Quantifying Leakage in the Presence of Unreliable Sources of Information

Sardaouna Hamadou 1 Catuscia Palamidessi 2, 1 Vladimiro Sassone 3
1 COMETE - Concurrency, Mobility and Transactions
LIX - Laboratoire d'informatique de l'École polytechnique [Palaiseau], Inria Saclay - Ile de France, X - École polytechnique, CNRS - Centre National de la Recherche Scientifique : UMR7161
Abstract : Belief and min-entropy leakage are two well-known approaches to quantify information flow in security systems. Both concepts stand as alternatives to the traditional approaches founded on Shannon entropy and mutual information , which were shown to provide inadequate security guarantees. In this paper we unify the two concepts in one model so as to cope with the frequent (potentially inaccurate, misleading or outdated) attackers' side information about individuals on social networks, online forums, blogs and other forms of online communication and information sharing. To this end we propose a new metric based on min-entropy that takes into account the adversary's beliefs.
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Journal of Computer and System Sciences, Elsevier, 2017, 88, pp.27-52
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Sardaouna Hamadou, Catuscia Palamidessi, Vladimiro Sassone. Quantifying Leakage in the Presence of Unreliable Sources of Information. Journal of Computer and System Sciences, Elsevier, 2017, 88, pp.27-52. 〈hal-01421417〉

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