QUARANTINE-BASED SEIRA MALWARE PROPAGATION MODEL FOR COMPUTER NETWORKS

Abstract

One of the high-profile issue of computer networks is the propagation of Malware and it get disrupted by the malware’s presence. In this study, we extend the classical SEIRA (Susceptible–Exposed–Infectious–Recovered–Antidotal) model by including a quarantined compartment (Q) to represent infected machines that are detected and isolated from the network. In the SEIQRA model, the quarantine approach has been used to halt the infection spread in computer networks. The model’s basic reproduction number (R₀) is derived using next generation approach. We examined the model's local stability in terms in the system's Jacobian for malware free and endemic equilibrium based on the basic reproduction number. Numerical simulations demonstrate that higher quarantine rates and stricter isolation significantly reduce the peak infection size and overall outbreak impact. In order to effectively contain malware, the model emphasizes the significance of integrating quarantine with protective adoption and recovery methods. Finally, numerical methods and MATLAB are employed to solve and simulate the system of equations developed and analysis of the model gives remarkable exposure.