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A Fresh Look at the Generalised Mix Framework

  • Andrei Serjantov
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4776)

Abstract

Anonymity systems designed to handle anonymous email have been implemented with a variety of different mixes. Although many of their properties have been analysed in previous work, some are still not well understood and many results are still missing.

In this paper we reexamine the generalised mix framework and the binomial mix of [7]. We show that under some parameterizations the binomial mix has undesirable properties. More specifically, for any constant parameterization of the binomial mix, there is a minimum number of messages beyond which it acts as a timed mix. In this case the number of messages inside it is no longer hidden from the adversary and the mix is vulnerable to easy active attack. We suggest ways to avoid this in the generalised mix framework. Secondly, we show that the binomial distribution used in the framework produces distribution of pool sizes with low variance and show how to improve on this.

Finally, we present a technique from queueing theory which allows us to analyse this property for a class of mixes assuming Poisson message arrivals.

Keywords

Binomial Distribution Pool Size Stochastic Volatility Modeling Stochastic Volatility Undesirable Property 
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 2007

Authors and Affiliations

  • Andrei Serjantov
    • 1
  1. 1.The Free Haven Project 

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