具有用户友好型私钥生成和规则表的自主身份框架

IF 6.2 2区 计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS Future Generation Computer Systems-The International Journal of Escience Pub Date : 2025-02-16 DOI:10.1016/j.future.2025.107757
Jungwon Seo , Sooyong Park
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Self-sovereign identity framework with user-friendly private key generation and rule table
The rise of self-sovereign identity (SSI) technology plays a critical role in addressing the limitations of conventional digital identity management systems. This paper focuses on the credential layer within the SSI technology stack, presenting a comprehensive solution to challenges related to usability, inefficient encryption and decryption processes, and verifiable credential management in existing SSI frameworks. To tackle these issues, the proposed approach introduces a user-friendly private key generation method, a rule table-based encryption and decryption technique, and a verifiable credential management system using smart contracts. In a usability evaluation involving 58 participants, 74.1% rated the proposed approach as user-friendly. Performance evaluations demonstrated that the rule table-based encryption method is between 10.37 and 171.51 times faster than existing encryption techniques. Similarly, the decryption process showed significant improvements, achieving performance that is 16.94 to 58.68 times faster than traditional methods. Security analyses were also conducted, highlighting the resilience against brute-force attacks and unauthorized access. The impact of this research extends beyond addressing current limitations, offering a robust and efficient framework that enhances the usability, security, and performance of SSI systems. By advancing the credential layer, this work paves the way for broader adoption of SSI technology across diverse applications, contributing to the evolution of decentralized identity management solutions.
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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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