What is it about?

A digital twin is a virtual version of a real-world object or system that helps us monitor, predict, and improve how things work. However, digital twins often need to share data across different companies and devices, which creates challenges around trust, data accuracy, and security. In this work, we explain how blockchain can support digital twins by making shared data tamper-proof, enabling secure collaboration, and verifying the identity and actions of each participant. This survey also reviews real examples from manufacturing, smart cities, healthcare, energy, and supply chains. The goal is to help researchers and engineers understand how blockchain can make digital twin systems more reliable and ready for real-world deployment.

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Why is it important?

Digital twins are becoming a key technology in modern industry, smart cities, transportation, and healthcare. However, they can only work effectively when multiple organizations are willing to share data in a secure and trustworthy way. Without trust, digital twins remain small, isolated, and limited in value. By showing how blockchain can provide verifiable data sharing, tamper resistance, and clear accountability, this work offers a path to build digital twin systems that are reliable enough for real-world deployment.

Perspectives

My perspective is that the integration of blockchain with digital twin systems represents a natural evolution toward trustworthy cyber-physical infrastructure. I believe this survey can help unify fragmented research efforts and provide a clearer roadmap for the next generation of secure and scalable digital twin applications. The value of this work lies in bridging the gap between conceptual digital twin models and real industrial deployment scenarios. Ensuring secure and verifiable data collaboration is essential for moving digital twins from lab prototypes to high-impact, production-scale systems.

Dun Li
Tsinghua University

Read the Original

This page is a summary of: Blockchain in the Digital Twin Context: A Comprehensive Survey, ACM Computing Surveys, December 2025, ACM (Association for Computing Machinery),
DOI: 10.1145/3772366.
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