Deployed ARMOR Protection: The Application of a Game-Theoretic Model for Security at the Los Angeles International Airport

Pita, James; Jain, Manish; Marecki, Janusz; Ordóñez, Fernando; Portway, Christopher; Tambe, Milind; Western, Craig; Paruchuri, Praveen; Kraus, Sarit

doi:10.1017/cbo9780511973031.004

Cited by 151 publications

(258 citation statements)

References 5 publications

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“…Stackelberg games are often used to model the interaction between defenders and adversaries (attackers) in security settings [12,16,17]. In such games, there is a defender, who plays the role of leader, taking action first, and a follower (attacker) who responds to the leader's actions.…”

Section: Securitymentioning

confidence: 99%

“…Background ARMOR (Assistant for Randomized Monitoring Over Routes) was our first application of security games [12]. It is deployed at the Los Angeles International Airport (LAX) since 2007.…”

Section: Securitymentioning

confidence: 99%

“…Given that LAX may be under surveillance by adversaries, the question is where and when to have the canine units patrol the different terminals. The foundation of ARMOR are algorithms for solving Bayesian Stackelberg games [11,12]; they recommend a randomized pattern for setting up checkpoints and canine patrols so as to maintain unpredictability.…”

Section: Securitymentioning

confidence: 99%

“…In security, many scenarios are naturally modeled as a game; much of our own research has focused on the use of Bayesian Stackelberg games for security resource allocation [12,17,16]. These games typically involve a defender who acts first by setting up a security policy and an adversary who may conduct surveillance and then react; in our work, given particular restrictions on payoffs in these games, they are often labeled as security games [16].…”

Section: Introductionmentioning

confidence: 99%

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Game Theory and Human Behavior: Challenges in Security and Sustainability

Rong

Tambe

Jain

et al. 2011

Algorithmic Decision Theory

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Abstract. Security and sustainability are two critical global challenges that involve the interaction of many intelligent actors. Game theory provides a sound mathematical framework to model such interactions, and computational game theory in particular has a promising role to play in helping to address key aspects of these challenges. Indeed, in the domain of security, we have already taken some encouraging steps by successfully applying game-theoretic algorithms to real-world security problems: our algorithms are in use by agencies such as the US coast guard, the Federal Air Marshals Service, the LAX police and the Transportation Security Administration. While these applications of game-theoretic algorithms have advanced the state of the art, this paper lays out some key challenges as we continue to expand the use of these algorithms in real-world domains. One such challenge in particular is that classical game theory makes a set of assumptions of the players, which may not be consistent with real-world scenarios, especially when humans are involved. To actually model human behavior within game-theoretic framework, it is important to address the new challenges that arise due to the presence of human players: (i) human bounded rationality; (ii) limited observations and imperfect strategy execution; (iii) large action spaces. We present initial solutions to these challenges in context of security games. For sustainability, we lay out our initial efforts and plans, and key challenges related to human behavior in the loop.

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Section: Securitymentioning

confidence: 99%

Section: Securitymentioning

confidence: 99%

Section: Securitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Game Theory and Human Behavior: Challenges in Security and Sustainability

Rong

Tambe

Jain

et al. 2011

Algorithmic Decision Theory

Self Cite

View full text Add to dashboard Cite

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“…To partially overcome this problem, researchers applied game theoretic methods that model a security scenario s i as a security game [3,13]. In such a security game, a defender agent and an attacker agent are modelled as the respective row and column players of this game.…”

Section: Introductionmentioning

confidence: 99%

Agent-Based Modelling for Security Risk Assessment

Janssen

Sharpanskykh

2017

Lecture Notes in Computer Science

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Abstract. Security Risk Assessment is commonly performed by using traditional methods based on linear probabilistic tools and informal expert judgements. These methods lack the capability to take the inherent dynamic and intelligent nature of attackers into account. To partially address the limitations, researchers applied game theory to study security risks. However, these methods still rely on traditional methods to determine essential model parameters, such as payoff values. To overcome the limitations of traditional methods, we propose an approach which combines agent-based modelling with Monte Carlo simulations. Agent-based models allow more realistic representation of essential aspects and processes of socio-technical systems at cognitive, social and organisational levels. Such models can be used to estimate risks and parameters related to them. An application of the approach is illustrated by a case study of an airport security checkpoint.

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Open‐loop Stackelberg learning solution for hierarchical control problems

Vamvoudakis

Lewis²,

Dixon

2017

Adaptive Control & Signal

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This work presents a novel framework based on adaptive learning techniques to solve the continuous-time open-loop Stackelberg games. The method yields real-time approximations of the game value and convergence of the policies to the open-loop Stackelberg-equilibrium solution, while also guaranteeing asymptotic stability of the equilibrium point of the closed-loop system. It is implemented as a separate actor/critic parametric network approximator structure for every player and involves simultaneous continuous-time adaptation. To introduce and implement the hierarchical structure to the coupled optimization problem, we adjoin to the leader the controller dynamics of the follower. A persistence of excitation condition guarantees convergence of both critics to the actual game values that eventually solve the hierarchical optimization problem. A simulation example shows the efficacy of the proposed approach. KEYWORDS leader-follower coupled Riccati equations, learning-based adaptation, noncooperative games, Stackelberg equilibrium Int J Adapt Control Signal Process. 2019;33:285-299.wileyonlinelibrary.com/journal/acs

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Deployed ARMOR Protection: The Application of a Game-Theoretic Model for Security at the Los Angeles International Airport

Cited by 151 publications

References 5 publications

Game Theory and Human Behavior: Challenges in Security and Sustainability

Game Theory and Human Behavior: Challenges in Security and Sustainability

Agent-Based Modelling for Security Risk Assessment

Open‐loop Stackelberg learning solution for hierarchical control problems

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