计算机科学
信息隐私
数据共享
计算机安全
安全多方计算
加密
块链
计算
秘密分享
密码学
计算机网络
分布式计算
医学
替代医学
病理
算法
作者
Yuhan Yang,Jing Wu,Chengnian Long,Wei Liang,Yi‐Bing Lin
出处
期刊:IEEE Transactions on Industrial Informatics
[Institute of Electrical and Electronics Engineers]
日期:2022-05-24
卷期号:18 (12): 9259-9267
被引量:20
标识
DOI:10.1109/tii.2022.3177630
摘要
With the rapid increase of the industrial data and the development of the industrial Internet of Things (IIoT) paradigm, the efficiency and the quality of service of the emerging applications have been improved. However, the contradiction between data sharing and privacy preserving is still an obstacle in the IIoT. To this end, in this article, we propose a privacy-preserving and publicly auditable multiparty computation scheme for industrial data sharing and computing, which avoids privacy leakage and computation misbehavior by separating the data ownership, data use, and data verification. Using the blockchain technology, a transparent management platform is provided to recognize and trace the illegal data and computation behavior. Moreover, we integrate the noninteractive zero-knowledge proof in the multiparty interaction mechanism, wherein the verification of data consistency and computation validity is executed publicly on the blockchain. Finally, we implement experiment to evaluate the performance of the computation latency, communication overhead and the influence of encryption parameter, and the numerical results illustrate the efficiency and feasibility of our scheme.
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