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Enhancing CAD Data Integrity and Security in Supply Chain Networks Using Blockchain

Chengnan Li et al.

International Journal of Information Systems and Supply Chain Management2025https://doi.org/10.4018/ijisscm.389716article
AJG 1ABDC C
Weight
0.37

What the paper says

Ensuring the integrity and security of CAD design data is critical in digital supply chains, where centralized systems face risks of tampering, unauthorized access, and transmission vulnerabilities. This study proposes a blockchain-based framework to enhance data integrity, traceability, and network security in CAD environments. XML is used to standardize design data, which is encrypted and stored in a decentralized manner using blockchain and distributed file systems, while smart contracts enforce access control and validation. Experimental results show that the approach effectively prevents data tampering, ensures secure information sharing, and improves transmission efficiency—making it a promising solution for secure collaboration across supply chain ecosystems. The framework supports version control and auditability of design changes, enhancing transparency among distributed engineering teams. By integrating blockchain with CAD workflows, the system strengthens trust and data reliability in digital product development within complex supply networks.

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https://doi.org/https://doi.org/10.4018/ijisscm.389716

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@article{chengnan2025,
  title        = {{Enhancing CAD Data Integrity and Security in Supply Chain Networks Using Blockchain}},
  author       = {Chengnan Li et al.},
  journal      = {International Journal of Information Systems and Supply Chain Management},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.4018/ijisscm.389716},
}

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Enhancing CAD Data Integrity and Security in Supply Chain Networks Using Blockchain

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.