Integration of Blockchain Technology and Federated Learning in Vehicular (IoT) Networks: A Comprehensive Survey

Abdul Rehman Javed, Muhammad Abul Hassan, Faisal Shahzad, Waqas Ahmed, Saurabh Singh, Thar Baker, Thippa Reddy Gadekallu

Research output: Contribution to journalArticlepeer-review

Abstract

The Internet of Things (IoT) revitalizes the world with tremendous capabilities and potential to be utilized in vehicular networks. The Smart Transport Infrastructure (STI) era depends mainly on the IoT. Advanced machine learning (ML) techniques are being used to strengthen the STI smartness further. However, some decisions are very challenging due to the vast number of STI components and big data generated from STIs. Computation cost, communication overheads, and privacy issues are significant concerns for wide-scale ML adoption within STI. These issues can be addressed using Federated Learning (FL) and blockchain. FL can be used to address the issues of privacy preservation and handling big data generated in STI management and control. Blockchain is a distributed ledger that can store data while providing trust and integrity assurance. Blockchain can be a solution to data integrity and can add more security to the STI. This survey initially explores the vehicular network and STI in detail and sheds light on the blockchain and FL with real-world implementations. Then, FL and blockchain applications in the Vehicular Ad Hoc Network (VANET) environment from security and privacy perspectives are discussed in detail. In the end, the paper focuses on the current research challenges and future research directions related to integrating FL and blockchain for vehicular networks.
Original languageEnglish
Article number4394
JournalSensors
Volume22
Issue number12
DOIs
Publication statusPublished - 10 Jun 2022

Bibliographical note

Funding Information:
We would like to thank Vellore Institute of Technology, Vellore, India for paying partial APC for this study.

Publisher Copyright:
© 2022 by the authors. Licensee MDPI, Basel, Switzerland.

Keywords

  • blockchain
  • federated learning
  • intelligence transportation system
  • vehicular ad hoc network (VANET)
  • vehicular internet of things (IoT)

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