Targeted Quarantine Strategies Mitigate SIS-model Cyber Epidemics on Complex Networks

Abstract

The rapid expansion of highly connected and heterogeneous digital infrastructures has fundamentally altered the dynamics of cyber epidemics, making it increasingly important to understand how malware propagates under realistic structural and policy conditions. In this study, we employ an SIS epidemic model on complex networks to investigate virus spreading under a range of cybersecurity scenarios, including minimally protected environments, anti-virus, vulnerable legacy systems, mixed security systems, rapidly evolving virus, and targeted quarantine of key nodes. Using simulations on scale-free topologies, we characterize how infection prevalence evolves over time and identify conditions under which outbreaks become explosive versus controlled. Our results show that vulnerable and rapidly evolving virus scenarios lead to fast and almost complete compromise, while antivirus and mixed-security configurations significantly reduce peak infection levels. Most importantly, we demonstrate that targeted quarantine of a small fraction of structurally important nodes can both delay the onset of large scale outbreaks and lower steady state infection, revealing a threshold in the fraction of quarantined nodes which required to alter spreading of computer virus. These findings highlight the critical role of network topology and selective protection in enhancing the resilience of cyber-physical infrastructures.