Measuring Information Leakage using Generalized Gain Functions

Mário S. Alvim 1 Konstantinos Chatzikokolakis 2, 3 Catuscia Palamidessi 2 Geoffrey Smith 4
2 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 : This paper introduces g-leakage, a rich general- ization of the min-entropy model of quantitative information flow. In g-leakage, the benefit that an adversary derives from a certain guess about a secret is specified using a gain function g. Gain functions allow a wide variety of operational scenarios to be modeled, including those where the adversary benefits from guessing a value close to the secret, guessing a part of the secret, guessing a property of the secret, or guessing the secret within some number of tries. We prove important properties of g-leakage, including bounds between min-capacity, g-capacity, and Shannon capacity. We also show a deep connection between a strong leakage ordering on two channels, C1 and C2, and the possibility of factoring C1 into C2 C3 , for some C3 . Based on this connection, we propose a generalization of the Lattice of Information from deterministic to probabilistic channels.
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Communication dans un congrès
Computer Security Foundations, 2012, Cambridge MA, United States. IEEE, pp.265-279, 2012, 〈10.1109/CSF.2012.26〉
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Dernière modification le : jeudi 10 mai 2018 - 02:06:52
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Mário S. Alvim, Konstantinos Chatzikokolakis, Catuscia Palamidessi, Geoffrey Smith. Measuring Information Leakage using Generalized Gain Functions. Computer Security Foundations, 2012, Cambridge MA, United States. IEEE, pp.265-279, 2012, 〈10.1109/CSF.2012.26〉. 〈hal-00734044〉

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