Efficient and provably secured puncturable attribute-based signature for Web 3.0

IF 6.2 2区 计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS
YueTong Wu , Hu Xiong , Fazlullah Khan , Salman Ijaz , Ryan Alturki , Abeer Aljohani
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引用次数: 0

Abstract

Web 3.0 is a grand design with intricate data interchange, implying the requirement of versatile network protocol to ensure its security. Attribute-based signature (ABS) allows a user, who is featured with a set of attributes, to sign messages under a predicate. The validity of the ABS signature demonstrates that this signature is generated by the user whose attributes satisfy the corresponding predicate, and thus flexibly achieves anonymous authentication. Similar to other digital signatures, the security of ABS is broken in case the private key of the user is leaked out. To address the threat brought by the key leakage, this paper proposes a puncturable attribute-based signature scheme that allows the private key generator to revoke the signing right associated with specific tags. This paper firstly elaborates the construction of the proposed ABS scheme with puncturable property, and then proves its security theoretically by reducing the involved security to the computational Diffie–Hellman assumption. This paper then experimentally shows that the suggested puncturable ABS scheme owns a more efficient storage cost and superior performance.
用于 Web 3.0 的高效且可证明安全的可标点属性签名
Web 3.0 是一个具有复杂数据交换的宏伟设计,这意味着需要多功能的网络协议来确保其安全性。基于属性的签名(ABS)允许具有一组属性的用户在一个谓词下对信息进行签名。ABS 签名的有效性表明,该签名是由属性满足相应谓词的用户生成的,从而灵活地实现了匿名认证。与其他数字签名类似,一旦用户的私钥泄露,ABS 的安全性就会被破坏。针对密钥泄露带来的威胁,本文提出了一种基于属性的可穿刺签名方案,允许私钥生成者撤销与特定标签相关的签名权。本文首先阐述了所提出的具有可穿刺属性的 ABS 方案的构造,然后通过将所涉及的安全性还原为计算 Diffie-Hellman 假设,从理论上证明了其安全性。然后,本文通过实验证明了所提出的可穿刺 ABS 方案具有更高效的存储成本和更优越的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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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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