{"title":"无托管的基于属性的签名与恒定大小的物联网","authors":"Xudong Liu , Xiaojun Tong , Yihui Wang","doi":"10.1016/j.ins.2025.122679","DOIUrl":null,"url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":51063,"journal":{"name":"Information Sciences","volume":"723 ","pages":"Article 122679"},"PeriodicalIF":6.8000,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Escrow-free attribute based signature with constant-size for the internet of things\",\"authors\":\"Xudong Liu , Xiaojun Tong , Yihui Wang\",\"doi\":\"10.1016/j.ins.2025.122679\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>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.</div></div>\",\"PeriodicalId\":51063,\"journal\":{\"name\":\"Information Sciences\",\"volume\":\"723 \",\"pages\":\"Article 122679\"},\"PeriodicalIF\":6.8000,\"publicationDate\":\"2025-09-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Information Sciences\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0020025525008126\",\"RegionNum\":1,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"0\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Information Sciences","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0020025525008126","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"0","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
Escrow-free attribute based signature with constant-size for the internet of things
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.
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.