Malware propagation modeling considering software diversity and immunization

摘要: Abstract In this paper, we propose a discrete-time susceptible–exposed–infected–recovered–susceptible (SEIRS) epidemic model of malware propagation in scale-free networks (SFNs) with considering software diversity. We study dynamical behavior the SEIRS model, which is determined by threshold (i.e., basic reproductive ratio). With threshold, can predict whether propagates or not. Also, using coloring algorithm, number diverse packages installed on nodes calculated and used as parameter to prevent spreading. Furthermore, investigate global dynamics analyze stability malware-free equilibrium. The evaluated results numerical simulations. Simulation show that proposed considers diversity, more effective than other existing models. have compared different immunization mechanisms, shown targeted better random for controlling spreading SFNs.