Blockchain Empowered Asynchronous Federated Learning for Secure Data Sharing in Internet of Vehicles

In Internet of Vehicles (IoV), data sharing among vehicles for collaborative analysis can improve the driving experience and service quality. However, the bandwidth, security and privacy issues hinder data providers from participating in the data sharing process. In addition, due to the intermittent and unreliable communications in IoV, the reliability and efficiency of data sharing need to be further enhanced. In this paper, we propose a new architecture based on federated learning to relieve transmission load and address privacy concerns of providers. To enhance the security and reliability of model parameters, we develop a hybrid blockchain architecture which consists of the permissioned blockchain and the local Directed Acyclic Graph (DAG). Moreover, we propose an asynchronous federated learning scheme by adopting Deep Reinforcement Learning (DRL) for node selection to improve the efficiency. The reliability of shared data is also guaranteed by integrating learned models into blockchain and executing a two-stage verification. Numerical results show that the proposed data sharing scheme provides both higher learning accuracy and faster convergence.

I. Introduction

The rapid development of new computing and communication technologies in 5G networks and beyond opens up possibilities for advanced vehicular services and applications such as autonomous driving and content delivery, which can yield improved driving experience. In this context, Internet of Vehicles (IoV), a new paradigm that integrates intelligent computing and vehicle's networking into vehicular networks [1], emerges as a crucial area. In the IoV, a large amount of diverse types of data is constantly generated by the moving vehicles, which includes additional data such as trajectories, traffic information and multimedia data. How to efficiently and effectively utilize the massive amount of available data to improve the driving experience and to provide extensive high-quality services in IoV, is a problem of paramount importance.