Game Theory for Security: An Important Challenge for Multiagent Systems

The goal of this paper is to introduce a real-world challenge problem for researchers in multiagent systems and beyond, where our collective efforts may have a significant impact on activities in the real-world. The challenge is in applying game theory for security: Our goal is not only to introduce the problem, but also to provide exemplars of initial successes of deployed systems in this challenge problem arena, some key open research challenges and pointers to getting started in this research.

[1]  Vincent Conitzer,et al.  Solving Stackelberg games with uncertain observability , 2011, AAMAS.

[2]  Milind Tambe,et al.  Towards Optimal Patrol Strategies for Urban Security in Transit Systems , 2011 .

[3]  Bo An,et al.  Multi-objective optimization for security games , 2012, AAMAS.

[4]  Tansu Alpcan,et al.  Network Security , 2010 .

[5]  R. Selten,et al.  A Generalized Nash Solution for Two-Person Bargaining Games with Incomplete Information , 1972 .

[6]  Milind Tambe,et al.  Approximation methods for infinite Bayesian Stackelberg games: modeling distributional payoff uncertainty , 2011, AAMAS.

[7]  Rong Yang,et al.  Challenges in Patrolling to Maximize Pristine Forest Area (Position Paper) , 2012, AAAI Spring Symposium: Game Theory for Security, Sustainability, and Health.

[8]  Bo An,et al.  Refinement of Strong Stackelberg Equilibria in Security Games , 2011, AAAI.

[9]  Yevgeniy Vorobeychik,et al.  Computing Randomized Security Strategies in Networked Domains , 2011, Applied Adversarial Reasoning and Risk Modeling.

[10]  K. Pauwels,et al.  Effects of Word-of-Mouth versus Traditional Marketing: Findings from an Internet Social Networking Site , 2009 .

[11]  A. Tversky,et al.  Prospect theory: an analysis of decision under risk — Source link , 2007 .

[12]  Bo An,et al.  GUARDS and PROTECT: next generation applications of security games , 2011, SECO.

[13]  Manish Jain,et al.  Game theory for security: Key algorithmic principles, deployed systems, lessons learned , 2012, 2012 50th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

[14]  Manish Jain,et al.  Software Assistants for Randomized Patrol Planning for the LAX Airport Police and the Federal Air Marshal Service , 2010, Interfaces.

[15]  R. McKelvey,et al.  Quantal Response Equilibria for Normal Form Games , 1995 .

[16]  Sarit Kraus,et al.  An efficient heuristic approach for security against multiple adversaries , 2007, AAMAS '07.

[17]  Manish Jain,et al.  Security Games with Arbitrary Schedules: A Branch and Price Approach , 2010, AAAI.

[18]  Bo An,et al.  Mixed-Initiative Optimization in Security Games: A Preliminary Report , 2011, AAAI Spring Symposium: Help Me Help You: Bridging the Gaps in Human-Agent Collaboration.

[19]  Rong Yang,et al.  Improving Resource Allocation Strategy against Human Adversaries in Security Games , 2011, IJCAI.

[20]  Milind Tambe,et al.  Deployed Security Games for Patrol Planning , 2013 .

[21]  Sarit Kraus,et al.  Robust solutions to Stackelberg games: Addressing bounded rationality and limited observations in human cognition , 2010, Artif. Intell..

[22]  Milind Tambe,et al.  TRUSTS: Scheduling Randomized Patrols for Fare Inspection in Transit Systems , 2012, IAAI.

[23]  Branislav Bosanský,et al.  Game-theoretic resource allocation for malicious packet detection in computer networks , 2012, AAMAS.

[24]  Milind Tambe,et al.  Security and Game Theory - Algorithms, Deployed Systems, Lessons Learned , 2011 .

[25]  Vincent Conitzer,et al.  Complexity of Computing Optimal Stackelberg Strategies in Security Resource Allocation Games , 2010, AAAI.

[26]  Bo An,et al.  PROTECT: a deployed game theoretic system to protect the ports of the United States , 2012, AAMAS.

[27]  Ariel Rubinstein,et al.  A Course in Game Theory , 1995 .

[28]  Sarit Kraus,et al.  Playing games for security: an efficient exact algorithm for solving Bayesian Stackelberg games , 2008, AAMAS.

[29]  B. Stengel,et al.  Leadership with commitment to mixed strategies , 2004 .

[30]  Sarit Kraus,et al.  Deployed ARMOR protection: the application of a game theoretic model for security at the Los Angeles International Airport , 2008, AAMAS 2008.

[31]  Nicholas J. Howard,et al.  Finding optimal strategies for influencing social networks in two player games , 2010 .

[32]  Sarit Kraus,et al.  A graph-theoretic approach to protect static and moving targets from adversaries , 2010, AAMAS.

[33]  Milind Tambe,et al.  GUARDS: game theoretic security allocation on a national scale , 2011, AAMAS.

[34]  Milind Tambe,et al.  A Framework for Evaluating Deployed Security Systems: Is There a Chink in your ARMOR? , 2010, Informatica.

[35]  Vincent Conitzer,et al.  Computing the optimal strategy to commit to , 2006, EC '06.

[36]  Manish Jain,et al.  Risk-Averse Strategies for Security Games with Execution and Observational Uncertainty , 2011, AAAI.

[37]  Vincent Conitzer,et al.  Security Games with Multiple Attacker Resources , 2011, IJCAI.

[38]  Milind Tambe,et al.  Security and Game Theory: IRIS – A Tool for Strategic Security Allocation in Transportation Networks , 2011, AAMAS 2011.

[39]  Nicola Basilico,et al.  Leader-follower strategies for robotic patrolling in environments with arbitrary topologies , 2009, AAMAS.

[40]  Vincent Conitzer,et al.  A double oracle algorithm for zero-sum security games on graphs , 2011, AAMAS.

[41]  A. Tversky,et al.  Prospect theory: analysis of decision under risk , 1979 .