
Security and Game Theory: Algorithms, Deployed Systems, Lessons Learned
by Tambe, Milind-
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Summary
Table of Contents
Acknowledghment | p. xiii |
Introductionand Overview of Security Games | p. 1 |
Introduction | p. 1 |
Motivation: Security Games | p. 3 |
Overview of Part II: Applications of Security Games | p. 9 |
Overview of Part III: Algorithmic Advances to Achieve Scale-up in Security Games | p. 11 |
Part IV: Toward the Future | p. 17 |
Summary | p. 23 |
Security Experts' Perspectives | |
Lax - Terror Target: The History, the Reason, the Countermeasure | p. 27 |
Introduction | p. 27 |
A Brief History of Significant Events | p. 27 |
Terrorism and the Economic Significance of the Aviation Domain | p. 34 |
Aviation Security | p. 36 |
Lax Terror History | p. 37 |
Rand Study | p. 39 |
Los Angeles World Airports Police | p. 41 |
Terrorist Operational Planning Cycle | p. 44 |
CREATE Pilot Project | p. 45 |
Summary | p. 49 |
Maritime Transportation System Security and the Use of Game Theory: A Perfect Match to Address Operational and Tactical Concerns | p. 51 |
Deployed Applications | |
Deployed ARMOR Protection: The Application of a Game-Theoretic Model for Security at the Los Angeles International Airport | p. 67 |
Introduction | p. 67 |
Related Work | p. 69 |
Security Domain Description | p. 70 |
Approach | p. 72 |
System Architecture | p. 76 |
Design Challenges | p. 80 |
Experimental Results | p. 81 |
Summary | p. 86 |
IRIS - A Tool for Strategic Security Allocation in Transportation Networks | p. 88 |
Introduction | p. 88 |
Federal Air Marshal Service | p. 91 |
Background | p. 92 |
System Architecture | p. 96 |
Major Challenges | p. 98 |
Organizational Acceptance | p. 100 |
Experimental Results | p. 102 |
Summary | p. 104 |
GUARDS: Game-Theoretic Security Allocation on a National Scale | p. 107 |
Introduction | p. 107 |
Background | p. 109 |
National Deployment Challenges | p. 111 |
System Architecture | p. 118 |
Evaluation | p. 119 |
Lessons in Transitioning Research into Practice | p. 124 |
Related Work and Summary | p. 125 |
Efficient Algorithms for Massive Security Games | |
Coordinating Randomized Policies for Increasing the Security of Agent Systems | p. 131 |
Introduction | p. 131 |
Related Work | p. 134 |
Randomization with No Adversary Mode | p. 135 |
Randomization Using a Partial Adversary Model | p. 140 |
Experimental Results | p. 147 |
Conclusions and Policy Implications | p. 153 |
Computing Optimal Randomized Resource Allocations for Massive Security Games | p. 156 |
Introduction | p. 156 |
Game-Theoretic Modeling of Security Games | p. 157 |
Motivating Domains | p. 159 |
A Compact Representation for Multiple Resources | p. 161 |
Exploiting Payoff Structure | p. 165 |
Scheduling and Resource Constraints | p. 169 |
Experimental Evaluation | p. 171 |
Conclusion | p. 175 |
Security Games with Arbitrary Schedules: A Branch and Price Approach | p. 177 |
Introduction | p. 177 |
Spars | p. 178 |
Aspen Solution Approach and Related Work | p. 180 |
Aspen Column Generation | p. 181 |
Improving Branching and Bounds | p. 84 |
Experimental Results | p. 186 |
Conclusion | p. 89 |
Future Research | |
Effective Solutions for Real-World Stackelberg Games: When Agents Must Deal with Human Uncertainties | p. 193 |
Introduction | p. 193 |
Background | p. 195 |
Robust Algorithms | p. 198 |
Experiments | p. 204 |
Summary and Related Work | p. 211 |
Approximation Methods for Infinite Bayesian Stackelberg Games: Modeling Distributional Payoff Uncertainty | p. 213 |
Introduction | p. 213 |
Related Work | p. 214 |
Bayesian Security Games | p. 215 |
Solution Methods | p. 219 |
Experimental Evaluation | p. 224 |
Conclusion | p. 23 |
Stackelberg versus Nash in Security Games: Interchangeability, Equivalence, and Uniqueness | p. 233 |
Introduction | p. 233 |
Motivating Domains | p. 235 |
Definitions and Notation | p. 235 |
Equilibria in Security Games | p. 238 |
Multiple Attacker Resources | p. 248 |
Experimental Results | p. 250 |
Summary and Related Work | p. 252 |
Evaluating Deployed Decision-Support Systems for Security: Challenges, Analysis, and Approaches | p. 254 |
Introduction | p. 254 |
Background: ARMOR and IRIS | p. 255 |
Formulating the Problem | p. 257 |
Evaluating Case Studies | p. 261 |
Goals for Security Decision-Support Systems | p. 272 |
Types of Evaluation | p. 274 |
Related Work | p. 278 |
Conclusions | p. 281 |
Short Bios | |
Author Bios | p. 287 |
References | p. 297 |
Index | p. 311 |
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