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Quantitative Information Flow and Applications to Differential Privacy

Mário Alvim 1 Miguel Andrés 1 Konstantinos Chatzikokolakis 1 Catuscia Palamidessi 1
1 COMETE - Concurrency, Mobility and Transactions
Inria Saclay - Ile de France, LIX - Laboratoire d'informatique de l'École polytechnique [Palaiseau]
Abstract : Secure information flow is the problem of ensuring that the information made publicly available by a computational system does not leak information that should be kept secret. Since it is practically impossible to avoid leakage entirely, in recent years there has been a growing interest in considering the quantitative aspects of information flow, in order to measure and compare the amount of leakage. Information theory is widely regarded as a natural framework to provide firm foundations to quantitative information flow. In this notes we review the two main information-theoretic approaches that have been investigated: the one based on Shannon entropy, and the one based on Rényi min-entropy. Furthermore, we discuss some applications in the area of privacy. In particular, we consider statistical databases and the recently-proposed notion of differential privacy. Using the information-theoretic view, we discuss the bound that differential privacy induces on leakage, and the trade-off between utility and privacy
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Submitted on : Friday, December 30, 2011 - 12:14:49 AM
Last modification on : Monday, December 14, 2020 - 3:33:07 PM
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Mário Alvim, Miguel Andrés, Konstantinos Chatzikokolakis, Catuscia Palamidessi. Quantitative Information Flow and Applications to Differential Privacy. Alessandro Aldini and Roberto Gorrieri. Foundations of Security Analysis and Design VI -- FOSAD Tutorial Lectures, 6858, Springer, pp.211--230, 2011, Lecture Notes in Computer Science, ⟨10.1007/978-3-642-23082-0_8⟩. ⟨hal-00655522⟩



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