Blockchain-enabled privacy protection scheme for IoT digital identity management

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.

Authors

Institutions

Publication Details

Journal
High-Confidence Computing
Published
2025-03-26
DOI
https://doi.org/10.1016/j.hcc.2025.100320
Citations
2
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
6.49
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Blockchain-enabled privacy protection scheme for IoT digital identity management

Guijuan Wang, Anming Dong, Yawei Wang, Jiguo Yu et al.
2 citations
High-Confidence Computing
Blockchain Technology Applications and Security
6.49
article

Blockchain-enabled privacy protection scheme for IoT digital identity management

Guijuan Wang, Anming Dong, Yawei Wang, Jiguo Yu, Yubing Han, Hao Yu
article en
2 citations

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.

High-Confidence ComputingVol. 5(4)
Amazon (United States) (US), University of Electronic Science and Technology of China (CN), Qilu University of Technology (CN), Shandong University (CN), Shandong Academy of Sciences (CN)
Openalex Percentile: Top 5%
Blockchain Technology Applications and Security
6.49
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Blockchain-enabled privacy protection scheme for IoT digital identity management — Guijuan Wang, Anming Dong, et al. · High-Confidence Computing (2025) | TGRS Research Map | TGRS