@conference {1502499,
	title = {Security Games with Information Leakage: Modeling and Computation },
	booktitle = {International Joint Conference on Artificial Intelligence (IJCAI 2015)},
	year = {2015},
	abstract = {Most models of Stackelberg security games assume that the attacker only knows the defender{\textquoteright}s mixed strategy, but is not able to observe (even partially) the instantiated pure strategy. Such partial observation of the deployed pure strategy {\textendash} an issue we refer to as information
leakage {\textendash} is a significant concern in practical applications. While previous research on patrolling
games has considered the attacker{\textquoteright}s real-time surveillance, our settings, therefore models and
techniques, are fundamentally different. More specifically, after describing the information leakage model, we start with an LP formulation to compute the defender{\textquoteright}s optimal strategy in the
presence of leakage. Perhaps surprisingly, we show that a key subproblem to solve this LP
(more precisely, the defender oracle) is NP-hard even for the simplest of security game models.
We then approach the problem from three possible directions: efficient algorithms for restricted
cases, approximation algorithms, and heuristic algorithms for sampling that improves upon the
status quo. Our experiments confirm the necessity of handling information leakage and the
advantage of our algorithms.},
	author = {Haifeng Xu and Albert X. Jiang and Sinha, Arunesh and Zinovi Rabinovich and Dughmi, Shaddin and Tambe, Milind}
}
