Security Automation Framework for Digital Twins in Smart Manufacturing
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Abstract
Digital twin technology is shaking things up in the manufacturing world by creating realtime virtual copies of physical assets. But as this technology evolves, keeping these systems safe and secure is more important than ever. Digital twins work by constantly exchanging data between the real world and their virtual counterparts, which makes them a target for cyberattacks. If these attacks succeed, they can throw off the accuracy of the virtual models and disrupt manufacturing processes. This research looks into security automation solutions specifically for digital twin systems in manufacturing settings, prioritizing monitoring and defending against new cyber threats. We’re suggesting automated security tools that use anomaly detection algorithms to keep an eye on the data flowing into digital twins, allowing us to spot and react to any unusual or harmful activities in real-time. Plus, we’re introducing automated lockdown features that protect the digital twin environment by isolating any compromised components to stop further damage. The goal of this framework is to boost the security, accuracy, and reliability of digital twin systems, ensuring these innovative technologies can be used safely and effectively in critical manufacturing operations. This paper dives into the design, implementation, and challenges of securing digital twins in the manufacturing space and adds to the ongoing push to weave security automation into the Industry 4.0 framework.