Resilience Assessment of Multi-Layered Cyber-Physical Systems

Thanks to technological advancements, critical infrastructures integrate many smart technologies and become highly connected to the cyber world. This is especially true for Cyber-Physical Systems (CPSs), which combine hardware and software components. Despite the advantages of smart infrastructures, e.g., sustainable energy usage, security, safety enhancement, and predictive algorithms using machine learning, they remain vulnerable to cyber threats and adversarial events such as cyber-attacks. This work focuses on the cyber resilience of CPSs. We propose a methodology leveraging knowledge graph modeling to increase the remediation potential of CPSs and to avoid critical failures that can occur due to cascading effects in complex architectures. We propose an approach based on multi-layered modeling applied to complex systems to achieve this objective. Indeed, a complex system can be considered an overlay of several layers. We use knowledge graphs to model a Secure Water Treatment System (SWaT) test bed subsystem. We conduct a resilience assessment analysis of several designs with a quantitative metric. This resilience analysis, applied to each layer of our models, is also used to highlight critical points, e.g., the key functions or components that are significant for completing a mission.