Complex Dynamic Analysis of a Delayed Cross-Diffusion Malware Propagation Model with Quarantine Strategies

As the application domains of Internet of Things (IoT) expand, IoT systems have been facing significant cybersecurity threats, particularly malware attacks. Effectively controlling the spread of malware has become a critical issue that requires urgent attention. This paper develops a delayed cross-diffusion malware propagation model with quarantine strategies in 2D space, aiming to describe and control the propagation of malware within IoT systems. The main control targets that we focus on are hotspot areas of malware outbreaks. We use Turing patterns to characterize the severity of malware propagation across different regions. The Turing instability conditions of the model with or without time delay are analyzed. Moreover, conditions for the emergence of different Turing patterns are given. Numerical simulations show that the malware propagation is significantly affected by infection rate, cross-diffusion coefficient, and time delay. Introducing quarantine strategies can effectively control the spread of malware.