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Optimal defense strategy based on the mean field game model for cyber security

Author

Listed:
  • Li Miao
  • Lina Wang
  • Shuai Li
  • Haitao Xu
  • Xianwei Zhou

Abstract

With the evolution of research on defense strategies in cyber security, the choice of an optimal strategy has become a key problem in current studies. Focusing on the balance between individual cost and overall network cost, we present an application of mean field game in large-scale defenders in cyber security, where players seek to construct an optimal defense strategy at their minimum cost. The contributions are threefold: first, we propose an individual cost function based on the mean field game in Hilbert space and discuss the overall network cost function, where each player has discrete-time dynamics. Then, the Nash equilibrium of the individual cost function with infinite players is researched. Finally, we establish an optimal condition in which the game equilibrium is the optimal solution to the overall cost function. Numerical examples are provided to illustrate the effectiveness of the presented strategy with an appropriate assumption.

Suggested Citation

  • Li Miao & Lina Wang & Shuai Li & Haitao Xu & Xianwei Zhou, 2019. "Optimal defense strategy based on the mean field game model for cyber security," International Journal of Distributed Sensor Networks, , vol. 15(2), pages 15501477198, February.
    • Handle: RePEc:sae:intdis:v:15:y:2019:i:2:p:1550147719831180
    DOI: 10.1177/1550147719831180
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    References listed on IDEAS

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    1. A. Bensoussan & K. Sung & S. Yam, 2013. "Linear–Quadratic Time-Inconsistent Mean Field Games," Dynamic Games and Applications, Springer, vol. 3(4), pages 537-552, December.
    2. Saim Bin Abdul Khaliq & Muhammad Faisal Amjad & Haider Abbas & Narmeen Shafqat & Hammad Afzal, 2019. "Defence against PUE attacks in ad hoc cognitive radio networks: a mean field game approach," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 70(1), pages 123-140, January.
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