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A Systematic Literature Review on Blockchain Enabled Federated Learning Framework for Internet of Vehicles - 2022

A Systematic Literature Review On Blockchain Enabled Federated Learning Framework For Internet Of Vehicles

Survey Paper on Blockchain Enabled Federated Learning Framework For Internet Of Vehicles

Research Area:  Machine Learning


While the convergence of Artificial Intelligence (AI) techniques with improved information technology systems ensured enormous benefits to the Internet of Vehicles (IoVs) systems, it also introduced an increased amount of security and privacy threats. To ensure the security of IoVs data, privacy preservation methodologies have gained significant attention in the literature. However, these strategies also need specific adjustments and modifications to cope with the advances in IoVs design. In the interim, Federated Learning (FL) has been proven as an emerging idea to protect IoVs data privacy and security. On the other hand, Blockchain technology is showing prominent possibilities with secured, dispersed, and auditable data recording and sharing schemes. In this paper, we present a comprehensive survey on the application and implementation of Blockchain-Enabled Federated Learning frameworks for IoVs. Besides, probable issues, challenges, solutions, and future research directions for BC-Enabled FL frameworks for IoVs are also presented. This survey can further be used as the basis for developing modern BC-Enabled FL solutions to resolve different data privacy issues and scenarios of IoVs.

Federated Learning Framework
Internet Of Vehicles
Deep Learning
Machine Learning

Author(s) Name:  Mustain Billah, Sk. Tanzir Mehedi, Adnan Anwar, Ziaur Rahman, Rafiqul Islam

Journal name:  Computer Science

Conferrence name:  

Publisher name:  arXiv:2203.05192

DOI:  10.48550/arXiv.2203.05192

Volume Information: