Real-time Identification of Skype Application Traffic using Behavior Analysis 


Vol. 36,  No. 2, pp. 131-140, Feb.  2011


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  Abstract

As the number of Internet users and applications is increasing, the importance of application traffic classification is growing more and more for efficient network management. While a number of methods for traffic classification have been introduced, such as signature-based and machine learning-based methods, Skype application, which uses encrypted communication on its own P2P network, is known as one of the most difficult traffic to identify. In this paper we propose a novel method to identify Skype application traffic on the fly. The main idea is to setup a list of Skype host information {IP, port} by examining the packets generated in the Skype login process and utilizes the list to identify other Skype traffic. By implementing the identification system and deploying it on our campus network, we proved the performance and feasibility of the proposed method.

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  Cite this article

[IEEE Style]

S. Lee, H. Lee, M. Choi, M. Kim, "Real-time Identification of Skype Application Traffic using Behavior Analysis," The Journal of Korean Institute of Communications and Information Sciences, vol. 36, no. 2, pp. 131-140, 2011. DOI: .

[ACM Style]

Sang-woo Lee, Hyun-shin Lee, Mi-jung Choi, and Myung-sup Kim. 2011. Real-time Identification of Skype Application Traffic using Behavior Analysis. The Journal of Korean Institute of Communications and Information Sciences, 36, 2, (2011), 131-140. DOI: .

[KICS Style]

Sang-woo Lee, Hyun-shin Lee, Mi-jung Choi, Myung-sup Kim, "Real-time Identification of Skype Application Traffic using Behavior Analysis," The Journal of Korean Institute of Communications and Information Sciences, vol. 36, no. 2, pp. 131-140, 2. 2011.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880