Reaction-diffusion modeling of malware propagation in mobile wireless sensor networks

Abstract

Mobile Wireless Sensor Networks (MWSNs) are employed in many fields, such as intelligent transportation, community health monitoring, and animal behavior monitoring. However, MWSNs may be vulnerable to malicious interference because of the large-scale characteristics. One of the threats is to inject malware into some nodes, especially mobile nodes. When a contaminated node communicates with its neighbors, multiple copies of the malware are transmitted to its neighbors, which may destroy nodes, block regular communications, or even damage the integrity of regular data packets. This work develops a modeling framework which mathematically characterizes the process of malware propagation in MWSNs based on the theory of reaction-diffusion equation. Our proposed model can efficiently predict the temporal dynamic behavior and spatial distribution of malware propagation over time, so that targeted immunization measures can be taken on infected nodes, whereas most of the existing models for malware propagation can only predict the temporal dynamic behavior rather than the spatial distribution of malware propagation over time. We conduct extensive simulations on large-scale MWSNs to evaluate the proposed model. The simulation results indicate that the proposed model and method are efficient, and that the mobile speed, communication range, and packet transmission rate of nodes are the main factors affecting malware propagation in MWSNs.