%0 Conference Paper %B AAAI Conference on Artificial Intelligence (AAAI) %D 2015 %T Exploring Information Asymmetry in Two-Stage Security Games %A Xu, H. %A Z. Rabinovich %A S. Dughmi %A M. Tambe %X Stackelberg security games have been widely deployed to protect real-world assets. The main solution concept there is the Strong Stackelberg Equilibrium (SSE), which optimizes the defender’s random allocation of limited security resources. However, solely deploying the SSE mixed strategy has limitations. In the extreme case, there are security games in which the defender is able to defend all the assets “almost perfectly” at the SSE, but she still sustains significant loss. In this paper, we propose an approach for improving the defender’s utility in such scenarios. Perhaps surprisingly, our approach is to strategically reveal to the attacker information about the sampled pure strategy. Specifically, we propose a two-stage security game model, where in the first stage the defender allocates resources and the attacker selects a target to attack, and in the second stage the defender strategically reveals local information about that target, potentially deterring the attacker’s attack plan. We then study how the defender can play optimally in both stages. We show, theoretically and experimentally, that the two-stage security game model allows the defender to achieve strictly better utility than SSE. %B AAAI Conference on Artificial Intelligence (AAAI) %G eng