A Data Rate Monitoring Approach for Cyberattack Detection in Digital Twin Communication

The increasing integration of Digital Twins (DTs) in Industry 4.0 environments establishes the physical-virtual communication layer as a critical vector for cyber vulnerabilities. Current literature predominantly focuses on complex security mechanisms, leaving a gap in the exploration of fundamental and computationally cost-effective network metrics. This paper addresses this gap by validating a non-intrusive attack detection method based exclusively on monitoring data rate throughput. A Docker simulation environment was used to emulate Denial of Service (DoS), Man-in-the-Middle (MiTM), and other intrusion attacks. The results demonstrate that each attack produces a distinct and detectable statistical signature. For example, the DoS attack caused a 50-fold increase in packet rate. We conclude that data rate analysis represents a viable and complementary approach to IIoT security, providing a robust, interpretable, and cost-effective first line of defense towards developing more resilient Digital Twins.