Empowered by 5G communication technology, high-speed information exchange can be realized on the Internet of Vehicles (IoV) for future intelligent transportation applications. Since most applications require vehicles to report perceived information to nearby base stations, how to defend against malicious attacks and selfish behaviors of vehicles in reporting activities has become an essential security issue. Some researchers have attempted to encourage vehicles to actively report truthful information by establishing reputations for them, but these efforts have some shortcomings. In model design, they neither verify the basis and process of reputation evaluation nor pay attention to the diversity and intelligence of vehicle behaviors. In system construction, they not only fail to meet the management needs of multi-party participation but also fail to provide verifiable reputation management services. In this paper, we propose $\mathcal{R}$ -tracing, a consortium blockchain-based vehicle reputation management scheme. The main contribution of our work lies in three points. First, a vehicle reputation model is designed with a reward and punishment mechanism and a regular tax mechanism. Second, a vehicle reputation management system is constructed by using Hyperledger Fabric, in which all tasks of reputation value update are abstracted into three types of transactions. Finally, the effectiveness of $\mathcal{R}$ -tracing is verified by extensive simulations running on a large-scale traffic scenario and performance evaluation on a prototype system. Compared with the typical linear reputation model, our model not only resists the usual malicious attack and selfish behavior but also effectively deals with the on-off attack and rational selfish behavior improved by intelligent vehicles. In the test of throughput, $\mathcal{R}$ -tracing achieves 600/textittps, outperforming two state-of-the-art blockchain-based schemes.

Inefficient data transmission has been a development bottleneck of Vehicular Ad-hoc NETworks (VANETs), especially in urban areas. It has been proved that many complex IP-based solutions are difficult to be applied in the highly dynamic and link-interrupted vehicular environment. In recent years, Named Data Networking (NDN) has become the most popular realization of Information-Centric Networking (ICN) for future networks. Its characteristics of multi-source, multi-path and in-network caching are helpful for improving the data transmission in VANETs. However, the bottom layer of vehicles cannot provide multiple interfaces to different domains like the routers in wired networks. Thus interface-based forwarding degenerates into directionless broadcasting with low performance and high overhead. Against this problem, we propose COMPASS, a novel named data transmission protocol for VANETs. Firstly, a dynamic directional interface model is built as the cornerstone of our COMPASS. Secondly, the forwarding strategies are improved for rapid interest dissemination and named data retrieving. Besides, an interface remapping method and the update strategies of Forwarding Information Base (FIB) and Pending Interest Table (PIT) are designed to enhance the robustness in high-mobility environment. Finally, the performance of COMPASS is verified on ndnSIM. Compared with the other three state-of-the-art protocols, COMPASS obtains the highest interest satisfaction ratio and the shortest transmission delay in urban traffic scenarios with restricted communication and storage overhead.

The rise of 5G communication technology brings opportunities to traffic-oriented crowdsourcing in the Internet of Vehicles (IoV). As vehicles act as workers in many traffic-oriented crowdsourcing systems, there's a growing focus on how to get high-quality reports when some vehicles may be malicious or selfish. Some researchers assign reputation values to vehicles and select high-reputation vehicles to complete tasks, but these efforts still have shortcomings. In model design, guaranteeing the objectivity of reputation calculation, suppressing malicious and selfish behaviors, and maximizing the utilities of honest vehicles and service providers should be considered simultaneously. In system construction, reputation verification service in multi-party intelligent transportation scenarios and reputation management system performance should be satisfied. In this paper, we propose $\mathcal {R}$ -manager, a consortium blockchain-based vehicle reputation management scheme. Firstly, we design a reputation model that uses confirmed results to update reputation and suppress malicious and selfish behaviors based on reputation deposit forfeit and a tax mechanism. Besides, the model maximizes the utilities of crowdsourcing participants by reaching the game equilibrium. Secondly, we design a reputation management system based on a consortium blockchain to abstract management activities as transactions and verify them by executing smart contracts, which meet multi-party management and reputation verification needs. Moreover, we design a half-committee endorsement strategy to improve system performance. Finally, our model is verified by simulation, and it can better suppress malicious and selfish behaviors compared with three different reputation models. We implement a prototype system and evaluate its performance. $\mathcal {R}$ -manager outperforms two state-of-the-art blockchain-based schemes.