Reliable Probabilistic Classification of Internet Traffic. / Dashevskiy, Mikhail; Luo, Zhiyuan.

In: International Journal of Information Acquisition, Vol. 6, No. 2, 2009, p. 133-146.

Research output: Contribution to journalArticlepeer-review

Published

Abstract

Classification of Internet traffic is very important to many applications such as network resource management, network security enforcement and intrusion detection. Many machine-learning algorithms have been successfully used to classify network traffic flows with good performance, but without information about the reliability in classifications. In this paper, we present a recently developed algorithmic framework, namely the Venn Probability Machine, for making reliable decisions under uncertainty. Experiments on publicly available real Internet traffic datasets show the algorithmic framework works well. Comparison is also made to the published results.
Original languageEnglish
Pages (from-to)133-146
Number of pages14
JournalInternational Journal of Information Acquisition
Volume6
Issue number2
DOIs
Publication statusPublished - 2009
This open access research output is licenced under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License.

ID: 1289316