Game-­theoretic Resource Allocation with Real-­time Probabilistic Surveillance Information

WenJun Ma, Weiru Liu, Kevin McAreavey

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)
140 Downloads (Pure)

Abstract

Game-theoretic security resource allocation problems have generated significant interest in the area of designing and developing security systems. These approaches traditionally utilize the Stackelberg game model for security resource scheduling in order to improve the protection of critical assets. The basic assumption in Stackelberg games is that a defender will act first, then an attacker will choose their best response after observing the defender’s strategy commitment (e.g., protecting a specific asset). Thus, it requires an attacker’s full or partial observation of a defender’s strategy. This assumption is unrealistic in real-time threat recognition and prevention. In this paper, we propose a new solution concept (i.e., a method to predict how a game will be played) for deriving the defender’s optimal strategy based on the principle of acceptable costs of minimax regret. Moreover, we demonstrate the advantages of this solution concept by analyzing its properties.
Original languageEnglish
Title of host publicationSymbolic and Quantitative Approaches to Reasoning with Uncertainty - Proceedings of 13th European Conference, ECSQARU 2015
EditorsSebastien Destercke, Thierry Denoeux
PublisherSpringer
Pages151-161
Number of pages11
ISBN (Electronic)978-3-319-20807-7
ISBN (Print)978-3-319-20806-0
DOIs
Publication statusPublished - 12 Jul 2015
EventThe 13th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU) 2015 - Compiegne, France
Duration: 15 Jul 201517 Jul 2015

Publication series

NameLecture Notes in Artificial Intelligence
ISSN (Print)0302-9743

Conference

ConferenceThe 13th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU) 2015
CountryFrance
CityCompiegne
Period15/07/201517/07/2015

Fingerprint

Security systems
Resource allocation
Scheduling
Costs

Cite this

Ma, W., Liu, W., & McAreavey, K. (2015). Game-­theoretic Resource Allocation with Real-­time Probabilistic Surveillance Information. In S. Destercke, & T. Denoeux (Eds.), Symbolic and Quantitative Approaches to Reasoning with Uncertainty - Proceedings of 13th European Conference, ECSQARU 2015 (pp. 151-161). (Lecture Notes in Artificial Intelligence). Springer. https://doi.org/10.1007/978-3-319-20807-7_14
Ma, WenJun ; Liu, Weiru ; McAreavey, Kevin. / Game-­theoretic Resource Allocation with Real-­time Probabilistic Surveillance Information. Symbolic and Quantitative Approaches to Reasoning with Uncertainty - Proceedings of 13th European Conference, ECSQARU 2015. editor / Sebastien Destercke ; Thierry Denoeux. Springer, 2015. pp. 151-161 (Lecture Notes in Artificial Intelligence).
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title = "Game-­theoretic Resource Allocation with Real-­time Probabilistic Surveillance Information",
abstract = "Game-theoretic security resource allocation problems have generated significant interest in the area of designing and developing security systems. These approaches traditionally utilize the Stackelberg game model for security resource scheduling in order to improve the protection of critical assets. The basic assumption in Stackelberg games is that a defender will act first, then an attacker will choose their best response after observing the defender’s strategy commitment (e.g., protecting a specific asset). Thus, it requires an attacker’s full or partial observation of a defender’s strategy. This assumption is unrealistic in real-time threat recognition and prevention. In this paper, we propose a new solution concept (i.e., a method to predict how a game will be played) for deriving the defender’s optimal strategy based on the principle of acceptable costs of minimax regret. Moreover, we demonstrate the advantages of this solution concept by analyzing its properties.",
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Ma, W, Liu, W & McAreavey, K 2015, Game-­theoretic Resource Allocation with Real-­time Probabilistic Surveillance Information. in S Destercke & T Denoeux (eds), Symbolic and Quantitative Approaches to Reasoning with Uncertainty - Proceedings of 13th European Conference, ECSQARU 2015. Lecture Notes in Artificial Intelligence, Springer, pp. 151-161, The 13th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU) 2015, Compiegne, France, 15/07/2015. https://doi.org/10.1007/978-3-319-20807-7_14

Game-­theoretic Resource Allocation with Real-­time Probabilistic Surveillance Information. / Ma, WenJun; Liu, Weiru; McAreavey, Kevin.

Symbolic and Quantitative Approaches to Reasoning with Uncertainty - Proceedings of 13th European Conference, ECSQARU 2015. ed. / Sebastien Destercke; Thierry Denoeux. Springer, 2015. p. 151-161 (Lecture Notes in Artificial Intelligence).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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T1 - Game-­theoretic Resource Allocation with Real-­time Probabilistic Surveillance Information

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N2 - Game-theoretic security resource allocation problems have generated significant interest in the area of designing and developing security systems. These approaches traditionally utilize the Stackelberg game model for security resource scheduling in order to improve the protection of critical assets. The basic assumption in Stackelberg games is that a defender will act first, then an attacker will choose their best response after observing the defender’s strategy commitment (e.g., protecting a specific asset). Thus, it requires an attacker’s full or partial observation of a defender’s strategy. This assumption is unrealistic in real-time threat recognition and prevention. In this paper, we propose a new solution concept (i.e., a method to predict how a game will be played) for deriving the defender’s optimal strategy based on the principle of acceptable costs of minimax regret. Moreover, we demonstrate the advantages of this solution concept by analyzing its properties.

AB - Game-theoretic security resource allocation problems have generated significant interest in the area of designing and developing security systems. These approaches traditionally utilize the Stackelberg game model for security resource scheduling in order to improve the protection of critical assets. The basic assumption in Stackelberg games is that a defender will act first, then an attacker will choose their best response after observing the defender’s strategy commitment (e.g., protecting a specific asset). Thus, it requires an attacker’s full or partial observation of a defender’s strategy. This assumption is unrealistic in real-time threat recognition and prevention. In this paper, we propose a new solution concept (i.e., a method to predict how a game will be played) for deriving the defender’s optimal strategy based on the principle of acceptable costs of minimax regret. Moreover, we demonstrate the advantages of this solution concept by analyzing its properties.

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Ma W, Liu W, McAreavey K. Game-­theoretic Resource Allocation with Real-­time Probabilistic Surveillance Information. In Destercke S, Denoeux T, editors, Symbolic and Quantitative Approaches to Reasoning with Uncertainty - Proceedings of 13th European Conference, ECSQARU 2015. Springer. 2015. p. 151-161. (Lecture Notes in Artificial Intelligence). https://doi.org/10.1007/978-3-319-20807-7_14