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Study of epidemiological based dynamic model of computer viruses for sustainable safeguard against threat propagations

Studies of virus propagation models have significant impact on the development of effective procedure for sustainable safeguard against complicated and emergent computer security threats for individuals as well as organizational systems. These threats act as expert of disguise and manipulation in order to evolve innovative ways to spoil, upset, steal and harm information and resources. The computer virus propagation can be modelled and controlled by establishing similar preventive policies as used in epidemiological studies for population based models. The epidemiological computer virus model is a shifted version of susceptible-infected-removal model which is represented by systems of nonlinear ordinary differential equations. The dynamics of the mathematical model of virus propagations in computer networks are studied for a number of scenarios by exploiting the strength of Adams numerical methods. The comparison of the proposed results is made with implicit backward differentiation as well as Explicit Runge-Kutta methods in order to prove the worth of the algorithm in terms of accuracy, convergence and complexity parameters for solving governing mathematical models of epidemiological computer virus systems.