BCE-PPDS: Blockchain-based cloud–edge collaborative privacy-preserving data sharing scheme for IoT

IF 6.2 2区 计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS
Guijuan Wang , Qi Liu , Zhongyuan Yu , Hongliang Zhang , Anming Dong
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引用次数: 0

Abstract

Internet of Things (IoT) devices generate large amounts of data every day that can be combined with intelligent platforms for predictive analytics and scientific research. However, concerns about privacy and security hinder the willingness of individuals to share data. Blockchain emerged as a promising infrastructure for facilitating secure data sharing due to its decentralized, immutability, and auditable benefits. In this paper, we propose a blockchain-based cloud–edge collaborative privacy protection data sharing scheme (BCE-PPDS), which is decentralized and enables data requesters (DRs) to search data resources using smart contracts to efficiently obtain target data. To protect the identity privacy of data owners (DOs), we propose a novel certificateless linkable ring signature algorithm with efficient performance. This algorithm is not only suitable for deployment on resource-limited IoT devices, so that DOs can realize anonymous identity authentication, but also can aggregate the generated ring signatures for batch verification, so as to improve the efficiency of signature verification. In addition, we designed a key distribution algorithm using the Asmuth–Bloom secret sharing scheme to ensure the security of the key. Under the random oracle model, BCE-PPDS is provably secure. The experimental results verify that BCE-PPDS is efficient and practical.
BCE-PPDS:基于区块链的物联网云边缘协作隐私保护数据共享方案
物联网(IoT)设备每天都会产生大量数据,这些数据可以与智能平台相结合,用于预测分析和科学研究。然而,对隐私和安全的担忧阻碍了个人分享数据的意愿。区块链由于其去中心化、不变性和可审计的优点,成为促进安全数据共享的有前途的基础设施。在本文中,我们提出了一种基于区块链的云边缘协作隐私保护数据共享方案(BCE-PPDS),该方案是分散的,使数据请求者(dr)能够使用智能合约搜索数据资源,从而有效地获取目标数据。为了保护数据所有者(DOs)的身份隐私,我们提出了一种新的无证书可链接环签名算法。该算法不仅适合部署在资源有限的物联网设备上,使DOs可以实现匿名身份认证,而且可以将生成的环签名聚合起来进行批量验证,从而提高签名验证的效率。此外,我们还设计了一个使用Asmuth-Bloom秘密共享方案的密钥分发算法,以确保密钥的安全性。在随机oracle模型下,BCE-PPDS是安全的。实验结果验证了BCE-PPDS的有效性和实用性。
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来源期刊
CiteScore
19.90
自引率
2.70%
发文量
376
审稿时长
10.6 months
期刊介绍: Computing infrastructures and systems are constantly evolving, resulting in increasingly complex and collaborative scientific applications. To cope with these advancements, there is a growing need for collaborative tools that can effectively map, control, and execute these applications. Furthermore, with the explosion of Big Data, there is a requirement for innovative methods and infrastructures to collect, analyze, and derive meaningful insights from the vast amount of data generated. This necessitates the integration of computational and storage capabilities, databases, sensors, and human collaboration. Future Generation Computer Systems aims to pioneer advancements in distributed systems, collaborative environments, high-performance computing, and Big Data analytics. It strives to stay at the forefront of developments in grids, clouds, and the Internet of Things (IoT) to effectively address the challenges posed by these wide-area, fully distributed sensing and computing systems.
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