A computational propagation model for malware based on the SIR classic model

The main goal of this work is to reformulate the compartmental and deterministic global SIR Kermack-McKendrick model in terms of stochastic and individual-based techniques. Specifically, the novel model proposed is based on the use of a probabilistic cellular automaton. Specific local transition function-sendowed with appropriate epidemiological coefficients are considered with the aim to replicate the sim-ulation results obtained from the global and continuous approach. Moreover, this new model exhibits important improvements with respect to the original Kermack-McKendrick model: different contact topologies can be considered (not only complete networks but also small-world networks and scale-free networks) and also specific and differentiating characteristics of the devices (resistance to infection, number of adjacent infectious nodes, detection and removal coefficients, etc.) and the specimen of mal-ware (virulence) are taken into account. A comparison between both models is introduced by showing that scale-free networks accelerate the propagation process.(c) 2021 Elsevier B.V. All rights reserved.