@inproceedings{03ed4d15af944743af7cd35b99fe6b2b,
title = "SMDS: Blockchain-Based Sensitive Data Storage for Smart Manufacturing",
abstract = "With the arrival of the digital age and the wide adoption of Internet technologies, the manufacturing industry is gradually entering the era of smart manufacturing. It is of great significance to adopt efficient digital solutions for data management. Organizations tend to choose distributed third-party cloud platforms to store and share data to reduce the costs of building their data platforms. Although distributed cloud storage solutions can solve various problems associated with centralized storage solutions, the collaboration between multiple nodes requires mutual trust. Blockchain technology can help to build trust among different parties. However, the existing consortium blockchain platform does not meet the needs of data privacy and large-scale data storage in smart manufacturing. Therefore, we propose a storage scheme based on the consortium blockchain platform Hyperledger Fabric and the InterPlanetary File System (IPFS). By improving the ledger data structure and designing corresponding smart contract functions, the proposed scheme can store various digital resources on the blockchain platform flexibly and provide fine-grained protection for sensitive data. Several simulation experiments are conducted to analyze the factors affecting the performance. The experiment results show that the space-time overhead of the proposed scheme is acceptable.",
keywords = "blockchain, data security, data storage, ipfs",
author = "Yao Xiao and Zikang Chen and Lei Xu and Keke Gai and Liehuang Zhu",
note = "Publisher Copyright: {\textcopyright} 2025 IEEE.; 11th IEEE International Conference on Big Data Security on Cloud, BigDataSecurity 2025 ; Conference date: 09-05-2025 Through 11-05-2025",
year = "2025",
doi = "10.1109/BigDataSecurity66063.2025.00019",
language = "English",
series = "Proceedings - 2025 IEEE 11th Conference on Big Data Security on Cloud, BigDataSecurity 2025",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "107--114",
booktitle = "Proceedings - 2025 IEEE 11th Conference on Big Data Security on Cloud, BigDataSecurity 2025",
address = "United States",
}