Toward the Adoption of Secure Cyber Digital Twins to Enhance Cyber-Physical Systems Security

Cyber-Physical Systems (CPSs) and Digital Twins (DTs) currently represent the two most notable examples of cyber-physical integration enabled by modern ICT technologies, and their adoption is becoming predominant to implement and analyse complex systems in several application domains. So-called cyber DTs are increasingly being used to carry out security analysis, monitoring and testing on the virtual replicas of complex systems rather than on the physical counterparts, especially when these may not be directly feasible due to cost and other constraints. However, since physical and virtual replicas live side by side in complex ecosystems, the need for secure and trustworthy DTs arises. In this paper, we introduce a preliminary conceptual framework aimed to increase the level of security of a complex CPS by leveraging a cyber DT providing advanced anomaly detection capabilities, achieved by means of state-of-art machine learning solutions (i.e., federated learning). The framework will also address the security and trustworthiness of the cyber DT itself, by leveraging both HW and SW solutions to support a secure communication and storage of the critical data exchanged among the physical and virtual worlds. To this aim, the integration of the blockchain technology into the DT architecture will be investigated.