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Unmixing Mix Traffic

  • Ye Zhu
  • Riccardo Bettati
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3856)

Abstract

We apply blind source separation techniques from statistical signal processing to separate the traffic in a mix network. Our experiments show that this attack is effective and scalable. By combining the flow separation method and frequency spectrum matching method, a passive attacker can get the traffic map of the mix network. We use a non-trivial network to show that the combined attack works. The experiments also show that multicast traffic can be dangerous for anonymity networks.

Keywords

Independent Component Analysis Blind Source Separation Frequency Match Correlation Attack Anonymous Communication 
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.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Ye Zhu
    • 1
  • Riccardo Bettati
    • 1
  1. 1.Department of Computer ScienceTexas A&M UniversityCollege StationUSA

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