Security is a critical concern around the world, whether it is the challenge of protecting ports, airports and other critical infrastructure, interdicting the illegal flow of drugs, weapons and money, protecting endangered species, forests and fisheries, suppressing crime in urban areas or security in cyberspace. Unfortunately, limited security resources prevent full security coverage at all times. Instead, these limited security resources must be allocated and scheduled randomly and efficiently. The security resource allocation must simultaneously take into account an adversary's response to the security coverage (e.g., an adversary can exploit predictability in security allocation), the adversary's preferences and the potential uncertainty over such preferences and capabilities.
Computational game theory can help us build decision-aids for efficient, randomized security resource allocation. Indeed, by casting the security allocation problem as a Bayesian Stackelberg game, we have developed new algorithms that have been deployed over multiple years in multiple applications: for security of ports and ferry traffic with the US coast guard (currently deployed in the ports of New York/New Jersey, Boston, Los Angeles/Long Beach and others), for security of airports and air traffic with the the Federal Air Marshals (FAMS) and the Los Angeles World Airport (LAX) police, and for security of metro trains with the Los Angeles Sheriff's Department (LASD) and the TSA, with additional applications under development. These applications are leading to real-world use-inspired research and application in the emerging research area of “security games”: these research challenges include scaling up of security games to large-scale problems, handling significant adversarial uncertainty, dealing with bounded rationality of human adversaries and other interdisciplinary challenges. I will provide an overview of my research's group's work in this area, outlining key algorithmic principles, research results, as well as a discussion of our deployed systems and lessons learned.
(*) This is joint work with a number of former and current PHD students, postdocs, and other collaborators, all listed at: http://teamcore.usc.edu/security
Milind Tambe is Helen N. and Emmett H. Jones Professor in Engineering at the University of Southern California(USC). He is a fellow of AAAI (Association for Advancement of Artificial Intelligence), recipient of the ACM/SIGART Autonomous Agents Research Award, Christopher Columbus Fellowship Foundation Homeland security award, the INFORMS Wagner prize for excellence in Operations Research practice and the Rist Prize of the Military Operations Research Society. Prof. Tambe has contributed several foundational papers in agents and multiagent systems; this includes areas of multiagent teamwork, distributed constraint optimization (DCOP) and security games. For this research, he has received the "influential paper award" from the International Foundation for Agents and Multiagent Systems(IFAAMAS), as well as with his research group, best paper awards at a number of premier Artificial Intelligence Conferences and workshops, including multiple best paper awards at the International Conference on Autonomous Agents and Multiagent Systems and International Conference on Intelligent Virtual Agents. In addition, the ''security games'' framework and algorithms pioneered by Prof. Tambe and his research group are now deployed for real-world use by several agencies including the US Coast Guard, the US Federal Air Marshals service, the Transportation Security Administration, LAX Police and the LA Sheriff's Department for security deployments at a variety of US ports, airports and transportation infrastructure. This research has led to him and his students receiving the US Coast Guard Meritorious Team Commendation from the Commandant, US Coast Guard First District's Operational Excellence Award, Certificate of Appreciation from the US Federal Air Marshals Service and special commendation given by the Los Angeles World Airports police from the city of Los Angeles. Additionally, for his research Prof. Tambe has also received the IBM Faculty Award, Okawa foundation faculty research award, RoboCup scientific challenge award and USC Viterbi School of Engineering use-inspired research award. Finally, for his teaching and service, Prof. Tambe has received the USC Steven B. Sample Teaching and Mentoring award and the ACM recognition of service award. Recently, he co-founded ARMORWAY, a company focused on risk mitigation and security resource optimization, where he serves on the board of directors. Prof. Tambe received his Ph.D. from the School of Computer Science at Carnegie Mellon University.