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Classification of HTTP traffic based on C5.0 Machine Learning Algorithm

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3 Author(s)
Bujlow, T. ; Dept. of Electron. Syst., Aalborg Univ., Aalborg, Denmark ; Riaz, T. ; Pedersen, J.M.

Our previous work demonstrated the possibility of distinguishing several kinds of applications with accuracy of over 99%. Today, most of the traffic is generated by web browsers, which provide different kinds of services based on the HTTP protocol: web browsing, file downloads, audio and voice streaming through third-party plugins, etc. This paper suggests and evaluates two approaches to distinguish various HTTP content: distributed among volunteers' machines and centralized running in the core of the network. We also assess accuracy of the global classifier for both HTTP and non-HTTP traffic. We achieved accuracy of 94%, which supposed to be even higher in real-life usage. Finally, we provided graphical characteristics of different kinds of HTTP traffic.

Published in:

Computers and Communications (ISCC), 2012 IEEE Symposium on

Date of Conference:

1-4 July 2012