Investigating the prospect of leveraging blockchain and machine learning to secure vehicular networks: a survey

Mahdi Dibaei, Xi Zheng*, Youhua Xia, Xiwei Xu, Alireza Jolfaei, Ali Kashif Bashir, Usman Tariq, Dongjin Yu, Athanasios V. Vasilakos

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)

Abstract

With recent developments in communication technologies, vehicular networks have become a reality with various applications. However, the cybersecurity aspect of vehicular networks is still an open issue that needs to be addressed with novel defence mechanisms against attacks. This paper first presents the state-of-the-art communication technologies in vehicular networks (either inter-vehicle networking or in-vehicle networking) along with their applications. Then we explore novel technologies including machine learning and blockchain as cybersecurity defence mechanisms in vehicular networks. Based on the extensive survey, we highlight some insights for future research to secure vehicular networks.
Original languageEnglish
Pages (from-to)683-700
Number of pages18
JournalIEEE Transactions on Intelligent Transportation Systems
Volume23
Issue number2
Early online date20 Aug 2021
DOIs
Publication statusPublished - Feb 2022

Keywords

  • Vehicular networks
  • blockchain
  • deep learning
  • machine learning

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