Journal of East China Normal University(Natural Science) ›› 2022, Vol. 2022 ›› Issue (5): 61-72.doi: 10.3969/j.issn.1000-5641.2022.05.006

• Blockchain System and Data Management • Previous Articles     Next Articles

Research on contract architecture and data privacy for education-oriented blockchain applications

Chaoran HUANG1, Xing TONG1, Zhao ZHANG1,*(), Cheqing JIN1, Yingjie YANG2, Gang QIN2   

  1. 1. School of Data Science and Engineering, East China Normal University, Shanghai 200062, China
    2. Digital & Smart Supply Chain Research and Development Center, Ouyeel Co. Ltd., Shanghai 201999, China
  • Received:2022-07-24 Accepted:2022-07-24 Online:2022-09-25 Published:2022-09-26
  • Contact: Zhao ZHANG E-mail:zhzhang@dase.ecnu.edu.cn

Abstract:

As the internet drives toward “digital transformation”, education equity and data trust-worthiness pose significant challenges in development. Blockchain, as a distributed ledger technology with tamperproof data, is jointly maintained by multiple parties and can solve equity and trustworthiness issues in scenarios such as educational resource allocation, intellectual property rights, and student information authentication. Although blockchain is capable of addressing the core education problems, its data immutability and transparency properties limit the upgradation process of smart contracts and disclosure of sensitive data in blockchain applications. Hence, updating educational applications and creating low privacy security of educational data becomes strenuous. To address the problem of limited smart contract upgrades, this study proposes an efficient and fully decoupled blockchain smart contract architecture. The as-proposed architecture aids in decoupling the contracts into proxy logical contracts, proxy data contracts, logical contracts, and data contracts, achieving an average reduction of 28.2% in upgradation costs compared with traditional methods. Moreover, we combined on- and off-chain collaboration to optimize transactions under the decoupled contract architecture and reduce data migration while updating contracts by integrating the underlying blockchain storage tree, optimized to reduce latency by half. To solve the problem of privacy protection, we propose a privacy data protection scheme based on permission management and LDP (Local Differential Privacy) to improve data privacy security while reducing the negative impact on blockchain performance. Finally, these solutions were integrated and implemented into an educational platform comprising a trusted knowledge exchange community and student growth system.

Key words: blockchain, smart contract, privacy protection, education

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