@inproceedings{276fdb95701149268a4e724aabdcb02b,
title = "Classification of HTTP traffic based on C5.0 Machine Learning Algorithm",
abstract = "Our previous work demonstrated the possibility of distinguishing several groups of traffic 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 types of HTTP traffic based on the content: distributed among volunteers' machines and centralized running in the core of the network. We also assess the accuracy of the centralized classifier for both the HTTP traffic and mixed HTTP/non-HTTP traffic. In the latter case, we achieved the accuracy of 94%. Finally, we provide graphical characteristics of different kinds of HTTP traffic.",
keywords = "traffic classification, computer networks, HTTP traffic, browser traffic, C5.0, Machine Learning Algorithms (MLAs), performance monitoring",
author = "Tomasz Bujlow and Tahir Riaz and Pedersen, {Jens Myrup}",
year = "2012",
month = jul,
day = "1",
doi = "10.1109/ISCC.2012.6249413",
language = "English",
isbn = "978-1-4673-2712-1 ",
series = "I E E E International Symposium on Computers and Communications",
publisher = "IEEE",
pages = "000882 -- 000887",
booktitle = "IEEE Symposium on Computers and Communications (ISCC), 2012",
address = "United States",
note = "The Seventeenth IEEE Symposium on Computers and Communications, ISCC{\textquoteright}12 ; Conference date: 01-07-2012 Through 04-07-2012",
}