## 2 Literature Review
The availability of the network is one of the crucial factors in the vehicular environment. If the network is not available, then no exchange of information takes place, which can lead to many disastrous events. [PERSON] et al. [27] focused on the DDoS attacks that targeted the RSUs in the network. A DDoS attack can render a system useless and deprive other entities of its resources. The authors proposed a framework for dealing with the detection and alleviation of low-rate DDoS attacks aimed at the RSUs which are hard to differentiate due to the fact that they evade certain filtering mechanisms. Due to the highly dynamic and rapid nature of the vehicular network, it has multiple vulnerabilities and is prone to many security attacks, e.g., DoS/DDoS attacks. A security mechanism was proposed by [PERSON] et al. [28], which prioritizes the wellbeing of individuals in vehicular networks by developing a statistical model which searches for extreme values that can be caused by the DoS/DDoS attacks. The proposed mechanism consumes a considerable amount of MAC frames, ARP requests, and features of DoS/DDoS attacks that are initiated by attacker vehicles with malicious intent. VANETs always play a crucial role in the development of a new breed of self-driving and semi-self-driving vehicles. Safety and comfort are not only provided to the passengers and drivers, but to the vehicles themselves, though such a network of vehicles is vulnerable to attacks such as black hole, gray hole, and rushing attacks. [PERSON] et al. [29] proposed an intelligent intrusion detection system (IDS) that protects the vehicles in the network from the gray hole and rushing attacks by detecting the anomalous behavior of the malicious nodes. These types of attacks are aimed to avert the transmissions that take place between the vehicles and the RSUs which can have fatal consequences for the new breed of self-driving and semi-self-driving vehicles. An effective misbehavior detection system (MDS) is needed to detect the erroneous information that is transmitted from the insider attacker nodes in the vehicular network. [PERSON] et al. [30] proposed a software-defined networking (SDN)-based detection framework for misbehaving vehicles with malicious intents. The authors exploited the characteristics of SDN, allowing them to dynamically change the parameters for the input according to the changing network. [PERSON] et al. [31] proposed a clustering-based detection mechanism for false downstream data in a fog-enabled vehicular environment. The authors used the fog servers to detect the malicious cluster head nodes and their anomalous data. They developed a clustering technique to accurately choose cluster head nodes and edge monitoring nodes for the detection of misbehaving vehicles and their malicious data. Ensuring trust levels in the vehicular environment is a very important factor that is often neglected. Higher trust levels mean that vehicles can safely exchange information with each other without any worries. A higher trust level also deals with many vulnerabilities that vehicles are exposed to in a connected environment. [PERSON] et al. [32] proposed a trust management mechanism that actively detects malicious nodes in the network and prevents their attacks which can degrade or cripple the network, while the use of blockchain ensures the trustworthiness of the data being exchanged.