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

Publication: Research - peer-reviewArticle in proceeding

View graph of relations

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.
Original languageEnglish
TitleFourth IEEE International Workshop on Performance Evaluation of Communications in Distributed Systems and Web based Service Architectures (PEDISWESA'12)
Number of pages6
Place of publicationCappadocia
PublisherIEEE Press
Publication date1 Jul 2012
Pages000882 - 000887
ISBN (print)978-1-4673-2712-1
ISBN (electronic)978-1-4673-2711-4
DOIs
StatePublished

Conference

ConferenceThe Seventeenth IEEE Symposium on Computers and Communications
LandTurkey
ByCappadocia
Periode01-07-1204-07-12

Keywords

  • traffic classification, computer networks, HTTP traffic, browser traffic, C5.0, Machine Learning Algorithms (MLAs), performance monitoring

Download statistics

No data available

ID: 62073457