SIR1R2: Characterizing Malware Propagation in WSNs With Second Immunization

As an infrastructure of Internet of Things, WSNs (Wireless Sensor Networks) play a more and more important role. However, WSNs are vulnerable to malware and malware can destroy their data security and integrity, which motivates us to explore the role of malware propagation in WSNs. First, according to the actual propagation characteristics of malware in the WSNs and the process of the density change of all node types, we propose an epidemiology-based malware propagation model in consideration of a secondary immune mechanism. Then we set up differential equations to describe the propagation model. By solving differential equations, we can obtain two kinds of equilibrium points indicating that the density of all node types tends to be stable in the WSNs. One is to achieve an equilibrium where only susceptible nodes exist in the WSNs. The other is that malware always exists in the WSNs. Moreover, we prove the local and global stability of these two equilibrium points. Eventually, we analyze the influence and effect of the secondary immunity, forgetting mechanism and containment mechanism on malware propagation in the WSNs, and validate the proposed model through simulations.