收稿日期: 2022-07-24
录用日期: 2022-07-24
网络出版日期: 2022-09-26
基金资助
国家自然科学基金 (61972152)
Research on contract architecture and data privacy for education-oriented blockchain applications
Received date: 2022-07-24
Accepted date: 2022-07-24
Online published: 2022-09-26
针对教育应用升级受限问题, 本文提出了高效的完全解耦合的智能合约架构. 将合约解耦合为代理逻辑合约、代理数据合约、逻辑合约和数据合约, 支持任意子合约的灵活升级, 升级成本与传统合约升级相比平均下降28.2%; 结合链上链下协作优化了解耦合合约架构下的交易执行性能, 结合区块链底层存储树减少了合约升级时数据的迁移量, 优化后降低约一半的延时. 针对教育数据隐私安全问题, 本文提出了基于权限管理和LDP (Local Differential Privacy)的隐私数据保护方案, 提高了数据隐私的安全性, 同时对区块链的性能几乎无影响. 最后将上述方案集成落地, 实现了一个由可信知识交流社区与学生成长系统构成的教育类平台.
黄超然 , 佟兴 , 张召 , 金澈清 , 杨英杰 , 秦钢 . 面向教育的区块链应用合约架构和数据隐私研究[J]. 华东师范大学学报(自然科学版), 2022 , 2022(5) : 61 -72 . DOI: 10.3969/j.issn.1000-5641.2022.05.006
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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