Industrial-Internet-of-Things-Based Digital Twin and Metaverse Privacy and Security Measures for a Trustworthy Industrial Metaverse Ecosystem

The industrial metaverse (IMV) represents a digital industrial system that, under the new generation of AI technology and the integration of digital twin technology, produces the virtual reality mapping, interaction, and integration of virtual and real space in the industrial field. In the expanse of the IMV, security and privacy challenges, such as cyberthreats, deepfakes, data theft, identity theft, and sensory manipulation within the metaverse, loom large and demand immediate attention. In this research, we propose an implementable architecture, technical requirements, dataflow system, and functional privacy and security solutions-policies that handle the challenges, guarantee a balance between privacy and innovation, and provide user education and satisfaction within edge network systems, which are imperative for a secure and trustworthy IMV network environment.