This research project focuses on improving the security of the population in the case of a terrorist threat, and how integrated modeling can be used (1) to improve scientific understanding of human decision-making in adversarial contexts, and (2) in the design of allocation policies and best practices for protection of soft targets, i.e., public transit facilities, places of mass gathering, and their users. It involves theoretical and computational research that will explore the foundations of infrastructure protection technologies through integrated modeling and optimization and will develop new methods and tools to support real-time emergency management and policy development. The project has a wide range of applications from homeland security and law enforcement to military applications. This research is transformational since it brings a fresh vision to risk management and sensing/control networks for security. The most significant impact of the research is expected to be to public facilities, campuses, school buildings and its users by providing support to first responders in decision making about prevention and deterrence of terrorist attacks as well as minimization of damage during an attack. Results of the work will be communicated with the major regional players, including NY/NJ Port Authority, NJ Transit, NJ Department of Homeland Security and NJDOT. The adversarial decision making models and virtual game infrastructure that will result from the research are also applicable to other areas such as training law enforcement personnel to prevent gang violence and training campus police. This study also seeks to have a broad impact, especially, in regard to the integration of research and education; it will provide the basis for a Ph.D. dissertation and will provide support to mentor a postdoctoral associate in information sciences and its application to security. The results of the research will establish the framework for a comprehensive book on infrastructure protection games to be used by students as well as practitioners.
The key features of the research project are (i) closed form analytical solutions, (ii) game models that explore the ways in which the uncertainty and incomplete information about the adversary type, attack type and power, can be exploited by the players, (iii) a patrolling game that incorporates detection probability and a people flow model representing moving targets, and (iv) a virtual game built inside an immersive virtual world designed to both collect data about the players' behavior and to validate the game models using metrics such as the expected damage, the fraction of unsuccessful attacks, etc. The objectives of the research are to (1) Develop stochastic network protection game algorithms to be used by the defenders, together with current technologies, in planning for emergency preparedness, for prevention of terrorist or cyber attacks to reduce the loss of valuable assets; (2) Design a virtual game involving the key elements of the above models in order to collect information about the behavior of various players of the game; (3) Test models for real player behavior in a controlled setting via virtual games to verify and refine models for human subject behavior in the stochastic games. These objectives will be accomplished by adapting resource allocation game models to the virtual game. Realistic player behavior data will be collected to validate the models. The anticipated results of this research are both analytical and relevant to practitioners, such as emergency management agencies, police, etc. The research makes contributions to i) stochastic modeling of adversarial policies in man-made emergencies; ii) stochastic game theory for partially observable systems; iii) decision-making in defending critical infrastructure; iv) educating future first responders in homeland security and resource allocation.
