Network-aware behavior clustering of Internet end hosts

Research output: Chapter in Book/Report/Conference proceedingConference contribution

36 Scopus citations

Abstract

This paper explores the behavior similarity of Internet end hosts in the same network prefixes. We use bipartite graphs to model network traffic, and then construct one-mode projection graphs for capturing social-behavior similarity of end hosts. By applying a simple and efficient spectral clustering algorithm, we perform network-aware clustering of end hosts in the same prefixes into different behavior clusters. Based on information-theoretical measures, we find that the clusters exhibit distinct traffic characteristics which provides improved interpretations of the separated traffic compared with the aggregated traffic of the prefixes. Finally, we demonstrate the applications of exploring behavior similarity in profiling network behaviors and detecting anomalous behaviors through synthetic traffic that combines Internet backbone traffic and packet traces from real scenarios of worm propagations and denial of service attacks.

Original languageEnglish (US)
Title of host publication2011 Proceedings IEEE INFOCOM
Pages2078-2086
Number of pages9
DOIs
StatePublished - Aug 2 2011
EventIEEE INFOCOM 2011 - Shanghai, China
Duration: Apr 10 2011Apr 15 2011

Publication series

NameProceedings - IEEE INFOCOM
ISSN (Print)0743-166X

Other

OtherIEEE INFOCOM 2011
CountryChina
CityShanghai
Period4/10/114/15/11

ASJC Scopus subject areas

  • Computer Science(all)
  • Electrical and Electronic Engineering

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