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Modeling computer virus prevalence with a susceptible-infected-susceptible model with reintroduction

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  • Wierman, John C.
  • Marchette, David J.

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  • Wierman, John C. & Marchette, David J., 2004. "Modeling computer virus prevalence with a susceptible-infected-susceptible model with reintroduction," Computational Statistics & Data Analysis, Elsevier, vol. 45(1), pages 3-23, February.
    • Handle: RePEc:eee:csdana:v:45:y:2004:i:1:p:3-23
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    References listed on IDEAS

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    1. Ball, Frank & Donnelly, Peter, 1995. "Strong approximations for epidemic models," Stochastic Processes and their Applications, Elsevier, vol. 55(1), pages 1-21, January.
    2. Oppenheim, Irwin & Shuler, Kurt E. & Weiss, George H., 1977. "Stochastic theory of nonlinear rate processes with multiple stationary states," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 88(2), pages 191-214.
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    Cited by:

    1. Yonghong Xu & Jianguo Ren, 2016. "Propagation Effect of a Virus Outbreak on a Network with Limited Anti-Virus Ability," PLOS ONE, Public Library of Science, vol. 11(10), pages 1-15, October.
    2. Shang, Jiaxing & Liu, Lianchen & Li, Xin & Xie, Feng & Wu, Cheng, 2015. "Epidemic spreading on complex networks with overlapping and non-overlapping community structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 171-182.
    3. Abdel-Gawad, Hamdy I. & Baleanu, Dumitru & Abdel-Gawad, Ahmed H., 2021. "Unification of the different fractional time derivatives: An application to the epidemic-antivirus dynamical system in computer networks," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
    4. McKinley, Trevelyan J. & Ross, Joshua V. & Deardon, Rob & Cook, Alex R., 2014. "Simulation-based Bayesian inference for epidemic models," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 434-447.
    5. Singh, Jagdev & Kumar, Devendra & Hammouch, Zakia & Atangana, Abdon, 2018. "A fractional epidemiological model for computer viruses pertaining to a new fractional derivative," Applied Mathematics and Computation, Elsevier, vol. 316(C), pages 504-515.
    6. A.H. Nzokem, 2021. "SIS Epidemic Model Birth-and-Death Markov Chain Approach," International Journal of Statistics and Probability, Canadian Center of Science and Education, vol. 10(4), pages 1-10, July.
    7. Ren, Jianguo & Yang, Xiaofan & Yang, Lu-Xing & Xu, Yonghong & Yang, Fanzhou, 2012. "A delayed computer virus propagation model and its dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 45(1), pages 74-79.
    8. Hohle, Michael & Feldmann, Ulrike, 2007. "RLadyBug--An R package for stochastic epidemic models," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 680-686, October.
    9. Zhang, Chunming & Huang, Haitao, 2016. "Optimal control strategy for a novel computer virus propagation model on scale-free networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 451(C), pages 251-265.
    10. Amador, Julia, 2014. "The stochastic SIRA model for computer viruses," Applied Mathematics and Computation, Elsevier, vol. 232(C), pages 1112-1124.

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