Browse > Article
http://dx.doi.org/10.7840/KICS.2011.36B.8.921

Study on the Functional Classification of IM Application Traffic using Automata  

Lee, Sang-Woo (고려대학교 컴퓨터정보학과)
Park, Jun-Sang (고려대학교 컴퓨터정보학과)
Yoon, Sung-Ho (고려대학교 컴퓨터정보학과)
Kim, Myung-Sup (고려대학교 컴퓨터정보학과)
Publication Information
The Journal of Korean Institute of Communications and Information Sciences / v.36, no.8B, 2011 , pp. 921-928 More about this Journal
Abstract
The increase of Internet users and services has caused the upsurge of data traffic over the network. Nowadays, variety of Internet applications has emerged which generates complicated and diverse data traffic. For the efficient management of Internet traffic, many traffic classification methods have been proposed. But most of the methods focused on the application-level classification, not the function-level classification or state changes of applications. The functional classification of application traffic makes possible the in-detail understanding of application behavior as well as the fine-grained control of applications traffic. In this paper we proposed automata based functional classification method of IM application traffic. We verified the feasibility of the proposed method with function-level control experiment of IM application traffic.
Keywords
Traffic classification; Automata; Application function; State transition; Payload signature;
Citations & Related Records
연도 인용수 순위
  • Reference
1 GoogleTalk, www.google.com/talk/.
2 Skype, http://www.skype.com.
3 Subhabrata Sen, Oliver Spatscheck, Dongmei Wang, "Accurate, scalable in-network identification of p2p traffic using application signatures" World Wide Web 2004, May 17-20, 2004, New York, USA.
4 L. Deri, S. Suin, "Effective traffic measurement using ntop", IEEE Communications Magazine 38, pp.138-143, 2000.
5 NateOn, http://nateonweb.nate.com/.
6 MSN, http://explore.live.com/home.
7 F. Risso, M. Baldi, O. Morandi, A. Baldini, and P. Monclus, "Lightweight, Payload-Based Traffic Classification An Experimental Evaluation," IEEE International Conference on Communications, Beijing, China, May. 19-23, pp.5869-5875, 2008.
8 Zhu Li, Ruixi Yuan, and Xiaohong Guan, "Accurate Classification of the Internet Traffic Based on the SVM Method" Proc. of the IEEE International Conference on Communications, Glasgow, Scotland, Jun. 24-28, pp.1373-1378, 2006.
9 Laurent Bernaille, Renata Teixeira, and Ismael Akodkenou, "Traffic classification on the fly" Proc. of the ACM SIGCOMM Computer Communication Review, Vol.36 No.2 April, pp. 23-26, 2006.
10 Huang. Nen-Fu, Feng. Yi-Hsuan, "Application Behavior Analysis Stateful Automata Mechanism", Journal of Computers, Vol.18, No.4, January, pp.3-14, 2008.
11 H.Liu, W.Feng, Y.Huang, X.Li, "A peer-to-peer traffic identification method using machine learning", in International Conference on Networking, Architecture, and Storage, NAS, July 29-31, pp.155-160, 2007.