Abstract
Data from interconnected vehicles may contain sensitive information such
as location, driving behavior, personal identifiers, etc. Without
adequate safeguards, sharing this data jeopardizes data privacy and
system security. The current centralized data-sharing paradigm in these
systems raises particular concerns about data privacy. Recognizing these
challenges, the shift towards decentralized interactions in technology,
as echoed by the principles of Industry 5.0, becomes paramount. This
work is closely aligned with these principles, emphasizing
decentralized, human-centric, and secure technological interactions in
an interconnected vehicular ecosystem. To embody this, we propose a
practical approach that merges two emerging technologies: Federated
Learning (FL) and Blockchain.Â