DDRIG in DRMS: Multi-target Technology Deployment and Information Disclosure in Attacker-defender Settings: Analyzing Game-theoretic Prescriptions and Human Decisions

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Defending against adversarial threats has been a central and longstanding focus for governments throughout the world. One prominent approach to improve defensive capabilities is to deploy new technologies among venues of interest (e.g., metal detectors at airports). When it comes to deploying new security and defense technologies, agencies must decide how the related information should be released to the public. Given that adversaries, such as terrorist organizations, can access information that is publicly disseminated, it is critical to understand the implications of releasing different types of information. For instance, security agencies may choose to release information on only a subset of venues where new technology is deployed, creating an uncertainty for an adversary regarding the deployment of the technology at other venues (e.g., airports). This research addresses this difficult information disclosure problem by building on previous work in game theory and adversarial decision making to develop models and experiments that provide insights into defensive information disclosure, adversarial beliefs, and adversarial target selection decisions.The research objectives of this proposed effort are to mathematically model, experimentally test, and robustly analyze technology deployment and information disclosure strategies in the context of security and defense. To meet these objectives, this project develops and analyzes a novel game-theoretic signaling model, which provides insightful analyses into optimal information disclosure strategies. Further, human experiments –designed to mimic the game model – are conducted to (i) study human beliefs and decision making in this context, and (ii) compare the game-theoretic prescriptions with actual human decisions. Successful completion of this project helps to inform the long-term effectiveness of technology deployments within the security and defense sectors. Although this research is motivated by problems in security and defense, the mathematical model and experimental framework is generalizable to any application in which the strategic release of information across multiple venues is of interest.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.