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Compositionality Results for Quantitative Information Flow

  • Yusuke Kawamoto
  • Konstantinos Chatzikokolakis
  • Catuscia Palamidessi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8657)

Abstract

In the min-entropy approach to quantitative information flow, the leakage is defined in terms of a minimization problem, which, in case of large systems, can be computationally rather heavy. The same happens for the recently proposed generalization called g-vulnerability. In this paper we study the case in which the channel associated to the system can be decomposed into simpler channels, which typically happens when the observables consist of several components. Our main contribution is the derivation of bounds on the g-leakage of the whole system in terms of the g-leakages of its components.

Keywords

Compositionality Result Channel Matrix Parallel Composition Gain Function Operational Scenario 
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 International Publishing Switzerland 2014

Authors and Affiliations

  • Yusuke Kawamoto
    • 1
    • 2
  • Konstantinos Chatzikokolakis
    • 2
    • 3
  • Catuscia Palamidessi
    • 1
    • 2
  1. 1.INRIAFrance
  2. 2.École PolytechniqueFrance
  3. 3.CNRSFrance

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