IEEE Consumer Electronics Magazine - November/December 2022 - 54

Security, Trust, and Privacy Solutions for Intelligent Internet of Vehicular Things
Figure 3. Delay caused by the 1-D CNN model
using different numbers of vehicles in a group.
operation. The number of filters and the dimensions
of the filters are shown in the figure. The
numbers of neurons in each FC layer is also
shown. The purpose of the 1-D CNN model is to
process the 1-D data obtained by the IoVT in
short time. The shortcut allows the algorithm to
find the global optimum.
The model was trained using ambient temperature
and the speed of cars. The data were
obtained using simulation software. The temperature
data amounted to 10 MB, and the car speed
date was 12 MB. 70% of the data were used for
training and 10% for validation; the other 20%
were used for testing.
Using a line of cars constituted of different
numbers of cars, Figure 3 indicates the delay (in
ms) introduced by the current 1-D CNN model.
The temperature and speed of the cars, to be
passed from the cars to the edge controller, is
shown in the diagram. We can observe from the
illustration that the delay is suitable for realtime
service. The IEEE 802.11 MAC protocol was
used in the simulations, and the transmission
range was set to 350 m. It should be noted that,
considering the limited range, not all signals
arrive at the edge controller due to barriers and
channel disputes.
SECURITY, TRUST, AND PRIVACY
CHALLENGES
Data security for ITS implies the anonymity of
a pilot, traveler, rider, footballer, or athlete.8 The
first and last name, driver's license number, vehicle
registration number, etc., should be used for
ITS. The concept of utilizing pseudonyms, often
called pseudoIDs, instead of connecting real54
world
personalities to vehicles that are part of an
ITS network was recently realized. The research
has shown that pseudonyms have the capacity to
protect the connection between VANET messages
carrying security details, including the
location of a vehicle, and the identity of the message
sender.9 Malicious actors can still trace particular
vehicles using simple pseudonyms. In
response, pseudonym analysis inside the
VANETs as an option to the usage of pseudonyms
for the defense of privacy, attribute-based credentials
can be proposed. Privacy-boosting attribute
parameters enable users to be safe and
authenticate verifiers to ensure that users are not
connected to authentication incidents and that
only certain attributes that are important for the
verifier are revealed from their credentials.
There is a vast potential for violating human
privacy with comprehensive and accurate details
on ITS users, from financial information to information
about where the device is installed and to
users' actions. Behavioral data security refers to
data privacy within the scope of an ITS, which
defines different facets of a community or persons
and their activities within an ITS. In order
for a behavioral privacy scheme to be sustained,
it must be able to anonymize and secure the consumer
data obtained from exposures and to hide
the typical behavioral habits of ITS users.
The ITS contains a broad range of innovations
for different purposes and priorities. This
intrinsic heterogeneity exacerbates the challenge
to ensure that certain elements are healthy
to use and are incorporated through an ITS.10 In
addition to the currently existing insecure modules,
there could be additional vulnerabilities
and exploitable risks as well as interactions with
various components. In addition, products from
multiple suppliers that are designed for the
same purpose may be built in compliance with
varying requirements, resulting in complexities
in detailed vulnerability research solutions.
There are two basic restrictions on safety
strategies given the rising pace of acceptance of
and improvements in ITS technology. The first is
scalability: defense technologies from ITS must
have the means for smooth consistency with
their expanding implementation sizes. For example,
in extremely large ITS deployments, every
key delivery mechanism or intrusion detection
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