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.
- 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 Scholar
- 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 ScholarCross Ref
- 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 Scholar
- Marten van Dijk, Ari Juels, Alina Oprea, Flipit: The Game of 'Stealthy Takeover'[J]. Journal of Cryptology, 2013, 26(4):655-713.Google ScholarDigital Library
- 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 Scholar
- 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 Scholar
- 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 Scholar
- 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 Scholar
- 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 Scholar
- 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 Scholar
- 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 Scholar
- 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 Scholar
- 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 Scholar
- 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 Scholar
- 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 Scholar
- 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 ScholarCross Ref
- 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 Scholar
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