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Bounds on the Leakage of the Input’s Distribution in Information-Hiding Protocols

  • Abhishek Bhowmick
  • Catuscia Palamidessi
Conference paper
  • 170 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5474)

Abstract

In information-hiding, an adversary that tries to infer the secret information has a higher probability of success if it knows the distribution on the secrets. We show that if the system leaks probabilistically some information about the secrets, (that is, if there is a probabilistic correlation between the secrets and some observables) then the adversary can approximate such distribution by repeating the observations. More precisely, it can approximate the distribution on the observables by computing their frequencies, and then derive the distribution on the secrets by using the correlation in the inverse direction. We illustrate this method, and then we study the bounds on the approximation error associated with it, for various natural notions of error. As a case study, we apply our results to Crowds, a protocol for anonymous communication.

Keywords

Noisy Channel Covert Channel Anonymous Communication Hide Event USENIX Security Symposium 
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 2009

Authors and Affiliations

  • Abhishek Bhowmick
    • 1
  • Catuscia Palamidessi
    • 2
  1. 1.Computer Science and EngineeringIIT KanpurIndia
  2. 2.INRIA Saclay and LIXEcole PolytechniqueFrance

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