RISKS AND VULNERABILITIES OF DIGITAL TWINS IN MANUFACTURING SYSTEMS DURING ENERGY CONSUMPTION OPTIMIZATION

Abstract

The presented scientific research is dedicated to an in-depth systemic analysis of information security issues arising during the implementation, integration, and operation of Digital Twin technology in modern cyber-physical manufacturing systems focused on energy consumption optimization. In the context of the rapid transition to Industry 4.0, accompanied by total digitalization and the convergence of computing resources with physical processes, Digital Twin technology has become an indispensable tool for achieving high energy efficiency, minimizing losses, and ensuring the sustainable development of the industry. However, as this research demonstrates, the breakdown of traditional physical network isolation (Air Gap) and the establishment of a continuous bidirectional data flow between the sensor equipment of operational technology and information technology cloud platforms create a large attack surface. The article provides a fundamental overview of the architectural vulnerabilities of the Industrial Internet of Things, analyzes the weaknesses of key communication protocols, and develops an extended threat classification based on an adapted STRIDE model. Special emphasis is placed on threats to data integrity, particularly False Data Injection (FDI) attacks and their cumulative impact on optimization algorithms. Within the methodological and practical part of the work, a representative local environment was built using the Software-in-the-Loop principle, which integrates a Python energy consumption emulator, the Eclipse Mosquitto message broker, and the event-driven Node-RED platform. Through the practical modeling of Spoofing and Tampering attacks, it was demonstrated that the compromise of input telemetry can completely disorient simple moving average (SMA) algorithms, hiding critical overloads from operators and blocking emergency load-shedding mechanisms, which under real conditions leads to the physical destruction of infrastructure. To counter the identified threat vectors, a comprehensive Defense in Depth architecture was developed, implemented, and verified. The proposed approach combines cryptographic encryption of the transport channel using the TLS protocol with strict authentication and application-level payload integrity validation using HMAC-SHA256 digital signatures and timestamp verification. The efficiency evaluation demonstrated the complete neutralization of the studied attacks while maintaining the functional stability of the control algorithms and resulting in entirely acceptable overheads on network delays at a level of 15–20%.