eprintid: 1243 rev_number: 11 eprint_status: archive userid: 6 dir: disk0/00/00/12/43 datestamp: 2012-03-27 09:38:21 lastmod: 2014-07-28 12:21:19 status_changed: 2012-03-27 09:38:21 type: book_section metadata_visibility: show creators_name: Boreale, Michele creators_name: Pampaloni, Francesca creators_name: Paolini, Michela creators_id: creators_id: francesca.pampaloni@imtlucca.it creators_id: michela.paolini@alumni.imtlucca.it title: Asymptotic information leakage under one-try attacks ispublished: pub subjects: QA75 divisions: CSA full_text_status: public keywords: Security; quantitative information leakage; information theory; Bayes risk; hidden Markov models note: Proceedings of the 14th International Conference, FOSSACS 2011, Held as Part of the Joint European Conferences on Theory and Practice of Software, ETAPS 2011, Saarbrücken, Germany, March 26–April 3, 2011 abstract: We study the asymptotic behaviour of (a) information leakage and (b) adversary’s error probability in information hiding systems modelled as noisy channels. Specifically, we assume the attacker can make a single guess after observing n independent executions of the system, throughout which the secret information is kept fixed. We show that the asymptotic behaviour of quantities (a) and (b) can be determined in a simple way from the channel matrix. Moreover, simple and tight bounds on them as functions of n show that the convergence is exponential. We also discuss feasible methods to evaluate the rate of convergence. Our results cover both the Bayesian case, where a prior probability distribution on the secrets is assumed known to the attacker, and the maximum-likelihood case, where the attacker does not know such distribution. In the Bayesian case, we identify the distributions that maximize the leakage. We consider both the min-entropy setting studied by Smith and the additive form recently proposed by Braun et al., and show the two forms do agree asymptotically. Next, we extend these results to a more sophisticated eavesdropping scenario, where the attacker can perform a (noisy) observation at each state of the computation and the systems are modelled as hidden Markov models. date: 2011 date_type: published series: Lecture Notes in Computer Science volume: 6604 number: 6604 publisher: Springer pagerange: 396-410 id_number: 10.1007/978-3-642-19805-2_27 refereed: TRUE isbn: 978-3-642-19804-5 book_title: Foundations of Software Science and Computational Structures editors_name: Hoffman, Martin official_url: http://dx.doi.org/10.1007/978-3-642-19805-2_27 projects: Work partially supported by the eu project Ascens under the fet open initiative in fp7. citation: Boreale, Michele and Pampaloni, Francesca and Paolini, Michela Asymptotic information leakage under one-try attacks. In: Foundations of Software Science and Computational Structures. Lecture Notes in Computer Science, 6604 (6604). Springer, pp. 396-410. ISBN 978-3-642-19804-5 (2011) document_url: http://eprints.imtlucca.it/1243/1/Pampaloni_LCNS_2011.pdf