## 5 The Concept of IoV  
### The Internet of Vehicles  
The unprecedented developments in computers and communication have escalated the implementation of IoV. The VANET is the previous version of IoV. IoV's primary objective is to ensure safe driving. While IoV has been embraced by the vehicle manufacturing industry, the technology presents myriad challenges and opportunities that are yet to be explored [75].  
Diverse network connections and varying road conditions are considered by intelligent vehicles that are controlled by sophisticated internal software. This software is responsible for managing and controlling vehicle systems. The software depends on information obtained from the interconnected devices and the internet. Most manufacturers decided to adopt IoV applications and start manufacturing their own cars when they discovered  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Citation** & **Year** & **IoV Security** & **IoV Trust** & **Machine Learning** & **Comparison** \\ \hline
[12] & 2017 & + & & The survey does not explore ML techniques and the trust scheme. \\ \hline
[74] & 2017 & + & & The survey discusses only security challenges and the trust and ML-based solutions are not explored. \\ \hline
[64] & 2018 & + & + & Only three types of trust models are considered. \\ \hline
[77] & 2018 & + & + & The survey does not provide a number of solutions based on ML techniques for security or trust in IoV. \\ \hline
[78] & 2018 & + & + & The authors present cryptographical solutions and ML-based solutions are missing. \\ \hline
[65] & 2019 & + & & The authors present many security solutions but detailed information on trust and ML techniques are missing. \\ \hline
[66] & 2020 & + & + & There is no security challenge discussed in this survey. \\ \hline
[76] & 2020 & + & + & The survey discussed ML-based solutions for security but not for trust. \\ \hline
[67] & 2020 & + & & The survey discusses only security protection but the trust and ML-based solutions are not presented. \\ \hline
[75] & 2020 & + & & The survey is missing the trust scheme and ML-based solutions in IoV. \\ \hline
[68] & 2020 & + & + & The survey does not discuss ML-based solutions for security and trust. \\ \hline
[69] & 2021 & + & & The survey is missing the trust scheme and ML-based solutions in IoV. \\ \hline
[70] & 2021 & + & + & Details about using ML-based solutions in the trust problem are missing. \\ \hline
[50] & 2022 & + & + & The authors do not explore the trust challenge and its solutions. \\ \hline
[71] & 2022 & + & & The survey does not explore ML and trust. \\ \hline
[72] & 2022 & + & & The survey does not mention ML or trust. \\ \hline
[73] & 2022 & + & & The authors present the security challenges of IoV environments, but ML-based solutions and trust are missing. \\ \hline Our Survey & 2023 & + & + & + & Our survey focuses on the areas of security, trust, and ML approaches. \\ \hline \hline \end{tabular}
\end{table}
Table 2: Comparison of surveys in terms of the focused areas of security, trust, and ML approaches.  
the process of converting vehicles from normal mobile nodes to intelligent vehicles. This discovery also brought stiff competition among renowned software-producing companies such as Apple, Google and Huawei [79].  
The emergence of IoV technology made it more convenient to own and drive a vehicle. In addition to improving traffic monitoring, the technology aimed to enhance comfortable driving, improve energy management, secure data transmission, and prevent road accidents. While this was good news, the new technology came with many challenges and opportunities. Some of the issues that have still not been addressed are achieving large-scale coverage, exchanging data in a secure environment, managing diverse network connections, and dealing with vehicles with a dynamic topology [80].