Author
Listed:
- 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)
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.
Suggested Citation
Debarun Kar & Thanh H. Nguyen & Fei Fang & Matthew Brown & Arunesh Sinha & Milind Tambe & Albert Xin Jiang, 2018.
"Trends and Applications in Stackelberg Security Games,"
Springer Books, in: Tamer Başar & Georges Zaccour (ed.), Handbook of Dynamic Game Theory, chapter 28, pages 1223-1269,
Springer.
Handle:
RePEc:spr:sprchp:978-3-319-44374-4_27
DOI: 10.1007/978-3-319-44374-4_27
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