Digital twins—virtual replicas of physical manufacturing systems—bring powerful tools for monitoring, simulation, optimization, and predictive maintenance, but they also introduce new cyber risks by bridging IT and OT environments. Because digital twins continuously collect data from sensors, devices, and control systems, they become attractive targets: an attacker who tampers with data can manipulate behavior predictions, degrade system accuracy, or even push a twin to issue harmful commands to real equipment. The tight coupling between virtual and physical layers means any breach in the digital domain can cascade into operational disruption, safety issues, or asset damage.

To defend digital twins, organizations should adopt a layered security approach. Zero Trust principles—such as least privilege access and continuous verification—should be applied to all interactions. Network segmentation is critical: twin traffic must be isolated from other OT and IT zones. All communications need strong encryption, both in transit and at rest. Endpoints and edge devices must be hardened: default settings eliminated, unnecessary services disabled, and secure baselines enforced. Real-time anomaly detection is key, especially using AI/ML tools that flag deviations in models or data flows, and must integrate with central security operations for swift response. Ultimately, balancing innovation, visibility, and resilience requires embedding security from design through deployment for digital twin systems in manufacturing.

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Source: https://gca.isa.org/blog/how-to-secure-digital-twins-in-manufacturing