IJEM Vol. 2, No. 4, 29 Aug. 2012
Cover page and Table of Contents: PDF (size: 1037KB)
Full Text (PDF, 1037KB), PP.1-8
Views: 0 Downloads: 0
Traffic identification, P2P, SVM
With the rapid development of the Internet, P2P has become the main network application in the Internet, which consumes most of the network resources. Accurately identifying and making control of the P2P traffic is of great significance. As a mature classification theory, support vector machine (SVM) algorithm is suitable for P2P traffic identification. This paper proposes a SVM based P2P flow identification method, adopting multidimensional flow properties as the input vector, which can improve the P2P flow classification accuracy. Analysis shows this method has many advantages over the other methods.
Yao Zhao,Zhixin Wei,Hua Zou,"SVM Based P2P Traffic Identification Method With Multiple Properties", IJEM, vol.2, no.4, pp.1-8, 2012. DOI: 10.5815/ijem.2012.04.01
[1]Sen, S.,Jia Wang. Analyze P2P traffic across large network. Networking, IEEE/ACM Transactions on Volume: 12, Issue: 2.2004.
[2]Ohzahata S ,Hagiwara Y, Terada M ,et al ,A Traffic Identification Method and Evaluations for a Pure P2P Application[M] .Lecture Notes in Computer Science ,2005.
[3]Hongbo Jiang, Andrew W. Moore, Zihui Ge, Shudong Jin, Jia Wang. Aug. self-learning IP traffic classification based on statistical flow characteristics. Proceedings of the 2007 SIGCOMM workshop on Internet network management, 2007.
[4]Kompella S,Wieselthier, J.E., Ephremides, A., Sherali, H.D. cross-layer peer-to-peer traffic identification and optimization based on active networking. Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks and Workshops, 2008.
[5]Nello C, John S T. An introduction to Support Vector Machines and other Kernel-based Learning Methods. Cambridge University Press, 2004.
[6]Gabriel Gómez Sena, Pablo Belzarena, Early traffic classification using Support Vector Machines, Proceeding LANC '09 Proceedings of the 5th International Latin American Networking Conference,2009
[7]Rui Wang, Yang Liu, Yue-xiang Yang, Hai-long Wang. A new method for P2P Traffic Identification Based on Support vector Machine. AIML 06 International Conference, 13 - 15 June 2006, Sharm El Sheikh, Egypt
[8]R. Yuan Z. Li, X. Guan, Accurate classification of the internet traffic based on the SVM method, in: Proceedings of the 42th IEEE International Conference on Communications (ICC 2007), June 2007
[9]PAN S R,FU M ,SHI C Q. Application of the Supporting Vector Machine in P2P Traffic Identification, COMPU TER EN GINEERING & SCIENCE, Vol132 ,No12 ,2010
[10]Chih-Chung Chang and Chi-Jen Lin. LIBSVM-A Library for support Vector Machines.http://www.csie.ntu.tw/~cjlin/libsvm/