Method for P2P traffic classification based on decision-tree model<br>基于决策树模型的P2P流量分类方法
%A CHEN Yun-jing
%A ZHANG Yun
%A CHEN Jing-tao
%A <br>陈云菁
%A 张赟
%A 陈经涛
%J 计算机应用研究
%D 2009
%I 
%X P2P traffic has become one of the most significant portions of the network traffic. Accurate identification of P2P traffic makes great sense for efficient network management and reasonable utility of network resources. In recent years, P2P traffic classification using machine learning has been a new direction in traffic identification. This paper proposed a new method based on decision-tree model, using C4.5 and P2P traffic characteristic. The experiments show this method can effectively avoid the instability of P2P traffic distribution change. Compared with SVM and NBK method, the average of classified precision can increase at least 3.83 percentage points.
%K P2P
%K traffic characteristic
%K decision-tree
%K traffic classification
%K C4
%K 5<br>对等网
%K 流量特征
%K 决策树
%K 流量分类
%K C4.5
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=72ECCD036FB948150B2951FDE52F4ECB&yid=DE12191FBD62783C&vid=96C778EE049EE47D&iid=59906B3B2830C2C5&sid=0657953EE285B382&eid=D766F1810FF6E08D&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=13