SIMULATION-DRIVEN EMPIRICAL VALIDATION OF CPS-RISE FOR CYBER RESILIENCE IN OIL AND GAS CYBER-PHYSICAL SYSTEMS

ABSTRACT

Cyber-Physical Systems (CPS) support critical oil and gas operations but are increasingly exposed to cyber-physical threats arising from OT-IT convergence, cloud connectivity, and industrial automation. This paper presents a concise empirical-validation version of CPS-RISE, a resilience framework that integrates AI-driven anomaly detection, blockchain-based audit integrity, secure middleware interoperability, and Digital Twin simulation. Unlike a broader framework-oriented article already published on CPS-RISE, this conference version foregrounds simulation design, measurable validation outcomes, and deployment implications within the RISE 2026 template limit. Evaluation using industrial CPS datasets, Hyperledger Fabric integrity testing, middleware performance assessment, and Digital Twin attack scenarios indicates improved anomaly detection, reduced false positives, faster response latency, scalable audit logging, stable interoperability, and faster recovery compared with fragmented CPS security baselines. The findings support integrated resilience architecture as a practical pathway for strengthening oil and gas CPS security.

Keywords: Cyber-Physical Systems, Artificial Intelligence, Resilience Engineering, Anomaly Detection, Oil and Gas Infrastructure, Industrial Control Systems