Trends and Applications in Stackelberg Security Games

Debarun Kar (), Thanh H. Nguyen (), Fei Fang (), Matthew Brown (), Arunesh Sinha (), Milind Tambe () and Albert Xin Jiang ()
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Debarun Kar: University of Southern California
Thanh H. Nguyen: University of Southern California
Fei Fang: University of Southern California
Matthew Brown: University of Southern California
Arunesh Sinha: University of Southern California
Milind Tambe: University of Southern California
Albert Xin Jiang: Trinity University

Chapter 28 in Handbook of Dynamic Game Theory, 2018, pp 1223-1269 from Springer

Abstract: Abstract 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 wildlife, forests, and fisheries; or 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, we founded a new “security games” framework that has led to building of decision aids for security agencies around the world. Security games are a novel area of research that is based on computational and behavioral game theory while also incorporating elements of AI planning under uncertainty and machine learning. Today security-games-based decision aids for infrastructure security are deployed in the US and internationally; examples include deployments at ports and ferry traffic with the US Coast Guard, for security of air traffic with the US Federal Air Marshals, and for security of university campuses, airports, and metro trains with police agencies in the US and other countries. 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. In cyber-security domain, the interaction between the defender and adversary is quite complicated with high degree of incomplete information and uncertainty. Recently, applications of game theory to provide quantitative and analytical tools to network administrators through defensive algorithm development and adversary behavior prediction to protect cyber infrastructures has also received significant attention. This chapter provides an overview of use-inspired research in security games including algorithms for scaling up security games to real-world sized problems, handling multiple types of uncertainty, and dealing with bounded rationality and bounded surveillance of human adversaries.

Keywords: Security games; Scalability; Uncertainty; Bounded rationality; Bounded surveillance; Adaptive adversary; Infrastructure security; Wildlife protection (search for similar items in EconPapers)
Date: 2018
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DOI: 10.1007/978-3-319-44374-4_27

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