A Game-Theoretic Approach for Threats Detection and Intervention in Surveillance

Wenjun Ma, Weiru Liu, Paul Miller, Xudong Luo

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

2 Citations (Scopus)


Threat prevention with limited security resources is a challenging problem. An optimal strategy is to eectively predict attackers' targets (or goals) based on current available information, and use such predictions to prevent (or disrupt) their planned attacks. In this paper, we propose a game-theoretic framework to address this challenge which encompasses the following three elements. First, we design a method to analyze an attacker's types in order to determine the most plausible type of an attacker. Second, we propose an approach to predict possible targets of an attack and the course of actions that the attackers may take even when the attackers' types are ambiguous. Third, a game-theoretic based strategy is developed to determine the best protection actions for defenders (security resources).
Original languageEnglish
Title of host publicationInternational Conference on Autonomous Agents and Multi-agent Systems
PublisherIFAAMAS Press
Number of pages2
ISBN (Print)978-1-4503-2738-1
Publication statusPublished - 2014
EventInternational Conference on Autonomous Agents and Multi-agent Systems (AAMAS'14) - Paris, France
Duration: 05 May 201409 May 2014


ConferenceInternational Conference on Autonomous Agents and Multi-agent Systems (AAMAS'14)


  • Security
  • Game theory

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