Interoperable Cyber Physical Systems for Smart Infrastructure: A Resilience First Security Framework

Cyber-Physical Systems (CPS) are the foundation of current smart infrastructure, but the growing interoperability of heterogeneous CPS elements makes them highly susceptible to cascading cyber-physical attacks. To overcome this issue, the paper presents a resilience-first security framework that combines data quality improvement, interoperability-conscious dependency modeling, and system-level risk and resilience analysis. The suggested method is tested using the SWaT industrial water treatment dataset, a collection of multivariate time-series data sampled at 1 Hz. CPS subsystems are decomposed and represented in the form of dependency graphs, and anomaly detection is performed through multivariate feature engineering. A CPS-aware data repair mechanism is used to cope with severe data incompleteness. Experimental findings indicate that the proposed repair method reduces approximately 7 × 10⁶ missing values to nearly zero, achieving almost 100% data completeness. Dependency-based risk analysis demonstrates that during an attack, system risk increases to the range of 0.85–0.95 for more than 30,000 samples. Chemical Dosing (≈0.75) and Distribution (≈0.65) are major contributors to risk propagation in subsystem analysis. Resilience evaluation shows rapid detection (1–2 samples), recovery within approximately 25 samples, and a composite resilience index of 0.03, validating the effectiveness of the proposed framework in enhancing CPS robustness and recovery.