Abstract
Security is a critical concern around the world, whether it is the challenge of protecting ports, airports and other critical infrastructure, protecting endangered wildlife, forests and fisheries, suppressing urban crime or security in cyberspace. Unfortunately, limited security resources prevent full security coverage at all times; instead, we must optimize the use of limited security resources. To that end, our "security games" framework -- based on computational and behavioral game theory, while also incorporating elements of AI planning under uncertainty and machine learning -- has led to building and deployment of decision aids for security agencies in the US and around the world. These decision aids are in use by agencies such as the US Coast Guard for protection of ports and ferry traffic, the Federal Air Marshals Service for security of air traffic and by various police agencies for security of university campuses, airports and metro trains. Moreover, recent work on "green security games" has led our decision aids to be deployed, assisting NGOs in protection of wildlife; and "opportunistic crime security games" have focused on suppressing urban crime. Finally, our security-game-based startup, ARMORWAY, is further enabling the deployment of game-theoretic security resource optimization. I will discuss our use-inspired research in security games that is leading to new research challenges, including algorithms for scaling up security games as well as for handling significant adversarial uncertainty and learning models of human adversary behaviors.
(*) Joint work with a number of current and former PhD students, postdocs all listed at teamcore.usc.edu/security