One of the principal missions of security in the Internet of Vehicles (IoV) is to establish credible social relationships. The trust management system has been proved to be an effective security solution in a connected vehicle environment. The use of trust management can play a significant role in achieving reliable data collection and dissemination and enhanced user security in the Internet of Vehicles. However, due to a large number of vehicles, the limited computing power of individuals, and the highly dynamic nature of the network, a universal and flexible architecture is required to realize the trust of vehicles in a dynamic environment. The existing solutions for trust management cannot be directly applied to the Internet of Vehicles. To ensure the safe transmission of data between vehicles and overcome the problems of high communication delay and low recognition rate of malicious nodes in the current trust management scheme, an efficient flow forwarding mechanism of the RSU close to the controller in the Software-Defined Vehicular Network is used to establish a hierarchical hybrid trust management architecture. This method evaluates the dynamic trust change of vehicle behavior based on the trust between vehicles and the auxiliary trust management of the infrastructure to the vehicle, combined with static and dynamic information and other indicators. The proposed trust management scheme is superior to the comparative schemes in resisting simple attacks, selective misbehavior attacks, and time-dependent attacks under the condition of ensuring superior real-time performance. Its overall accuracy is higher than that of the baseline scheme.

中文翻译：

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支持 SDN 的 VANET 中的分层混合信任管理方案

车联网 (IoV) 安全的主要任务之一是建立可信的社会关系。信任管理系统已被证明是联网车辆环境中的有效安全解决方案。信任管理的使用可以在实现可靠的数据收集和传播以及增强车联网中的用户安全方面发挥重要作用。然而，由于车辆数量众多、个人计算能力有限以及网络的高度动态性，需要一种通用且灵活的架构来实现动态环境中车辆的信任。现有的信任管理解决方案不能直接应用于车联网。为保证车辆间数据的安全传输，克服当前信任管理方案通信延迟高、恶意节点识别率低的问题，在软件定义的车载网络中，RSU靠近控制器的高效流转发机制用于建立分层混合信任管理架构。该方法基于车辆之间的信任和基础设施对车辆的辅助信任管理，结合静态和动态信息等指标，对车辆行为的动态信任变化进行评估。所提出的信任管理方案在保证卓越实时性的条件下，在抵抗简单攻击、选择性不当行为攻击和时间依赖攻击方面优于对比方案。