DocumentCode :
2095602
Title :
A P2P Traffic Classification Method Based on SVM
Author :
Xusheng, Zhou
Author_Institution :
Hunan Univ. Of Technol. Zhuzhou, Zhuzhou, China
Volume :
2
fYear :
2008
fDate :
20-22 Dec. 2008
Firstpage :
53
Lastpage :
57
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 that based on the statistical theory to classifies the different P2P traffic application. Mainly research on four kind of network traffic classification, in document sharing BitTorrent, in media flows PPLive, in network telephone Skype, in immediate communication MSN. Introduced P2P traffic classification overall framework based on the SVM. Described how gain the traffic sample and the processing method. And introduced the experimental results and constructs the traffic classifier. The experimental result confirmed the validity of proposed method; average precise rate is 92.38%.
Keywords :
peer-to-peer computing; statistical analysis; support vector machines; telecommunication traffic; P2P network traffic classification; P2P traffic classification method; SVM; document sharing BitTorrent; immediate communication MSN; media flows PPLive; network telephone Skype; network traffic statistical characteristic; statistical theory; Arithmetic; IP networks; Internet; Machine learning; Protocols; Support vector machine classification; Support vector machines; TCPIP; Telecommunication traffic; Traffic control; Network traffic classification; P2P; Support vector machine; Traffic feature;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Computational Technology, 2008. ISCSCT '08. International Symposium on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-3746-7
Type :
conf
DOI :
10.1109/ISCSCT.2008.368
Filename :
4731570
Link To Document :
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