Discrete stochastic modelling of computer viruses prevalence on a reduced scale-free network
by Mohamed Essouifi; Abdelfattah Achahbar
International Journal of Computer Applications in Technology (IJCAT), Vol. 63, No. 3, 2020

Abstract: We construct a stochastic version of the deterministic epidemiological model, introduced by Yang and Yang in 2014, to study computer viruses spreading across a network with two degrees. We compare the results expected by these two approaches. To be closer to real situations, where randomness is always present, we use the discrete time Markov chain method to explore the dynamic behaviour of infection and susceptibility densities of nodes in the network. Monte Carlo simulations, in good agreement with the deterministic approach especially when the proportion N1/N2 increases, lead to the conclusion that any attempt to entirely eradicate network viruses would prove unavailing. As a consequence, the only alternative choice is to contain their prevalence by adopting countermeasures. Our stochastic modelling approach is systematic and shows a good skill in predicting the dynamic behaviour of the computer virus propagation.

Online publication date: Thu, 03-Sep-2020

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