DBT-PDP:基于区块链的可证明数据拥有与外包数据批量传输

IF 3.2 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS
Chengming Yi , Hua Zhang , Weiming Sun , Jun Ding
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引用次数: 0

摘要

在大规模数据所有权交易的场景下,现有的数据完整性审计方案面临着来自恶意第三方审计人员的安全风险,且计算和通信效率低下,极大地影响了其实用性。本文提出了一种基于区块链的数据完整性审计方案,数据所有权可以分批交易。我们的方案采用了支持数据所有权批量交易的数据标签结构。数据标签的更新过程不涉及每条数据的唯一信息,任何用户都可以通过一条交易辅助信息在一次交易中完成多条数据的所有权交易。同时,我们的方案中引入了智能合约,执行属于第三方审计人员的数据完整性审计,因此我们的方案可以摆脱恶意第三方审计人员潜在的安全风险。安全性分析表明,在随机预测模型和 k-CEIDH 假设下,我们的方案被证明是安全的。实验表明,与同类方案相比,我们的方案中数据所有权交易的通信开销和计算时间更低。同时,在数据完整性审计方面,我们方案的通信开销和计算时间与同类方案相似。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

DBT-PDP: Provable data possession with outsourced data batch transfer based on blockchain

DBT-PDP: Provable data possession with outsourced data batch transfer based on blockchain

In the scenario of large-scale data ownership transactions, existing data integrity auditing schemes are faced with security risks from malicious third-party auditors and are inefficient in both calculation and communication, which greatly affects their practicability. This paper proposes a data integrity audit scheme based on blockchain where data ownership can be traded in batches. A data tag structure which supports data ownership batch transaction is adopted in our scheme. The update process of data tag does not involve the unique information of each data, so that any user can complete ownership transactions of multiple data in a single transaction through a single transaction auxiliary information. At the same time, smart contract is introduced into our scheme to perform data integrity audit belongs to third-party auditors, therefore our scheme can free from potential security risks of malicious third-party auditors. Safety analysis shows that our scheme is proved to be safe under the stochastic prediction model and k-CEIDH hypothesis. Compared with similar schemes, the experiment shows that communication overhead and computing time of data ownership transaction in our scheme is lower. Meanwhile, the communication overhead and computing time of our scheme is similar to that of similar schemes in data integrity audit.

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CiteScore
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