Leveraging digital twin technology for real-time data security monitoring in cyber-physical systems

Physical processes can be highly combined with computation intelligence, via Cyber-Physical Systems (CPS), which foundationally represent the core of modern smart environments. With these systems there comes the high degree of efficiency and automation which have unfortunately become susceptible to the highly advanced world of cyber threats especially in the real time data flows. Such threats can usually evade traditional security mechanisms, which are reactive and possess low levels of contextual awareness, thus making them unable to detect and react dynamically.This study suggests an innovative framework based on the Digital Twin (DT) technology which helps to monitor the security of real-time data in the CPS. The suggested system will have the synchronized virtual replica of the physical environment that will monitor the data flow incessantly to spot abnormalities and counteract a possible cyber-attack even before it occurred. The framework combining anomaly detection algorithms and mechanisms of real-time feedback will also detect security breaches when they happen, including data injection, tampering, and denial-of-service attacks, at earlier stages.To test the performance of the DT in terms of the security model, an experimental testbed comprising of a simulation of a CPS is created. The effectiveness of results shows better detection and lesser response time in comparison to the traditional approach. This piece of work adds to an existing literature base on smart cybersecurity strategies and also identifies the possibilities of Digital Twins as a form of active defense in data protection on a critical infrastructure system.