Internet traffic analysis in a large university town: A graphical and clustering approach

Weitao Weng, Kai Lei, Kuai Xu, Xiaoyou Liu, Tao Sun

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

Abstract

Campus networks consist of a rich diversity of end hosts including wired desktops, servers, and wireless BYOD devices such as laptops and smartphones, which are often compromised in insecure networks. Making sense of traffic behaviors of end hosts in campus networks is a daunting task due to the open nature of the network, heterogeneous devices, high mobility of end users, and a wide range of applications. To address these challenges, this paper applies a combination of graphical approaches and spectral clustering to group the Internet traffic of campus networks into distinctive traffic clusters in a divide-and-conquer manner. Specifically, we first model the data communication between a particular subnet of campus networks and the Internet on a specific application port via bipartite graphs, and subsequently use the one-mode projection to capture behavior similarity of end hosts in the same subnet for the same network applications. Finally we apply a spectral clustering algorithm to explore the behavior similarity to identify distinctive application clusters within each subnet. Our experimental results have demonstrated the benefits of our proposed method for analyzing Internet traffic of a large university town to discover anomalous behaviors and to uncover distinctive temporal and spatial traffic patterns.

Original languageEnglish (US)
Title of host publicationWeb-Age Information Management - 17th International Conference, WAIM 2016, Proceedings
PublisherSpringer Verlag
Pages378-389
Number of pages12
Volume9658
ISBN (Print)9783319399362
DOIs
StatePublished - 2016
Event17th International Conference on Web-Age Information Management, WAIM 2016 - Nanchang, China
Duration: Jun 3 2016Jun 5 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9658
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other17th International Conference on Web-Age Information Management, WAIM 2016
CountryChina
CityNanchang
Period6/3/166/5/16

Keywords

  • Bipartite graph
  • Campus network
  • Spectral clustering
  • Traffic analysis

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

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  • Cite this

    Weng, W., Lei, K., Xu, K., Liu, X., & Sun, T. (2016). Internet traffic analysis in a large university town: A graphical and clustering approach. In Web-Age Information Management - 17th International Conference, WAIM 2016, Proceedings (Vol. 9658, pp. 378-389). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9658). Springer Verlag. https://doi.org/10.1007/978-3-319-39937-9_29