Innovative Methods for Ensuring Cybersecurity of Technological Control Systems of a Digital Twin of a Food Industry Enterprise

Cybersecurity in digital twin environments for the food industry presents unique challenges due to the merging of cyber‐physical systems with legacy industrial control systems. Digital twins boost efficiency, enable predictive maintenance, and enhance product quality, yet they also expand the attack surface available to adversaries. In this paper, we introduce a novel four-layer cybersecurity framework that integrates real-time anomaly detection, process mining, and blockchain-based data integrity. Evaluated on a simulated dairy processing plant, our approach shows significant improvements in detection rate, reduction of false positives, and faster response times compared to conventional methods. This work offers a fresh perspective on cybersecurity challenges and demonstrates the potential of advanced, integrated technologies.