Document Type

Journal Article

Publication Title

IEEE Network

Volume

36

Issue

6

First Page

60

Last Page

66

Publisher

IEEE

School

School of Science

RAS ID

52369

Comments

This is an Authors Accepted Manuscript version of an article published by IEEE in IEEE Network, at https://doi.org/10.1109/MNET.103.2100338

© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Yan, S., Ihsan, U., Malaney, R., Sun, L., & Tomasin, S. (2022). Location verification for future wireless vehicular networks: Research directions and challenges. IEEE Network, 36(6), 60-66. https://doi.org/10.1109/MNET.103.2100338

Abstract

Vehicle location information obtained through the global navigation satellite system (GNSS) will play a pivotal role in emerging vehicular networks. This vital information is, however, susceptible to a host of unwanted manipulations, especially if a malicious entity is involved. The most obvious example of such manipulations is the forwarding by a malicious vehicle of false GNSS locations to other members of the network. Such events can lead to poor operational outcomes for the vehicular network, and in extreme cases even lead to catastrophic safety violations. Here, we highlight research efforts pursued in the past few years that have attempted to address this weakness in vehicular networks. We also discuss the importance of location verification in the wake of emerging wireless technologies, such as those being proposed for beyond 5G (B5G) wireless vehicular networks. In particular, we detail an opportunity to conduct location reporting and verification simultaneously with the aid of mmWave technology and discuss how emerging machine learning (ML) techniques will provide for location verification solutions where reliability levels will be commensurate with that required by the vehicular network paradigm. We close by discussing the potential enhancements for location verification within a future combined B5G-ML architecture.

DOI

10.1109/MNET.103.2100338

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