%0 Thesis %D 2015 %T Balancing Tradeoffs in Security Games: Handling Defenders and Adversaries with Multiple Objectives %A Brown, Matthew %X Stackelberg security games (SSG) have received a significant amount of attention in the literature for modeling the strategic interactions between a defender and an adversary, in which the defender has a limited amount of security resources to protect a set of targets from a potential attack by the adversary. SSGs are at the heart of several significant decision-support applications deployed in real world security domains. All of these applications rely on standard assumptions made in SSGs, including that the defender and the adversary each have a single objective which is to maximize their expected utility. Given the successes and real world impact of previous SSG research, there is a natural desire to push towards increasingly complex security domains, leading to a point where considering only a single objective is no longer appropriate. My thesis focuses on incorporating multiple objectives into SSGs. With multiple conflicting objectives for either the defender or adversary, there is no one solution which maximizes all objectives simultaneously and tradeoffs between the objectives must be made. Thus, my thesis provides two main contributions by addressing the research challenges raised by considering SSGs with (1) multiple defender objectives and (2) multiple adversary objectives. These contributions consist of approaches for modeling, calculating, and analyzing the tradeoffs between objectives in a variety of different settings. First, I consider multiple defender objectives resulting from diverse adversary threats where protecting against each type of threat is treated as a separate objective for the defender. Second, I investigate the defender’s need to balance between the exploitation of collected data and the exploration of alternative strategies in patrolling domains. Third, I explore the necessary tradeoff between the efficacy and the efficiency of the defender’s strategy in screening domains. Forth, I examine multiple adversary objectives for heterogeneous populations of boundedly rational adversaries that no longer strictly maximize expected utility. The contributions of my thesis provide the novel game models and algorithmic techniques required to incorporate multiple objectives into SSGs. My research advances the state of the art in SSGs and opens up the model to new types of security domains that could not have been handled previously. As a result, I developed two applications for real world security domains that either have been or will be tested and evaluated in the field. %G eng %9 PhD thesis