Digital Twin Vulnerabilities in Industrial Cyber-Physical Systems: A Security Framework for Threat Simulation and Containment

Abstract

Digital Twins (DTs) combined with Industrial Cyber-Physical Systems (CPS) have revolutionized operational efficiency, predictive maintenance, and real-time control within Industry 4.0. Nevertheless, this integration has revealed some critical vulnerabilities in areas such as data synchronization, communication interfaces, model logic, and deployment mechanisms. In this article, the authors propose an extensive security framework for threat simulation and containment that can be applied to DT-enabled CPS. It begins by categorizing distinctive digital twin weaknesses and examining the area of threat based on situational modeling. They provide a layered architecture that includes sandboxing, anomaly detection, model rollback, and a quarantine environment to reduce the compromise of a system. In a case study based on a smart factory, the framework yields better detection accuracy, shorter response times, and minimal downtime in operations when compared to traditional CPS-only defenses. This paper demonstrates the need to seek integrated security mechanisms that incorporate both monitoring, containment, and recovery mechanisms to protect the snowballing DT-CPS ecosystem.