Privacy-enhanced distributed revocable identity management scheme based self-sovereign identity

In recent years, the rapid proliferation of digital services and resources on Industrial Internet has imposed higher demands on universality and privacy of identity management. Particularly with the advent of the digital economy, prudent users are urged to maintain control over their digital identity credentials. However, traditional identity management methods have failed to meet this requirement and thus have been prone to raise users' concerns about potential financial loss. Specifically, conventional identity management systems(IDMS) have been plagued by imperceptible privacy disclosure, which derives from the flaws in single points of failure, excessive disclosure, correlation analysis, traceability, and revocation. The emerging Self-Sovereign Identity (SSI) architecture aims to tackle these issues and is propelling the evolution of privacy-enhanced distributed identity management. To this end, we proposed a privacy-enhanced distributed identity management scheme with sequential aggregate issuance, threshold traceability and revocability in the setting of multiple credential issuers and regulators. We adopted the Decentralized identifiers(DIDs) and verifiable credentials(VCs) based on the SSI architecture to ensure the hierarchical identity authentication. The security and performance analysis shows that our proposal achieves the desired design goals and is feasible for distributed Industrial Internet.

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Publication Details

Journal
Journal of Cloud Computing Advances Systems and Applications
Published
2024-11-08
DOI
https://doi.org/10.1186/s13677-024-00715-8
Citations
5
Primary Topic
Cryptography and Data Security
Type
article
Field-Weighted Citation Impact
1.74

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article

Privacy-enhanced distributed revocable identity management scheme based self-sovereign identity

Guo Xian, Tao Feng, Xusheng Wang, Junli Fang
5 citations
Journal of Cloud Computing Advances Systems and Applications
Cryptography and Data Security
1.74
article

Privacy-enhanced distributed revocable identity management scheme based self-sovereign identity

Guo Xian, Tao Feng, Xusheng Wang, Junli Fang
article en
5 citations

Abstract

In recent years, the rapid proliferation of digital services and resources on Industrial Internet has imposed higher demands on universality and privacy of identity management. Particularly with the advent of the digital economy, prudent users are urged to maintain control over their digital identity credentials. However, traditional identity management methods have failed to meet this requirement and thus have been prone to raise users' concerns about potential financial loss. Specifically, conventional identity management systems(IDMS) have been plagued by imperceptible privacy disclosure, which derives from the flaws in single points of failure, excessive disclosure, correlation analysis, traceability, and revocation. The emerging Self-Sovereign Identity (SSI) architecture aims to tackle these issues and is propelling the evolution of privacy-enhanced distributed identity management. To this end, we proposed a privacy-enhanced distributed identity management scheme with sequential aggregate issuance, threshold traceability and revocability in the setting of multiple credential issuers and regulators. We adopted the Decentralized identifiers(DIDs) and verifiable credentials(VCs) based on the SSI architecture to ensure the hierarchical identity authentication. The security and performance analysis shows that our proposal achieves the desired design goals and is feasible for distributed Industrial Internet.

Journal of Cloud Computing Advances Systems and ApplicationsVol. 13(1)
Gansu Agricultural University (CN), Lanzhou University of Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 13%
Cryptography and Data Security
1.74
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Privacy-enhanced distributed revocable identity management scheme based self-sovereign identity — Guo Xian, Tao Feng, et al. · Journal of Cloud Computing Advances Systems and Applications (2024) | TGRS Research Map | TGRS