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Modeling and analyzing of botnet interactions

Author

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  • Song, Li-Peng
  • Jin, Zhen
  • Sun, Gui-Quan

Abstract

The dynamics of interacting botnets and the effects of the strategies selected by interacting botnet owners on the spread of botnets remain unclear. As a result, in this paper, we present a botnet interaction model, obtained by coupling a fast evolutionary game dynamics to a slow population dynamics model, in which two botnet types are considered. We analyze the fast evolutionary game model and obtain two stable equilibria. Additionally, we substitute them into the complete model and get two reduced models. Such models allow us to study the effects of strategies selected by botnet owners. Analysis of the models shows that when all owners adopt the cooperative strategy both types of botnets can survive with much lower contact rates. However, while they choose the competitive strategy one type of botnet will become extinct and the other will persist with a lower infection rate. The equilibrium conditions of the evolutionary game model, which can guide us in designing effective counter-botnet methods, are also obtained.

Suggested Citation

  • Song, Li-Peng & Jin, Zhen & Sun, Gui-Quan, 2011. "Modeling and analyzing of botnet interactions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(2), pages 347-358.
    • Handle: RePEc:eee:phsmap:v:390:y:2011:i:2:p:347-358
    DOI: 10.1016/j.physa.2010.10.001
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    Cited by:

    1. Dubey, Ved Prakash & Kumar, Rajnesh & Kumar, Devendra, 2020. "A hybrid analytical scheme for the numerical computation of time fractional computer virus propagation model and its stability analysis," Chaos, Solitons & Fractals, Elsevier, vol. 133(C).
    2. Pan, Wei & Jin, Zhen, 2018. "Edge-based modeling of computer virus contagion on a tripartite graph," Applied Mathematics and Computation, Elsevier, vol. 320(C), pages 282-291.
    3. Kaakai, Sarah & El Karoui, Nicole, 2023. "Birth Death Swap population in random environment and aggregation with two timescales," Stochastic Processes and their Applications, Elsevier, vol. 162(C), pages 218-248.

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