TY - GEN
T1 - Information Leakage Games
AU - Alvim, Mário S.
AU - Chatzikokolakis, Konstantinos
AU - Kawamoto, Yusuke
AU - Palamidessi, Catuscia
N1 - Publisher Copyright:
© 2017, Springer International Publishing AG.
PY - 2017/1/1
Y1 - 2017/1/1
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/85032866904
U2 - 10.1007/978-3-319-68711-7_23
DO - 10.1007/978-3-319-68711-7_23
M3 - Conference contribution
AN - SCOPUS:85032866904
SN - 9783319687100
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 437
EP - 457
BT - Decision and Game Theory for Security - 8th International Conference, GameSec 2017, Proceedings
A2 - Kiekintveld, Christopher
A2 - Schauer, Stefan
A2 - An, Bo
A2 - Rass, Stefan
A2 - Fang, Fei
PB - Springer Verlag
T2 - 8th International Conference on Decision and Game Theory for Security, GameSec 2017
Y2 - 23 October 2017 through 25 October 2017
ER -