Cyber-Physical Security Framework for IoT-Integrated Industrial Control Systems

Abstract

By opening access to Internet of Things (IoT) technologies, Industrial Control Systems (ICS) are undergoing a paradigm shift with inherent capabilities of unprecedented real-time monitoring, automation, data-driven decisioning, and predictive maintenance being provided across power grids, manufacturing facilities, and smart transportation systems. Although such integration of operational technology (OT) and information technology (IT) in increasing efficiency and visibility of operations, it also provides another area of vulnerability because the ICS will be more exposed to advanced cyber-physical attacks, such as data falsification, service denial and malicious modification of commands. To overcome this two-layered defense difficulty, this paper dintroduces a complete Cyber-Physical Security Framework (CPSF) that is compatible with IoT incorporated ICS environments. The CPSF follows a wide security policy consisting of secure hardware modules to support trusted device authentication, an encrypted low-latency communication protocol to mitigate the data in motion and an AI-based multi-modal hybrid intrusion detection system in real time based on a rule and over anomaly approaches. Moreover, a distributed ledger using blockchain technology is utilized to guarantee tamper-resistant logging of controls actions and the configuration change, consequently increasing the ability to forensics and system accountability. The implementation of the framework takes place in the hybrid simulation-testbed environment, which combines both OPC-UA over MQTT enabling industrial communication and Hyperledger Fabric acting as a decentralized system of assuring security. Experimental findings indicate that the proposed CPSF can attain a detection rate of 94.6 percent with a false positive ratio of just 3.2 percent, and satisfy the intensive end-to-end latency requirements of industrial automation systems, at less than 80 milliseconds. This demonstrates that the framework can enable strong, scalable and low-latency cyber-physical security thereby being a suitable approach to protect essential industrial systems against the changing threats. Finally, future research possibilities are discussed, such as the introduction of federated learning when dealing with distributed threat intelligence and post-quantum cryptography mechanisms as resilience measures towards new paradigms of computation.