基于多 TA 模型的雾化 VANET 条件隐私保护认证协议

IF 5.8 2区 计算机科学 Q1 TELECOMMUNICATIONS Vehicular Communications Pub Date : 2024-05-07 DOI:10.1016/j.vehcom.2024.100785
Pankaj Kumar , Hari Om
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引用次数: 0

摘要

在物联网、云计算、智能交通系统和雾计算等技术进步的推动下,车载无线网络(VANET)迅速发展,这促使人们引入基于雾节点的 VANET,为资源有限的设备提供服务。在传统的 VANET 安全模型中,由于使用了集中式可信机构,随着服务访问请求的增加,有可能出现单点故障和服务不可用的情况。此外,每个路边单元与可信机构之间都是一对一的通信。这可能会增加系统的复杂性和流量负荷。为解决这些问题,本文讨论了一种基于多重受信机构模型的新型雾化 VANET 验证协议,由于整个流量负载分布在多个子受信机构之间,该协议降低了服务不可用和单点故障的几率。由于结合了雾节点,一组路边装置可以集中控制,受托机构无需对每个路边装置进行单独认证。通过非正式和正式的安全分析,对所提出协议的安全性进行了严格检验。此外,正如性能比较部分所展示的那样,该协议具有增强的安全功能,能够满足安全和隐私要求,同时通信、计算和存储成本相对较低。因此,所提出的协议为雾化 VANET 提供了一种安全、高效的身份验证协议。
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Multi-TA model-based conditional privacy-preserving authentication protocol for fog-enabled VANET

The rapid growth of Vehicular Ad-hoc Networks (VANET), fueled by advancements in the Internet-of-Things, cloud computing, Intelligent Transportation Systems, and fog computing, has led to the introduction of fog node-based VANET to serve resource-constrained devices. In the traditional security models of VANET, due to the use of a centralized trusted authority, there is a chance of single-point-of-failure and service unavailable with the increased service access requests. Also, there was one-to-one communication between each roadside unit and trusted authority. This may increase the system complexity and increase the traffic load. To address these issues, a novel authentication protocol for fog-enabled VANET based on multiple trusted authority model is discussed which reduces the chance of service unavailability and single-point-of-failure as the entire traffic load is distributed among multiple sub-trusted authority. Due to the incorporation of fog node, a group of roadside units can be controlled centrally, where trusted authority does not need to perform individual authentication for each roadside unit. The proposed protocol's security is rigorously examined through both informal and formal security analysis. Additionally, the protocol exhibits enhanced security features, as demonstrated in a performance comparison section, showcasing its ability to meet the security and privacy requirements while incurring relatively low communication and computation and storage costs. Thus, the proposed protocol offers a secure and efficient authentication protocol for fog-enabled VANET.

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来源期刊
Vehicular Communications
Vehicular Communications Engineering-Electrical and Electronic Engineering
CiteScore
12.70
自引率
10.40%
发文量
88
审稿时长
62 days
期刊介绍: Vehicular communications is a growing area of communications between vehicles and including roadside communication infrastructure. Advances in wireless communications are making possible sharing of information through real time communications between vehicles and infrastructure. This has led to applications to increase safety of vehicles and communication between passengers and the Internet. Standardization efforts on vehicular communication are also underway to make vehicular transportation safer, greener and easier. The aim of the journal is to publish high quality peer–reviewed papers in the area of vehicular communications. The scope encompasses all types of communications involving vehicles, including vehicle–to–vehicle and vehicle–to–infrastructure. The scope includes (but not limited to) the following topics related to vehicular communications: Vehicle to vehicle and vehicle to infrastructure communications Channel modelling, modulating and coding Congestion Control and scalability issues Protocol design, testing and verification Routing in vehicular networks Security issues and countermeasures Deployment and field testing Reducing energy consumption and enhancing safety of vehicles Wireless in–car networks Data collection and dissemination methods Mobility and handover issues Safety and driver assistance applications UAV Underwater communications Autonomous cooperative driving Social networks Internet of vehicles Standardization of protocols.
期刊最新文献
Decentralized multi-hop data processing in UAV networks using MARL Prediction-based data collection of UAV-assisted Maritime Internet of Things Hybrid mutual authentication for vehicle-to-infrastructure communication without the coverage of roadside units Hierarchical federated deep reinforcement learning based joint communication and computation for UAV situation awareness Volunteer vehicle assisted dependent task offloading based on ant colony optimization algorithm in vehicular edge computing
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