Escrow-free attribute based signature with constant-size for the internet of things

IF 6.8 1区 计算机科学 0 COMPUTER SCIENCE, INFORMATION SYSTEMS
Xudong Liu , Xiaojun Tong , Yihui Wang
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引用次数: 0

Abstract

Attribute based signature (ABS) provides a promising solution for anonymous authentication. However, numerous prevailing ABS algorithms are ill-suited for anonymous authentication in the Internet of Things (IoT), due to problems such as key escrow, high computational overhead, inflexible access policies, and vulnerability to collusion attacks. Considering these shortcomings, we present an escrow-free attribute based signature with constant-size signature for IoT. Our proposal uses the linear secret-sharing scheme (LSSS) and the notion of certificateless cryptography to restrict the authorities of each attribute authority and the system authority. In addition, it generates a constant-size signature and achieves high verification efficiency by aggregating attribute keys. Theoretical analyses demonstrate that our proposal achieves anonymous authentication and is provably secure under the standard model. Simulation experiments show that the execution time of our algorithm is less than 50 ms to run during both the signature and verification phases, making it well-suited for applications with limited resources.
无托管的基于属性的签名与恒定大小的物联网
基于属性的签名(ABS)为匿名认证提供了一种很有前途的解决方案。然而,由于密钥托管、高计算开销、不灵活的访问策略和易受合谋攻击等问题,许多流行的ABS算法不适合物联网(IoT)中的匿名身份验证。考虑到这些缺点,我们提出了一种基于物联网的无托管属性签名和恒大小签名。我们的建议使用线性秘密共享方案(LSSS)和无证书加密的概念来限制每个属性机构和系统机构的权限。此外,该算法生成一个固定大小的签名,并通过聚合属性密钥实现较高的验证效率。理论分析表明,该方案实现了匿名认证,并且在标准模型下具有可证明的安全性。仿真实验表明,该算法在签名和验证阶段的执行时间都小于50 ms,非常适合资源有限的应用。
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来源期刊
Information Sciences
Information Sciences 工程技术-计算机:信息系统
CiteScore
14.00
自引率
17.30%
发文量
1322
审稿时长
10.4 months
期刊介绍: Informatics and Computer Science Intelligent Systems Applications is an esteemed international journal that focuses on publishing original and creative research findings in the field of information sciences. We also feature a limited number of timely tutorial and surveying contributions. Our journal aims to cater to a diverse audience, including researchers, developers, managers, strategic planners, graduate students, and anyone interested in staying up-to-date with cutting-edge research in information science, knowledge engineering, and intelligent systems. While readers are expected to share a common interest in information science, they come from varying backgrounds such as engineering, mathematics, statistics, physics, computer science, cell biology, molecular biology, management science, cognitive science, neurobiology, behavioral sciences, and biochemistry.
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