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Information Leakage Games

  • Universidade Federal de Minas Gerais
  • National Institute of Advanced Industrial Science and Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We consider a game-theoretic setting to model the interplay between attacker and defender in the context of information flow, and to reason about their optimal strategies. In contrast with standard game theory, in our games the utility of a mixed strategy is a convex function of the distribution on the defender’s pure actions, rather than the expected value of their utilities. Nevertheless, the important properties of game theory, notably the existence of a Nash equilibrium, still hold for our (zero-sum) leakage games, and we provide algorithms to compute the corresponding optimal strategies. As typical in (simultaneous) game theory, the optimal strategy is usually mixed, i.e., probabilistic, for both the attacker and the defender. From the point of view of information flow, this was to be expected in the case of the defender, since it is well known that randomization at the level of the system design may help to reduce information leaks. Regarding the attacker, however, this seems the first work (w.r.t. the literature in information flow) proving formally that in certain cases the optimal attack strategy is necessarily probabilistic.

Original languageEnglish
Title of host publicationDecision and Game Theory for Security - 8th International Conference, GameSec 2017, Proceedings
EditorsChristopher Kiekintveld, Stefan Schauer, Bo An, Stefan Rass, Fei Fang
PublisherSpringer Verlag
Pages437-457
Number of pages21
ISBN (Print)9783319687100
DOIs
Publication statusPublished - 1 Jan 2017
Event8th International Conference on Decision and Game Theory for Security, GameSec 2017 - Vienna, Austria
Duration: 23 Oct 201725 Oct 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10575 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference8th International Conference on Decision and Game Theory for Security, GameSec 2017
Country/TerritoryAustria
CityVienna
Period23/10/1725/10/17

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