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On-chain repairing for multi-party data migration

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Abstract

Blockchain can be used to solve the problem of mutual trust between different institutions. However, when migrating data from a traditional system to a blockchain system, the order of data transactions is difficult to determine and the data transactions on the chain can not be modified. Therefore, it is necessary to build an on-chain repairing mechanism for multi-party data migration. In this paper, an on-chain repairing system for multi-party data migration is designed to realize the multi-party data migration, the block data repairing, and the data auditing. The multi-party data migration is utilized to determine the order of data transactions, and the order determining during data transaction is solved by setting up transaction pools and sorting transactions of the same institution or different institutions. The controlled data repairing strategy is utilized to repair the error data in the blockchain based on the chameleon-hash algorithm. The data repairing audit strategy is used to ensure the controllable data repairing. Compared with the Hyperledge Fabric, the additional cost for multi-party data migration of our method is not more than 10%.

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Funding

This study was funded by the Guangdong Science and Technology Plan Project (2019B010139001), Guangzhou Science and Technology Plan Project (201902020016), Guangdong Natural Science Fund Project (2021A1515011243), Yunfu Science and Technology Plan Project (S2021010104) and the National Key R&D Program of China under Grant No. 2019YFB2101700, the National Natural Science Foundation of China No. 62072202.

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Authors and Affiliations

  1. School of Computer Science and Technology, Guangdong University of Technology, 510006, Guangzhou, China

    Wenchao Jiang & Sui Lin

  2. School of Cyber Science and Engineering, Huazhong University of Science and Technology, 430074, Wuhan, China

    Weiqi Dai & Qiwen Lv

  3. Taotall Technology Development Co., Ltd, 510635, Guangzhou, China

    Dongjun Ning

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  1. Wenchao Jiang
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  2. Weiqi Dai
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  3. Qiwen Lv
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  4. Dongjun Ning
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  5. Sui Lin
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Contributions

Wenchao Jiang designed the system and the framework of this paper, Qiwen Lv conducted the implementation, experiments and tests, Wenchao Jiang, Weiqi Dai, and Qiwen Lv wrote the paper together, Dongjun Ning provided the application and test scenario, and Sui Lin and Weiqi Dai check and proofread the paper.

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Correspondence to Weiqi Dai.

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This article belongs to the Topical Collection: Special Issue on Privacy and Security in Machine Learning

Guest Editors: Jin Li, Francesco Palmieri and Changyu Dong

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Jiang, W., Dai, W., Lv, Q. et al. On-chain repairing for multi-party data migration. World Wide Web 26, 2749–2766 (2023). https://doi.org/10.1007/s11280-023-01148-0

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  • DOI: https://doi.org/10.1007/s11280-023-01148-0

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