Vehicular networking is an emerging research area. It enables the vehicles equipped with communication and sensing capacities to communicate vehicle-to-vehicle or with available roadside infrastructure. It has significant applications in terms of information and traffic management and road safety. To make vehicular communication more effective, vehicular cloud computing (VCC) architecture is introduced by utilising vehicular resources, cloud computing infrastructure and internet of things environment. VCC provides a scalable platform to support intelligent transport systems. However, there is a lack of efficient and secure mutual authentication framework in VCC. This study presents a chaotic map-based mutual authentication framework for VCC to ensure secure and efficient communication along with anonymity. The authors use a simulation tool AVISPA ‘Automated Validation of Internet Security Protocols and Applications’ to verify the protocol security against active attacks. The study also includes the proof of security in the random oracle model to justify security claim against known attacks. It presents the study of performance to validate the efficiency of the proposed scheme. Moreover, a comparative study of performance attributes with related schemes to identify the improvement in communication and computation efficiency is included.

中文翻译：

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SFVCC：用于车辆云计算的基于混沌地图的安全框架

车载网络是一个新兴的研究领域。它使具备通信和传感功能的车辆能够在车辆之间或与可用的路边基础设施之间进行通信。它在信息和交通管理以及道路安全方面具有重要的应用。为了使车辆通信更加有效，通过利用车辆资源，云计算基础设施和物联网环境引入了车辆云计算（VCC）架构。VCC提供了可扩展的平台来支持智能运输系统。但是，在VCC中缺少有效且安全的相互身份验证框架。这项研究为VCC提出了一个基于混沌地图的相互认证框架，以确保安全和有效的通信以及匿名性。作者使用模拟工具AVISPA“ Internet安全协议和应用程序的自动验证”来验证针对主动攻击的协议安全性。该研究还包括随机预言模型中的安全性证明，以证明针对已知攻击的安全性是合理的。它提出了对性能的研究，以验证所提出方案的效率。此外，还对性能属性与相关方案进行了比较研究，以识别通信和计算效率的提高。它提出了对性能的研究，以验证所提出方案的效率。此外，还对性能属性与相关方案进行了比较研究，以识别通信和计算效率的提高。它提出了对性能的研究，以验证所提出方案的效率。此外，还对性能属性与相关方案进行了比较研究，以识别通信和计算效率的提高。