The impact of individual security awareness deficiencies on malware propagation in scale-free networks

In the era of rapid information technology advancement, network malware proliferates through complex networks, with high-risk nodes serving as critical diffusion sources, posing severe challenges to global cybersecurity. To thoroughly analyze the propagation mechanisms of malware via high-risk nodes and develop effective containment strategies, this study proposes a novel malware propagation model—the ‘Susceptible-High-risk-Exposed-Infected-Recovered-Vaccine (SHEIR-V) model’—based on the classical Susceptible-Infected-Recovered (SIR) framework and the topological features of scale-free networks. Using mean-field theory, we derive the dynamic equations of the SHEIR-V model and analyze its equilibrium points and basic reproduction number(R₀). Results indicate that when R₀⪅1, malware propagation eventually vanishes; when R₀⪆1, it stabilizes into an endemic state. Numerical simulations validate the model’s accuracy, demonstrating that the infection rate of high-risk nodes and their risk exposure levels are positively correlated with propagation speed.