Federated Learning with Blockchain Approach for Trust Management in IoV

Abstract

The internet of vehicles (IoV), a variant of the traditional VANET, allows real-time data exchange between vehicles, roadside units, parking, and city infrastructure. Nevertheless, the IoV poses many security concerns due to its open nature. Traditional security solutions may not address all the IoV security risks and provide complete protection. Therefore, it is critical to establish trust and to identify dishonest nodes. As a result, trust management-based techniques are also required to improve IoV security. This paper proposes federated learning with a blockchain approach for trust management (FBTM) in IoV. Thus, a vehicular trust evaluation is designed to improve the data acquired for the federated learning model learning process. Moreover, a novel blockchain-based reputation system is developed to guarantee the storage and the share of global federated learning models. In the meanwhile, proof of reputation consensus is proposed to evaluate the roadside units operating as aggregators in the IoV network. Simulation results demonstrate that the proposed scheme is effective for IoV security.