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Evolutionary dynamics of the interdependent security games on complex network

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  • Wang, Zhen
  • Li, Chaofan
  • Jin, Xing
  • Ding, Hong
  • Cui, Guanghai
  • Yu, Lanping

Abstract

With the development of information technology, the infrastructure between enterprises and the connections between businesses show complex network characteristics. The security investment made by an enterprise in a network has an impact on its neighbors, but also bears the impact of its neighbors’ security investments. Such individual interaction problems are often modeled as interdependent security games (IDS). In this paper, we study IDS models under three different attack scenarios: the total effort, the weakest link and the best shot. We use evolutionary game theory to explore the dynamics of social payoffs and the average social investments of these three models under different network topologies. The results show that under the total effort model, individuals are more inclined to increase their investments, while under the weakest link and best shot models, individuals choose to minimize their investments due to selfishness. Finally, we study the cluster effect under different network structures and find the threshold at which it exists.

Suggested Citation

  • Wang, Zhen & Li, Chaofan & Jin, Xing & Ding, Hong & Cui, Guanghai & Yu, Lanping, 2021. "Evolutionary dynamics of the interdependent security games on complex network," Applied Mathematics and Computation, Elsevier, vol. 399(C).
    • Handle: RePEc:eee:apmaco:v:399:y:2021:i:c:s0096300321000990
    DOI: 10.1016/j.amc.2021.126051
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    References listed on IDEAS

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    Cited by:

    1. Jin, Xing & Tao, Yuchen & Wang, Jingrui & Wang, Chao & Wang, Yongheng & Zhang, Zhouyang & Wang, Zhen, 2023. "Strategic use of payoff information in k-hop evolutionary Best-shot networked public goods game," Applied Mathematics and Computation, Elsevier, vol. 459(C).
    2. Lou, Fangzheng & Li, Feng & Wang, Jing & Wang, Yan, 2022. "Reliable output feedback control for persistent dwell-time switched piecewise-affine systems against deception attacks," Applied Mathematics and Computation, Elsevier, vol. 426(C).

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