Decentralized identity management based on autonomous identity in e-commerce and its application to key opinion leader

In the context of modern e-commerce, decentralized identity management has emerged as a critical solution to address privacy, security, and trust issues, especially for Key Opinion Leaders (KOLs). This paper introduces an autonomous identity management system that leverages blockchain technology to decentralize control over identity credentials. By utilizing decentralized identifiers (DIDs) and verifiable credentials (VCs), the system enables secure, transparent, and tamper-proof management of digital identities without the need for centralized authorities. The intelligent platform management capability of this system enhances identity verification and data security, making it particularly well-suited for applications where trust and privacy are paramount, such as KOL interactions in e-commerce. The system integrates advanced smart contract mechanisms to automate identity verification and credential management, thereby increasing efficiency and reducing operational costs. The proposed method was tested in various scenarios, demonstrating superior performance in terms of security, scalability, and operational efficiency compared to traditional centralized systems. Results indicate that the decentralized identity platform not only strengthens security but also provides a scalable solution for managing digital identities in an intelligent and autonomous manner, making it highly applicable to KOLs in e-commerce. Future work will focus on extending the platform’s capabilities to a broader range of applications and improving user experience.

Authors

Publication Details

Journal
IET conference proceedings.
Published
2025-01-09
DOI
https://doi.org/10.1049/icp.2024.4247
Primary Topic
Cognitive Computing and Networks
Type
article
Field-Weighted Citation Impact
0.00
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article

Decentralized identity management based on autonomous identity in e-commerce and its application to key opinion leader

Ping Cui
IET conference proceedings.
Cognitive Computing and Networks
article

Decentralized identity management based on autonomous identity in e-commerce and its application to key opinion leader

Ping Cui
article en

Abstract

In the context of modern e-commerce, decentralized identity management has emerged as a critical solution to address privacy, security, and trust issues, especially for Key Opinion Leaders (KOLs). This paper introduces an autonomous identity management system that leverages blockchain technology to decentralize control over identity credentials. By utilizing decentralized identifiers (DIDs) and verifiable credentials (VCs), the system enables secure, transparent, and tamper-proof management of digital identities without the need for centralized authorities. The intelligent platform management capability of this system enhances identity verification and data security, making it particularly well-suited for applications where trust and privacy are paramount, such as KOL interactions in e-commerce. The system integrates advanced smart contract mechanisms to automate identity verification and credential management, thereby increasing efficiency and reducing operational costs. The proposed method was tested in various scenarios, demonstrating superior performance in terms of security, scalability, and operational efficiency compared to traditional centralized systems. Results indicate that the decentralized identity platform not only strengthens security but also provides a scalable solution for managing digital identities in an intelligent and autonomous manner, making it highly applicable to KOLs in e-commerce. Future work will focus on extending the platform’s capabilities to a broader range of applications and improving user experience.

IET conference proceedings.Vol. 2024(21)
Reduced inequalities
Openalex Percentile: Top 100%
Cognitive Computing and Networks
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Decentralized identity management based on autonomous identity in e-commerce and its application to key opinion leader — Ping Cui · IET conference proceedings. (2025) | TGRS Research Map | TGRS