Big Data Research ›› 2023, Vol. 9 ›› Issue (6): 39-52.doi: 10.11959/j.issn.2096-0271.2023071

• TOPIC: BIG DATA SECURITY AND PRIVACY COMPUTING • Previous Articles     Next Articles

A blockchain-based privacy protection scheme for sensing data trading

Yunhui LI, Jiahui CHEN   

  1. School of Computers, Guangdong University of Technology, Guangzhou 510006, China
  • Online:2023-11-15 Published:2023-11-01
  • Supported by:
    The National Natural Science Foundation of China(61902079)

Abstract:

Sensing data trading is to transform sensory data into economic value and promote the utility and sharing of data.To ensure the reliability and privacy of data transaction, a blockchain sensing data transaction scheme based on shuffle differential privacy was proposed.In our scheme, we set an audit node to supervise users and perform tasks, a shuffle node to deal with disputes and reward distribution.We used the differential privacy technology under the shuffle model to add noise to the user's data.In addition, we supplied additive secret sharing divide the data into r shufflers to prevent the mapping relationship between users and data.Our scheme does not require a trusted third party, while data consumers could publish tasks and broadcast data through the blockchain trading platform for secure and private transactions.According to the privacy amplification theorem, the proposed scheme could obtain similar privacy protection with the centralized differential privacy.Finally, we gave experiments to verify the feasibility of the scheme.Compared with related algorithms, the data accuracy obtained by our scheme was better.

Key words: sensing data, data sharing, blockchain, privacy protection, differential privacy

CLC Number: 

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