%0 Journal Article
%T P2P streaming identification method based on endpoint features<br>基于端点特征的P2P流媒体识别方法
%A CHEN Wei
%A LAN Ju-long
%A ZHANG Jian-hui
%A <br>陈　伟
%A 兰巨龙
%A 张建辉
%J 计算机应用研究
%D 2012
%I 
%X Due to the great differences in statistical features between control flows and data flows, the performance of DFIdeep flow inspection in the identification of P2P streaming traffic is not so ideal. Enlightened by the idea of DFI, this paper proposed a P2P streaming identification method based on endpoint features. This method chose six features aimed at net-endpoint so as to identify P2P streaming traffic using machine learning. Experimental results show that this method performs better in overall accuracy over DFI, and it can also be used in real-time P2P streaming traffic identification.
%K P2P streaming
%K machine learning
%K flow
%K endpoint<br>P2P流媒体
%K 机器学习
%K 流
%K 端点
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=31780116840884785570E3A741AE32C2&yid=99E9153A83D4CB11&vid=771469D9D58C34FF&iid=DF92D298D3FF1E6E&sid=B4133463C310C9AB&eid=66B847606A3FBCE0&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=13