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Analysis of Communities of Interest in Data Networks

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Book cover Passive and Active Network Measurement (PAM 2005)

Abstract

Communities of interest (COI) have been applied in a variety of environments ranging from characterizing the online buying behavior of individuals to detecting fraud in telephone networks. The common thread among these applications is that the historical COI of an individual can be used to predict future behavior as well as the behavior of other members of the COI. It would clearly be beneficial if COIs can be used in the same manner to characterize and predict the behavior of hosts within a data network. In this paper, we introduce a methodology for evaluating various aspects of COIs of hosts within an IP network. In the context of this study, we broadly define a COI as a collection of interacting hosts. We apply our methodology using data collected from a large enterprise network over a eleven week period. First, we study the distributions and stability of the size of COIs. Second, we evaluate multiple heuristics to determine a stable core set of COIs and determine the stability of these sets over time. Third, we evaluate how much of the communication is not captured by these core COI sets.

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References

  1. Jin, E.M., et al.: The structure of growing social networks. Physics Review E 64, 845 (2001)

    Article  Google Scholar 

  2. Kumar, R., et al.: The web and social networks. IEEE Computer 25(11), 32–36 (2002)

    Google Scholar 

  3. Kleinberg, J.: The Small-World Phenomenon: An Algorithmic Perspective. In: Proceedings 32nd ACM Symposium on Theory of Computing, pp. 163–170 (2000)

    Google Scholar 

  4. Kleinberg, J.: Navigation in a small world. Nature 405, 845 (2000)

    Article  Google Scholar 

  5. Godfrey Tan et. al., “Role Classification of Hosts within Enterprise Networks Based on Connection Patterns,” in Proceedings of 2003 USENIX Annual Technical Conference, pp. 15–28, San Antonio, TX (June 2003)

    Google Scholar 

  6. Cortes, C., Pregibon, D., Volinsky, C.T.: Communities of interest. Intelligent Data Analysis 6(3), 211–219 (2002)

    MATH  Google Scholar 

  7. Cranor, C., et al.: Gigascope: a stream database for network applications. In: Proceedings of ACM SIGMOD (June 2003)

    Google Scholar 

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© 2005 Springer-Verlag Berlin Heidelberg

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Aiello, W., Kalmanek, C., McDaniel, P., Sen, S., Spatscheck, O., Van der Merwe, J. (2005). Analysis of Communities of Interest in Data Networks. In: Dovrolis, C. (eds) Passive and Active Network Measurement. PAM 2005. Lecture Notes in Computer Science, vol 3431. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-31966-5_7

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  • DOI: https://doi.org/10.1007/978-3-540-31966-5_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25520-8

  • Online ISBN: 978-3-540-31966-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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