A Novel P2P Traffic Identification Scheme Based on Support Vector Machine Fuzzy Network

被引:4
作者
Gao, Zhong [1 ]
Lu, Guanming [1 ]
Gu, Daquan [2 ]
机构
[1] Nanjing Univ Posts & Telecommun, Coll Telecommun & Informat Engn, Nanjing, Peoples R China
[2] PLA Univ Sci & Technol, Coll Meteorol, Nanjing, Peoples R China
来源
WKDD: 2009 SECOND INTERNATIONAL WORKSHOP ON KNOWLEDGE DISCOVERY AND DATA MINING, PROCEEDINGS | 2009年
关键词
D O I
10.1109/WKDD.2009.116
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
with the rapid development of the Internet, the P2P (Peer-to-Peer) technology which is characterized by no utilization of any servers with centralized functions has kept advancing apace. However, how to improve the accuracy of the P2P traffic identification efficiently is still a challenging problem. In this paper, we propose a new approach for P2P traffic identification, which uses a novel Support Vector Machine Fuzzy Network (SVMFN) to make the identification more suitable and accurate in various network environments with different rates. The experimental results show that the generalization performance and the accuracy of identification are improved significantly compared to that of the traditional methods, and adapt to engineering applications.
引用
收藏
页码:909 / +
页数:2
相关论文
共 9 条
[1]   A tutorial on Support Vector Machines for pattern recognition [J].
Burges, CJC .
DATA MINING AND KNOWLEDGE DISCOVERY, 1998, 2 (02) :121-167
[2]  
CRISTIANINI N, 2000, INTRO SUPPORT VECTOR, P132
[3]  
HSU CW, 2003, PRACTICAL GUIDE SUPP, P345
[4]  
Karagiannis T., 2004, GLOBECOM
[5]  
Karagiannis T., 2004, The 4th ACM SIGCOMM conference on Internet measurement, P121
[6]  
Kim MS, 2003, LECT NOTES COMPUT SC, V2867, P55
[7]  
SEN S, 2004, ACCURATE SCALABLE IN
[8]  
Vapnik Vladimir, 1999, The nature of statistical learning theory
[9]  
WESTON J, 1999, P 7 EUR S ART NEUR N, P431