## 2 Background
### An Overview of Internet of Vehicles
#### 2.1.4 Security in Internet of Vehicles  
IoV technologies are developing rapidly, and a number of industries investing in these technologies are in a race to launch state-of-the-art self-driving vehicles. These rapid advancements in IoV result in security issues that threaten not only the industry but consumers as well [8]. The challenge lies in preventing security breaches and privacy violations in IoV, making it less susceptible to cyberattacks [3].  
Cyberattacks in Internet of Vehicles Networks  
Vehicular sensor networks comprise a variety of vehicle sensors used to monitor and measure various physical parameters associated with the vehicle and the environment in which it is located. These sensors contribute to a more comfortable driving experience and smoother driving operations. Table 1 lists some of the most frequently employed smart vehicle sensors. Each of these sensors is built using cutting-edge electronic components and communication systems. Due to their limited available resources, implementing sophisticated and reliable security algorithms on these sensors directly is impractical. Consequently, these sensors are susceptible to various cyberattacks [16].  
IoVs are susceptible to several types of attacks and threats, including the following:  
* The flow of bogus information: Attackers use fake information to make users believe in a false environment.
* Message injection attack: Attackers send seemingly legitimate messages to gain access to one or more entities, which they can also utilize to send out malicious messages [16].
* Replay attack: Attackers iterate messages to gain unlawful access to the network's services and resources [17].
* Cookie theft attack: Resembling the previous attack, attackers use a copy of the cookies they stole to reach the network's resources.
* Sybil attack: Attackers create fabricated vehicles around the vehicle they are targeting and generate a signal jam, compelling the target to use an alternate path. To do this, they use a countless number of fake IDs for a single node to create the appearance of multiple nodes [18].
* Man-in-middle attack: Attackers insert themselves between two communicating entities. In this type of attack, which can be active or passive, the attackers can receive messages from one entity and send them to the other [16].
* Denial-of-service and distributed denial-of-service attacks: Attackers attempt to disrupt the network's efficiency by flooding the target channel with messages that exceed its handling capacity. This is carried out to use the network's limited resources illegally [10].
* Dissimulation of GPS attack: Attackers intercept and modulate GPS signals before the intended receiver receives them. This type of attack can endanger the lives of the people in the target vehicle as they are given the wrong directions.
* Impersonation attack: As the name implies, attackers impersonate the identity of a legitimate user on the network to spoof unsuspecting vehicles on the network with messages that are not only fictitious but dangerous.  
* Masquerading attack: Again, as the name implies, attackers masquerade as authorized users. Unlike the previous attack, attackers copy the legitimate ID of one of the network's nodes and can create two different senders using the same identity.
* Wormhole attack: Attacker nodes fake incorrect information about the distance from the target node, aiming to obtain every message sent from the receiver to flow through it. Deadlocks are typically created by these types of attacks [17].
* Eavesdropping attack: Attackers passively listen to the communication on the network. They become a part of the network, aiming to secretly obtain confidential, sensitive data and use it unlawfully.