A Hierarchical Blockchain-Enabled Federated Learning Algorithm for Knowledge Sharing in Internet of Vehicles

TLDR

Internet of Vehicles relies on collaborative data sensing, computing, and processing, and while big data and AI promise efficient knowledge sharing, security, privacy, and the limitations of conventional AI algorithms in distributed vehicular networks pose significant challenges. This study proposes a hierarchical blockchain framework coupled with a hierarchical federated learning algorithm to enable secure and efficient knowledge sharing among vehicles. The framework trains vehicles on environmental data using machine learning, shares the learned knowledge through a blockchain‑enabled trading market modeled as a multi‑leader, multi‑player game, and incorporates a federated learning algorithm tailored for distributed patterns and privacy requirements. Simulations demonstrate that the hierarchical blockchain‑enabled federated learning system is feasible for large‑scale vehicular networks, improves sharing efficiency and learning quality, and effectively mitigates malicious attacks.

Abstract

Internet of Vehicles (IoVs) is highly characterized by collaborative environment data sensing, computing and processing. Emerging Big Data and Artificial Intelligence (AI) technologies show significant advantages and efficiency for knowledge sharing among intelligent vehicles. However, it is challenging to guarantee the security and privacy of knowledge during the sharing process. Moreover, conventional AI-based algorithms cannot work properly in distributed vehicular networks. In this paper, a hierarchical blockchain framework and a hierarchical federated learning algorithm are proposed for knowledge sharing, by which vehicles learn environmental data through machine learning methods and share the learning knowledge with each others. The proposed hierarchical blockchain framework is feasible for the large scale vehicular networks. The hierarchical federated learning algorithm is designed to meet the distributed pattern and privacy requirement of IoVs. Knowledge sharing is then modeled as a trading market process to stimulate sharing behaviours, and the trading process is formulated as a multi-leader and multi-player game. Simulation results show that the proposed hierarchical algorithm can improve the sharing efficiency and learning quality. Furthermore, the blockchain-enabled framework is able to deal with certain malicious attacks effectively.