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A game theoretic approach to cyber security risk management

Author

Listed:
  • Scott Musman
  • Andrew Turner

Abstract

This paper describes the Cyber Security Game (CSG). Cyber Security Game is a method that has been implemented in software that quantitatively identifies cyber security risks and uses this metric to determine the optimal employment of security methods for any given investment level. Cyber Security Game maximizes a system’s ability to operate in today’s contested cyber environment by minimizing its mission risk. The risk score is calculated by using a mission impact model to compute the consequences of cyber incidents and combining that with the likelihood that attacks will succeed. The likelihood of attacks succeeding is computed by applying a threat model to a system topology model and defender model. Cyber Security Game takes into account the widespread interconnectedness of cyber systems, where defenders must defend all multi-step attack paths and an attacker only needs one to succeed. It employs a game theoretic solution using a game formulation that identifies defense strategies to minimize the maximum cyber risk (MiniMax). This paper discusses the methods and models that compose Cyber Security Game . A limited example of a Point of Sale system is used to provide specific demonstrations of Cyber Security Game models and analyses.

Suggested Citation

  • Scott Musman & Andrew Turner, 2018. "A game theoretic approach to cyber security risk management," The Journal of Defense Modeling and Simulation, , vol. 15(2), pages 127-146, April.
  • Handle: RePEc:sae:joudef:v:15:y:2018:i:2:p:127-146
    DOI: 10.1177/1548512917699724
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    References listed on IDEAS

    as
    1. Kunreuther, Howard & Heal, Geoffrey, 2003. "Interdependent Security," Journal of Risk and Uncertainty, Springer, vol. 26(2-3), pages 231-249, March-May.
    2. Vicki M. Bier, 2007. "Choosing What to Protect," Risk Analysis, John Wiley & Sons, vol. 27(3), pages 607-620, June.
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    Cited by:

    1. Dipankar Dasgupta & Zahid Akhtar & Sajib Sen, 2022. "Machine learning in cybersecurity: a comprehensive survey," The Journal of Defense Modeling and Simulation, , vol. 19(1), pages 57-106, January.

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