Information Leakage Games

Alvim, Mário S.; Chatzikokolakis, Konstantinos; Kawamoto, Yusuke; Palamidessi, Catuscia

doi:10.1007/978-3-319-68711-7_23

Cited by 21 publications

(27 citation statements)

References 33 publications

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“…Notable exceptions are the works [4,8,21], which consider attackers who interact with and influence the system, possibly in an adaptive way, with the purpose of maximizing the leakage of information.…”

Section: Example 2 (Dining Cryptographers)mentioning

confidence: 99%

“…We consider zero-sum games, in which the gain (for the attacker) is represented by the leakage. While for visible choice it is appropriate to use the "classic" game-theoretic framework, for hidden choice we need to adopt the more general framework of the information leakage games proposed in [4]. This happens because, in contrast with standard game theory, in games with hidden choice the utility of a mixed strategy is a convex function of the distribution on the defender's pure actions, rather than simply the expected value of their utilities.…”

Section: Example 3 (Crime Attack)mentioning

confidence: 99%

“…-We present a general framework for reasoning about information leakage in a game-theoretic setting, extending the notion of information leakage games proposed in [4] to both simultaneous and sequential games, with either hidden or visible choice. -We present a rigorous compositional way, using visible and hidden choice operators, for representing adversary and defender's actions in information leakage games.…”

Section: Example 3 (Crime Attack)mentioning

confidence: 99%

“…-We provide a taxonomy of the various scenarios (simultaneous and sequential) showing when randomization is necessary, for either attacker or defender, to achieve optimality. Although it is well-known in information flow that the defender's best strategy is usually randomized, only recently it has been shown that when defender and adversary act simultaneously, the adversary's optimal strategy also requires randomization [4]. -We use our framework in a detailed case study of a password-checking protocol.…”

Section: Example 3 (Crime Attack)mentioning

confidence: 99%

“…a set of basic axioms. 4 Channels, Posterior Vulnerability, and Leakage. Computational systems can be modeled as information theoretic channels.…”

Section: Secrets and Vulnerabilitymentioning

confidence: 99%

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Leakage and Protocol Composition in a Game-Theoretic Perspective

Alvim

Chatzikokolakis

Kawamoto

et al. 2018

Lecture Notes in Computer Science

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Abstract. In the inference attacks studied in Quantitative Information Flow (QIF), the adversary typically tries to interfere with the system in the attempt to increase its leakage of secret information. The defender, on the other hand, typically tries to decrease leakage by introducing some controlled noise. This noise introduction can be modeled as a type of protocol composition, i.e., a probabilistic choice among different protocols, and its effect on the amount of leakage depends heavily on whether or not this choice is visible to the adversary. In this work we consider operators for modeling visible and invisible choice in protocol composition, and we study their algebraic properties. We then formalize the interplay between defender and adversary in a game-theoretic framework adapted to the specific issues of QIF, where the payoff is information leakage. We consider various kinds of leakage games, depending on whether players act simultaneously or sequentially, and on whether or not the choices of the defender are visible to the adversary. Finally, we establish a hierarchy of these games in terms of their information leakage, and provide methods for finding optimal strategies (at the points of equilibrium) for both attacker and defender in the various cases.

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Section: Example 2 (Dining Cryptographers)mentioning

confidence: 99%

Section: Example 3 (Crime Attack)mentioning

confidence: 99%

Section: Example 3 (Crime Attack)mentioning

confidence: 99%

Section: Example 3 (Crime Attack)mentioning

confidence: 99%

“…a set of basic axioms. 4 Channels, Posterior Vulnerability, and Leakage. Computational systems can be modeled as information theoretic channels.…”

Section: Secrets and Vulnerabilitymentioning

confidence: 99%

See 3 more Smart Citations

Leakage and Protocol Composition in a Game-Theoretic Perspective

Alvim

Chatzikokolakis

Kawamoto

et al. 2018

Lecture Notes in Computer Science

Self Cite

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Hybrid statistical estimation of mutual information and its application to information flow

et al. 2019

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Analysis of a probabilistic system often requires to learn the joint probability distribution of its random variables. The computation of the exact distribution is usually an exhaustive precise analysis on all executions of the system. To avoid the high computational cost of such an exhaustive search, statistical analysis has been studied to efficiently obtain approximate estimates by analyzing only a small but representative subset of the system's behavior. In this paper we propose a hybrid statistical estimation method that combines precise and statistical analyses to estimate mutual information, Shannon entropy, and conditional entropy, together with their confidence intervals. We show how to combine the analyses on different components of a discrete system with different accuracy to obtain an estimate for the whole system. The new method performs weighted statistical analysis with different sample sizes over different components and dynamically finds their optimal sample sizes. Moreover, it can reduce sample sizes by using prior knowledge about systems and a new abstraction-then-sampling technique based on qualitative analysis. To apply the method to the source code of a system, we show how to decompose the code into components and to determine the analysis method for each component by overviewing the implementation of those techniques in the HyLeak tool. We demonstrate with case studies that the new method outperforms the state of the art in quantifying information leakage.

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