Distributed and trustworthy digital twin platform based on blockchain and Web3 technologies

Abstract

The fourth industrial revolution has significantly increased the adoption of Digital Twins (DTs) across various sectors, including intelligent manufacturing, automation, logistics, and medical analysis. Despite substantial progress in deploying DT projects, numerous challenges remain, such as managing distributed data flows, protecting commercial confidentiality, securing intellectual property, and ensuring privacy and security. This research introduces a novel approach to addressing these challenges by leveraging blockchain and Web3 technologies, including non-fungible tokens (NFTs) and Distributed Autonomous Organizations (DAOs). The study aims to develop a distributed, tamper-proof DT cooperation platform that facilitates traceable and trustworthy data sharing while preserving intellectual property rights and enabling decentralized governance. This platform enhances idea and invention ownership, promotes collective decision-making through consensus protocols, and explores innovative solutions like blockchain-based federated learning and efficient DT project fundraising tools. Relying on security models and analysis tools, this study addresses several important security analysis methods/tools/models (e.g., random oracle model, BAN logic, AVISPA tool, and TAMARIN prover) that are known as practical analysis methods. They can strongly prove every claimed security feature of DT projects. The proposed solutions set the stage for future academic and industrial advancements, supported by a comprehensive SWOT (Strongness - Weakness - Opportunity - Threat) analysis, and outline potential future research directions.