IDEAS home Printed from https://ideas.repec.org/a/spr/telsys/v86y2024i2d10.1007_s11235-024-01130-9.html
   My bibliography  Save this article

Tripartite evolutionary game in the process of network attack and defense

Author

Listed:
  • Zigang Chen

    (Chongqing University of Posts and Telecommunications
    Sichuan Police College)

  • Chaochao Fan

    (Chongqing University of Posts and Telecommunications)

  • Tao Leng

    (Sichuan Police College)

  • Long Chen

    (Chongqing University of Posts and Telecommunications)

  • Yuhong Liu

    (Santa Clara University)

  • Xiaoyong Li

    (Beijing University of Posts and Telecommunications)

  • Dongfeng Yuan

    (Nanyang Institute of Technology)

Abstract

At present, confrontations in cyberspace are becoming increasingly fierce, and network attacks and defenses have become the main form of confrontation between parties in cyberspace. The maximum benefit can be obtained by using scientific decision-making. Traditional network attack and defense research mainly focuses on the relationship between network attackers and network defenders, but more is need to explain the benefits of the evolution of network attacks and defenses. Given this, this paper constructs a tripartite evolutionary game model among network attackers, network defenders, and government regulators, analyzes the evolutionary stability of each participant’s strategy choice, discusses the influence of each element on the tripartite strategic choices, and further analyzes the stability of the equilibrium point of the tripartite evolutionary system. The research results show that (1) the timely supervision of the network by the government supervision department is conducive to enhancing the construction of network security and has strategic significance for the security of cyberspace; (2) the network defense department can obtain more effective defense measures when being attacked by the network; (3) the network defense party can analyze the strategic defense requirements that are more in line with its own benefits. Finally, we use Matlab2021a to conduct simulation analysis, verify the effectiveness of the evolutionary game model under different initial conditions, and put forward reasonable suggestions for network defenders and government regulators according to the conclusions of the analysis.

Suggested Citation

  • Zigang Chen & Chaochao Fan & Tao Leng & Long Chen & Yuhong Liu & Xiaoyong Li & Dongfeng Yuan, 2024. "Tripartite evolutionary game in the process of network attack and defense," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 86(2), pages 351-361, June.
    • Handle: RePEc:spr:telsys:v:86:y:2024:i:2:d:10.1007_s11235-024-01130-9
    DOI: 10.1007/s11235-024-01130-9
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11235-024-01130-9
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11235-024-01130-9?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Chandra Naik & Pushparaj D. Shetty, 2022. "FLAG: fuzzy logic augmented game theoretic hybrid hierarchical clustering algorithm for wireless sensor networks," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 79(4), pages 559-571, April.
    2. Zahra Rashidi & Vesal Hakami, 2023. "Distributed content placement in cache-enabled small cell networks in the presence of malicious users," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 82(3), pages 345-362, March.
    3. El Mehdi Kandoussi & Mohamed Hanini & Iman Mir & Abdelkrim Haqiq, 2020. "Toward an integrated dynamic defense system for strategic detecting attacks in cloud networks using stochastic game," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 73(3), pages 397-417, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chandra Naik & D. Pushparaj Shetty, 2025. "Multi-attribute decision making approach for energy efficient sensor placement and clustering in wireless sensor networks," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 88(1), pages 1-17, March.
    2. Yanting Zhang & Zhe Zhu & Wei Ning & Amir M. Fathollahi-Fard, 2022. "An Improved Optimization Algorithm Based on Density Grid for Green Storage Monitoring System," Sustainability, MDPI, vol. 14(17), pages 1-19, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:telsys:v:86:y:2024:i:2:d:10.1007_s11235-024-01130-9. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.