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Decidability of Parameterized Probabilistic Information Flow

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Computer Science – Theory and Applications (CSR 2007)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4649))

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Abstract

In this paper, we consider the decidability of two problems related to information flow in a system with respect to some property. A flow occurs in a system if the conditional probability of the property under some partial observation differs from the a priori probability of that property. For systems modelled as finite Markov chains we prove that the two following problems are decidable: does a system has information flow for a given regular property? is it true that the system has no information flow for any (sequential) property?

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Author information

Authors and Affiliations

  1. University Paris 12, France

    Danièle Beauquier & Marie Duflot

  2. Steklov Institute of Mathematics, St.Petersburg, Russia

    Yury Lifshits

Authors
  1. Danièle Beauquier
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  2. Marie Duflot
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  3. Yury Lifshits
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Editor information

Volker Diekert Mikhail V. Volkov Andrei Voronkov

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© 2007 Springer-Verlag Berlin Heidelberg

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Beauquier, D., Duflot, M., Lifshits, Y. (2007). Decidability of Parameterized Probabilistic Information Flow. In: Diekert, V., Volkov, M.V., Voronkov, A. (eds) Computer Science – Theory and Applications. CSR 2007. Lecture Notes in Computer Science, vol 4649. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74510-5_11

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  • DOI: https://doi.org/10.1007/978-3-540-74510-5_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74509-9

  • Online ISBN: 978-3-540-74510-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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