Blockchain-enabled privacy protection scheme for IoT digital identity management

Hao Yu , Guijuan Wang , Anming Dong , Yubing Han , Yawei Wang , Jiguo Yu

High-Confidence Computing ›› 2025, Vol. 5 ›› Issue (4) : 100320

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High-Confidence Computing ›› 2025, Vol. 5 ›› Issue (4) :100320 DOI: 10.1016/j.hcc.2025.100320
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Blockchain-enabled privacy protection scheme for IoT digital identity management

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Abstract

With the growth of the Internet of Things (IoT), millions of users, devices, and applications compose a complex and heterogeneous network, which increases the complexity of digital identity management. Traditional centralized digital identity management systems (DIMS) confront single points of failure and privacy leakages. The emergence of blockchain technology presents an opportunity for DIMS to handle the single point of failure problem associated with centralized architectures. However, the transparency inherent in blockchain technology still exposes DIMS to privacy leakages. In this paper, we propose the privacy-protected IoT DIMS (PPID), a novel blockchain-based distributed identity system to protect the privacy of on-chain identity data. The PPID achieves the unlinkability of identity-credential-verification. Specifically, the PPID adopts the Zero Knowledge Proof (ZKP) algorithm and Shamir secret sharing (SSS) to safeguard privacy security, resist replay attacks, and ensure data integrity. Finally, we evaluate the performance of ZKP computation in PPID, as well as the transaction fees of smart contract on the Ethereum blockchain.

Keywords

Blockchain / IoT / Privacy preservation / Zero-knowledge proof / Identity management

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Hao Yu, Guijuan Wang, Anming Dong, Yubing Han, Yawei Wang, Jiguo Yu. Blockchain-enabled privacy protection scheme for IoT digital identity management. High-Confidence Computing, 2025, 5(4): 100320 DOI:10.1016/j.hcc.2025.100320

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CRediT authorship contribution statement

Hao Yu: Writing - original draft. Guijuan Wang: Writing - review & editing, Investigation, Funding acquisition, Formal analysis. Anming Dong: Methodology, Investigation, Data curation. Yubing Han: Supervision, Resources, Methodology. Yawei Wang: Project administration, Methodology, Investigation. Jiguo Yu: Funding acquisition, Writing - original draft, Writing - review & editing.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

This work was supported in part by NSF of China (62202250, 62272256); in part by Shandong Province Youth Innovation Team Project (2024KJH032); in part by the Major Program of Shandong Provincial Natural Science Foundation for the Fundamental Research (ZR2022ZD03); in part by the National Natural Science Foundation of China (62402254); in part by the Natural Science Foundation of Shandong Province of China (ZR2022QF094); and in part by the Colleges and Universities 20 Terms Foundation of Jinan City (202228093), the Pilot Project for Integrated Innovation of Science, Education, and Industry of Qilu University of Technology (Shandong Academy of Sciences) (2024ZDZX08).

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