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Research on Simulation of Network Attack and Defense situation based on Evolutionary Game

Published:13 May 2021Publication History

ABSTRACT

Network attack and defense research is the focus in the field of network security, but most of the existing network attack and defense studies focus on one of the two sides of attacker and defender, which cannot accurately explain the nature of the attack-defense confrontation. It failed to describe and analyze the game behavior at the micro-level and the network attack and defense scenario at the macro level. Aiming at this, this paper firstly establishes a network attack and defense game model based on evolutionary game theory from the point of view of attack-defense confrontation and studies the quantitative methods of attack-defense income, game equilibrium, and strategic confrontation. Then based on NetLogo and improved SI (Susceptible-Infectious) model, the simulation model of network attack and defense is constructed. Finally, the effectiveness of the proposed model and method is verified by simulation experiments, and the countermeasures and suggestions to enhance the network defense capability are analyzed and summarized from the simulation results.

References

  1. Yu Fu, Hongcheng Li, Xiaoping Wu, Detecting APT attacks: A survey from the perspective of big data analysis[J]. Journal on Communications, 2015, 036(011):1-14.Google ScholarGoogle Scholar
  2. Zafar Iqbal, Zahid Anwar. SCERM—A novel framework for automated management of cyber threat response activities[J]. Future Generation Computer Systems, 2020, 2020 (7): 687-708Google ScholarGoogle ScholarCross RefCross Ref
  3. Xiaohu Liu, Hengwei Zhang, Yuchen Zhang, Research on Network Attack and Defense Situation based on Game Theory Model and NetLogo Simulation [J]. Journal of System Simulation,2020,32(10):1918-1926.Google ScholarGoogle Scholar
  4. Marten van Dijk, Ari Juels, Alina Oprea, Flipit: The Game of 'Stealthy Takeover'[J]. Journal of Cryptology, 2013, 26(4):655-713.Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Mingqing Zhang, Xiaohu Liu, Jun Tang, Study on Modeling and Simulation of DDoS Active Defense [J]. Journal of System Simulation, 2014,26(11):2698-2703.Google ScholarGoogle Scholar
  6. Laobing Zhang, Qiming Ruan, Xiaogang Qiu. Two Complementary Methods for Studying Complex Social Systems: Simulation and Game Theory [J]. Journal of System Simulation, 2019,31(10):1960-1969.Google ScholarGoogle Scholar
  7. Hengwei Zhang, Tao Li. Optimal Active Defense Based on Multi-stage Attack-Defense Signaling Game [J]. ACTA ELECTRONICA SINICA, 2017,45(02):431-439.Google ScholarGoogle Scholar
  8. Wei Jiang, Binxing Fang, Zhihong Tian, Research on Defense Strategies Selection Based on Attack-Defense Stochastic Game Model[J]. Journal of Computer Research and Development, 2010(10):44-53.Google ScholarGoogle Scholar
  9. Jianming Huang, Hengwei Zhang, Jindong Wang, Defense strategies selection based on attack-defense evolutionary game model [J]. Journal on Communications, 2017,38(01):168-176.Google ScholarGoogle Scholar
  10. Junnan Yang, Hongqi Zhang, Chuanfu Zhang. Network Defense Decision-Making Method Based on Stochastic Game and Improved WoLF-PHC [J]. Journal of Computer Research and Development, 2019,56(05):942-954.Google ScholarGoogle Scholar
  11. Jianming Huang, Hengwei Zhang. Improving replicator dynamic evolutionary game model for selecting optimal defense strategies [J]. Journal on Communications, 2018,39(01):170-182.Google ScholarGoogle Scholar
  12. Jianming Huang, Hengwei Zhang. A Method for Selecting Defense Strategies Based on Stochastic Evolutionary Game Model [J]. ACTA ELECTRONICA SINICA,2018,46(09):2222-2228.Google ScholarGoogle Scholar
  13. Rong Liu, Fenglan Wang, Fei Wang. Network Attack and Defense Strategy Based on Evolutionary Game Model [J]. Science Technology and Engineering, 2020,20(21):8671-8675.Google ScholarGoogle Scholar
  14. Fengming Liu, Yongsheng Ding. Dynamics analysis of evolutionary game-based trust computing for P2P networks[J]. Application Research of Computers, 2016, 33(8): 2460-2463.Google ScholarGoogle Scholar
  15. Yongchen Guo, Yang Shen. Multi-Agent Modeling and Simulation on China's Marine Energy Channel Security [J]. Journal of System Simulation, 2019, 31(04):655-670.Google ScholarGoogle Scholar
  16. Railsback S, Daniel Ayllón, Berger U, Improving Execution Speed of Models Implemented in NetLogo[J]. Journal of Artificial Societies & Social Simulation, 2017, 20(1):3.Google ScholarGoogle ScholarCross RefCross Ref
  17. H. Zhang, J. Wang, Dingkun Yu, Jihong Han and Tao Li, "Active defense strategy selection based on static Bayesian game," Third International Conference on Cyberspace Technology (CCT 2015), Beijing, 2015, pp. 1-7, doi: 10.1049/cp.2015.0806.Google ScholarGoogle Scholar

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  • Published in

    cover image ACM Other conferences
    ICNCC '20: Proceedings of the 2020 9th International Conference on Networks, Communication and Computing
    December 2020
    157 pages
    ISBN:9781450388566
    DOI:10.1145/3447654

    Copyright © 2020 ACM

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    Publication History

    • Published: 13 May 2021

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