IEEE Consumer Electronics Magazine - November/December 2022 - 39

Guest Editors' Introduction
Security, Trust, and Privacy Solutions
for Intelligent Internet of Vehicular
Things-Part I
Uttam Ghosh
Meharry Medical College
Hellen Maziku
University of Dar es Salaam (UDSM)
Hari Prabhat Gupta
Indian Institute of Technology BHU
& THE INTERNET OF Things evolution have given
birth to several new groundbreaking applications,
such as the Internet of Vehicles (IoV), smart cities,
and cyber-physical systems. In the Internet of
Vehicles, the vehicles include various smart devices
to obtain and communicate information from
surroundings. This information can be helpful in
safe navigation, detecting hurdles, optimizing
routes, and in traffic management. For efficient decision-making,
in IoVs, V2V, and V2X communication
have been used to compliment onboard sensor
inputs and provide better services. A key concern
when relying on vehicle data is vulnerable to data.
Therefore, the need is to discuss the solutions that
provide security, trust, and privacy (STP) to both
communicating entities and secure vehicle data
from malicious entities. The use of artificial intelligence
(AI) in multidimensional makes them useful
for the Internet of Vehicular Things. An Intelligent
Internet of Vehicle Things gives the desired results
in the given time constraintswith less human effort.
Digital Object Identifier 10.1109/MCE.2022.3207333
Date ofcurrent version 6 October 2022.
The increasing number of Internet of Vehicle
Things (IoVT) resultsinanincreaseindataexploration
and risk to STP. This special section selected
seven articles to address the issues and challenges
related to STP in Intelligent IoVT. We briefly introduce
the accepted articles in the following.
In " Privacy-Preserving Deep Reinforcement
Learning in Vehicle Ad Hoc Networks, " U. Ahmed,
et al. propose a deep-reinforcement learning
method to sensitize the private information for a
given vehicle connected over vehicle ad hoc networks,
maintaining a balance between security
and privacy through any sanitization process.
Furthermore, the authors provide a set of recommendations
and potential applications for the
vehicle ad hoc networks as use cases.
In " Security, Trust, and Privacy for the Internet
of Vehicles: A Deep Learning Approach, "
G. Muhammad and M. Alhussein, propose a deep
learning model to process the data generated by
the IoVT. In addition, this article addresses several
STP issues in an intelligent transportation system.
Continuing the theme of preserving security
and privacy in an intelligent transportation system
(ITS) is M. Abdel-Basset et al.'s article titled
November/December 2022
Published by the IEEE Consumer Technology Society
2162-2248 ß 2022 IEEE
39
Biplab Sikdar
National University of Singapore
Joel J. P. C. Rodrigues
Federal University of Piauı
IEEE Consumer Electronics Magazine - November/December 2022

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