计算机科学
计算机网络
计算机安全
认证(法律)
密码学
匿名
吊销列表
架空(工程)
撤销
密码协议
协议(科学)
GSM演进的增强数据速率
群签名
加密
公钥密码术
公钥基础设施
病理
操作系统
电信
替代医学
医学
作者
Yanping Wang,Xiaofen Wang,Hong-Ning Dai,Xiaosong Zhang,Muhammad Imran
出处
期刊:IEEE Transactions on Industrial Informatics
[Institute of Electrical and Electronics Engineers]
日期:2023-06-01
卷期号:19 (6): 7835-7847
被引量:2
标识
DOI:10.1109/tii.2022.3226244
摘要
Intelligent Transport Systems (ITS) have received growing attention recently driven by technical advances in Industrial Internet of Vehicles (IIoV). In IIoV, vehicles report traffic data to management infrastructures to achieve better ITS services. To ensure security and privacy, many anonymous authentication-enabled data reporting protocols are proposed. However, these protocols usually require a large number of preloaded pseudonyms or involve a costly and irrevocable group signature. Thus, they are not ready for realistic deployment due to large storage overhead, expensive computation costs, or absence of malicious users' revocation. To address these issues, we present a novel data reporting protocol for edge-assisted ITS in this paper, where the traffic data is sent to distributed edge nodes for local processing. Specifically, we propose a new anonymous authentication scheme fine-tuned to fulfill the needs of vehicular data reporting, which allows authenticated vehicles to report unlimited unlinkable messages to edge nodes without huge pseudonyms download and storage costs. Moreover, we designed an efficient certificate update scheme based on a bivariate polynomial function. In this way, malicious vehicles can be revoked with time complexity $\mathcal {O}$ (1). The security analysis demonstrates that our protocol satisfies source authentication, anonymity, unlinkability, traceability, revocability, nonframeability, and nonrepudiation. Further, extensive simulation results show that the performance of our protocol is greatly improved since the signature size is reduced by at least 8%, the computation costs in message signing and verification are reduced by at least 56% and 67%, respectively, and the packet loss rate is reduced by at least 14%.
科研通智能强力驱动
Strongly Powered by AbleSci AI