Usability of Classic SIR and Diffusion Models for Assessing Malware Spread in the Early Stages of Infectious Diseases

As the processes of societal digitalization and the application of artificial intelligence accelerate, the intensity of cybersecurity threats increases accordingly. The purposes behind malware distribution are becoming more criminalized and business oriented. As society becomes increasingly dependent on social networks and digital technologies, and financial, infrastructure, and governance institutions rely more on these technologies, the spread of malware is becoming ever more dangerous. Therefore, it is crucial to predict infection spread risks in a timely manner. Various epidemiological models are used for modeling malware spread, but the choice of specific models is often more intuitive than evidence based. The aim of this article is to assess the suitability of two models from the epidemiological models set, specifically the classic SIR and SIR w/diffusion models, for modeling malware spread. The findings of this study will be valuable for both researchers studying infection spread and cybersecurity specialists.