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Discovering Hidden Groups in Communication Networks

  • Conference paper

Part of the Lecture Notes in Computer Science book series (LNCS,volume 3073)

Abstract

We describe models and efficient algorithms for detecting groups (communities) functioning in communication networks which attempt to hide their functionality – hidden groups. Our results reveal the properties of the background network activity that make detection of the hidden group easy, as well as those that make it difficult.

Keywords

  • Hide Markov Model
  • Random Graph
  • Random Model
  • Communication Graph
  • Rensselaer Polytechnic Institute

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

This research was partially supported by NSF grants 0324947 and 0346341

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References

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© 2004 Springer-Verlag Berlin Heidelberg

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Baumes, J., Goldberg, M., Magdon-Ismail, M., Wallace, W.A. (2004). Discovering Hidden Groups in Communication Networks. In: Chen, H., Moore, R., Zeng, D.D., Leavitt, J. (eds) Intelligence and Security Informatics. ISI 2004. Lecture Notes in Computer Science, vol 3073. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-25952-7_28

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  • DOI: https://doi.org/10.1007/978-3-540-25952-7_28

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22125-8

  • Online ISBN: 978-3-540-25952-7

  • eBook Packages: Springer Book Archive