Dynamic Model of Malware Propagation Based on Community Structure in Heterogeneous Networks

Abstract

Heterogeneous networks are used as models for many real-world networks and systems due to their diversity in structures, characteristics, and connections. Consequently, the study of these networks helps to better understand the vulnerabilities and the malware propagation in real complex systems. In this paper, the impact of community structure, which is one of the main characteristics of heterogeneous networks, on malware propagation is investigated. The Vulnerable-Unprotected-Malfunctioned-Recovered-Vulnerable (VUMRV) model is used to simulate the dynamics and the propagation process. The process of density change among network members in all states of communities and the entire network, as well as the effect of the secured mechanism, is analyzed. The equilibrium points are obtained by solving the differential equations equivalent to the proposed model. In addition, the basic reproduction number $\left(R_0\right)$ as a metric is computed by using the next generation matrix method to determine the potential impact of the malware and its epidemic spread in the network. Numerical simulations are performed to validate and compare the theoretical results, and analyze the combined impact of the network topology and security strategies on the final epidemic situation. The results clearly demonstrate the effectiveness of using the community structure property of heterogeneous networks as a malware propagation control method.