Securing Self-aware Cyber-physical Systems Using Digital Twins

Self-aware cyber-physical systems (SA-CPSs) integrate CPSs with the capability to dynamically perceive, interpret, and respond to their operational parameters and limitations. In critical infrastructures, security of such systems is paramount due to potential cascading effects of cyber-attacks. While SA-CPSs face both common and targeted threats, existing research primarily emphasizes self-awareness in non-security domains. This study addresses this gap by leveraging digital twins—software models which are synchronized virtual replicas of physical SA-CPS—to enhance security through real-time compliance monitoring and automated responses. By utilizing the Architecture Development Method (ADM) principles, this research aims to define the compliant state, compare the current state with compliant state, identify security gaps and implement corrective actions via the SA-CPS’ digital twin. The outcome seeks to furnish a high-level architecture that can be used to enhance SA-CPS’ security while identifying key components, integration processes and future research directions.