Self-Sovereign Identity Management for Hierarchical Federated Learning in Vehicular Networks

Abstract

There has been a rapid increase in the number of connected vehicles with a huge amount of data exchange between these vehicles that needs to be communicated, processed and analyzed reliably and efficiently. For secure and decentralized authentication, self-sovereign identity (SSI) management in vehicular networks have attracted attention in recent years. Hierarchical deployment frameworks, on the other hand, can provide secure and efficient knowledge sharing for vehicular networks with heterogeneous and geographically distributed vehicles and infrastructure in 6G networks. In this paper, we explore the joint use of hierarchical federated learning, as a collaborative machine learning framework, and hierarchical SSI management in vehicular networks, highlighting its advantages, limitations. At the end of the paper, we also provide two illustrative use cases.