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

Tomasz Bujlow, Tahir Riaz, Jens Myrup Pedersen

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

14 Citationer (Scopus)
1016 Downloads (Pure)

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.
OriginalsprogEngelsk
TitelIEEE Symposium on Computers and Communications (ISCC), 2012
Antal sider6
UdgivelsesstedCappadocia
ForlagIEEE
Publikationsdato1 jul. 2012
Sider000882 - 000887
ISBN (Trykt)978-1-4673-2712-1
ISBN (Elektronisk)978-1-4673-2711-4
DOI
StatusUdgivet - 1 jul. 2012
BegivenhedThe Seventeenth IEEE Symposium on Computers and Communications - Cappadocia, Tyrkiet
Varighed: 1 jul. 20124 jul. 2012

Konference

KonferenceThe Seventeenth IEEE Symposium on Computers and Communications
Land/OmrådeTyrkiet
ByCappadocia
Periode01/07/201204/07/2012
NavnI E E E International Symposium on Computers and Communications
ISSN1530-1346

Fingeraftryk

Dyk ned i forskningsemnerne om 'Classification of HTTP traffic based on C5.0 Machine Learning Algorithm'. Sammen danner de et unikt fingeraftryk.

Citationsformater