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Deception in multi-attacker security game with nonfuzzy and fuzzy payoffs

Iranian Journal of Numerical Analysis and Optimization, ISSN: 2423-6969, Vol: 12, Issue: 3, Page: 542-566
2022
  • 1
    Citations
  • 0
    Usage
  • 0
    Captures
  • 1
    Mentions
  • 0
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

  • Citations
    1
  • Mentions
    1
    • News Mentions
      1
      • News
        1

Most Recent News

University of Birjand Researchers Publish Findings in Numerical Analysis (Deception in multi-attacker security game with nonfuzzy and fuzzy payoffs)

2022 NOV 29 (NewsRx) -- By a News Reporter-Staff News Editor at Math Daily News -- Investigators discuss new findings in numerical analysis. According to

Article Description

There is significant interest in studying security games for defense optimization and reducing the effects of attacks on various security systems involving vital infrastructures, financial systems, security, and urban safeguarding centers. Game theory can be used as a mathematical tool to maximize the efficiency of limited security resources. In a game, players are smart, and it is natural for each player (defender or attacker) to try to deceive the opponent using various strategies in order to increase his payoff. Defenders can use deception as an effective means of enhancing security protection by giving incorrect information, hiding specific security resources, or using fake resources. However, despite the importance of deception in security issues, there is no considerable research on this field, and most of the works focus on deception in cyber environments. In this paper, a mixed-integer linear programming problem is proposed to allocate forces efficiently in a security game with multiple attackers using game theory analysis. The important subjects of information are their credibility and reliability. Especially when the defender uses deceptive defense forces, there are more ambiguity and uncertainty. Security game with Z-number payoffs is considered to apply both ambiguities in the payoffs and the reliability of earning these payoffs. Finally, the proposed method is illustrated by some numerical examples.

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