Security and Game Theory: Algorithms, Deployed Systems, Lessons Learned

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Edition: 1st
Format: Hardcover
Pub. Date: 2011-12-31
Publisher(s): Cambridge Univ Pr
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Summary

Global threats of terrorism, drug-smuggling, and other crimes have led to a significant increase in research on game theory for security. Game theory provides a sound mathematical approach to deploy limited security resources to maximize their effectiveness. A typical approach is to randomize security schedules to avoid predictability, with the randomization using artificial intelligence techniques to take into account the importance of different targets and potential adversary reactions. This book distills the forefront of this research to provide the first and only study of long-term deployed applications of game theory for security for key organizations such as the Los Angeles International Airport police and the U.S. Federal Air Marshals Service. The author and his research group draw from their extensive experience working with security officials to intelligently allocate limited security resources to protect targets, outlining the applications of these algorithms in research and the real world. The book also includes professional perspectives from security experts Erroll G. Southers; Lieutenant Commander Joe DiRenzo III, U.S. Coast Guard; Lieutenant Commander Ben Maule, U.S. Coast Guard; Erik Jensen, U.S. Coast Guard; and Lieutenant Fred S. Bertsch IV, U.S. Coast Guard.

Table of Contents

Acknowledghmentp. xiii
Introductionand Overview of Security Gamesp. 1
Introductionp. 1
Motivation: Security Gamesp. 3
Overview of Part II: Applications of Security Gamesp. 9
Overview of Part III: Algorithmic Advances to Achieve Scale-up in Security Gamesp. 11
Part IV: Toward the Futurep. 17
Summaryp. 23
Security Experts' Perspectives
Lax - Terror Target: The History, the Reason, the Countermeasurep. 27
Introductionp. 27
A Brief History of Significant Eventsp. 27
Terrorism and the Economic Significance of the Aviation Domainp. 34
Aviation Securityp. 36
Lax Terror Historyp. 37
Rand Studyp. 39
Los Angeles World Airports Policep. 41
Terrorist Operational Planning Cyclep. 44
CREATE Pilot Projectp. 45
Summaryp. 49
Maritime Transportation System Security and the Use of Game Theory: A Perfect Match to Address Operational and Tactical Concernsp. 51
Deployed Applications
Deployed ARMOR Protection: The Application of a Game-Theoretic Model for Security at the Los Angeles International Airportp. 67
Introductionp. 67
Related Workp. 69
Security Domain Descriptionp. 70
Approachp. 72
System Architecturep. 76
Design Challengesp. 80
Experimental Resultsp. 81
Summaryp. 86
IRIS - A Tool for Strategic Security Allocation in Transportation Networksp. 88
Introductionp. 88
Federal Air Marshal Servicep. 91
Backgroundp. 92
System Architecturep. 96
Major Challengesp. 98
Organizational Acceptancep. 100
Experimental Resultsp. 102
Summaryp. 104
GUARDS: Game-Theoretic Security Allocation on a National Scalep. 107
Introductionp. 107
Backgroundp. 109
National Deployment Challengesp. 111
System Architecturep. 118
Evaluationp. 119
Lessons in Transitioning Research into Practicep. 124
Related Work and Summaryp. 125
Efficient Algorithms for Massive Security Games
Coordinating Randomized Policies for Increasing the Security of Agent Systemsp. 131
Introductionp. 131
Related Workp. 134
Randomization with No Adversary Modep. 135
Randomization Using a Partial Adversary Modelp. 140
Experimental Resultsp. 147
Conclusions and Policy Implicationsp. 153
Computing Optimal Randomized Resource Allocations for Massive Security Gamesp. 156
Introductionp. 156
Game-Theoretic Modeling of Security Gamesp. 157
Motivating Domainsp. 159
A Compact Representation for Multiple Resourcesp. 161
Exploiting Payoff Structurep. 165
Scheduling and Resource Constraintsp. 169
Experimental Evaluationp. 171
Conclusionp. 175
Security Games with Arbitrary Schedules: A Branch and Price Approachp. 177
Introductionp. 177
Sparsp. 178
Aspen Solution Approach and Related Workp. 180
Aspen Column Generationp. 181
Improving Branching and Boundsp. 84
Experimental Resultsp. 186
Conclusionp. 89
Future Research
Effective Solutions for Real-World Stackelberg Games: When Agents Must Deal with Human Uncertaintiesp. 193
Introductionp. 193
Backgroundp. 195
Robust Algorithmsp. 198
Experimentsp. 204
Summary and Related Workp. 211
Approximation Methods for Infinite Bayesian Stackelberg Games: Modeling Distributional Payoff Uncertaintyp. 213
Introductionp. 213
Related Workp. 214
Bayesian Security Gamesp. 215
Solution Methodsp. 219
Experimental Evaluationp. 224
Conclusionp. 23
Stackelberg versus Nash in Security Games: Interchangeability, Equivalence, and Uniquenessp. 233
Introductionp. 233
Motivating Domainsp. 235
Definitions and Notationp. 235
Equilibria in Security Gamesp. 238
Multiple Attacker Resourcesp. 248
Experimental Resultsp. 250
Summary and Related Workp. 252
Evaluating Deployed Decision-Support Systems for Security: Challenges, Analysis, and Approachesp. 254
Introductionp. 254
Background: ARMOR and IRISp. 255
Formulating the Problemp. 257
Evaluating Case Studiesp. 261
Goals for Security Decision-Support Systemsp. 272
Types of Evaluationp. 274
Related Workp. 278
Conclusionsp. 281
Short Bios
Author Biosp. 287
Referencesp. 297
Indexp. 311
Table of Contents provided by Ingram. All Rights Reserved.

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