A model for malware propagation in scale-free networks based on rumor spreading process

In this paper, we propose a dynamic model of malware propagation in scale-free networks (SFNs) based on a rumor spreading model. The proposed model, which is called the susceptible-exposed-infectious-recovered-susceptible with a vaccination state (SEIRS-V) model, illustrates the dynamics of malware propagation with respect to time in SFNs. The model considers the impact of software diversity to halt the outbreak of malware in networks. Using the SEIRS-V model, we derive the basic reproductive ratio that governs whether or not a malware is extinct. Furthermore, we calculate the number of diverse software packages installed on computer nodes that can be introduced as a parameter to prevent malware spreading. We accomplish the systematic analysis of the model and represent the local and global stability of malware-free equilibrium. Using numerical simulations, we examine the theoretical analysis. The effects of diversification and vaccination on the model are investigated. Simulation results demonstrate that the model is more effective than other existing models of malware propagation, in terms of reducing the density of infected node.