# FSCB-IDS: Feature Selection and Minority Class Balancing for Attacks Detection in VANETs
## 2 Background and Related works  
### Background  
This section provides background and recent work that has focused on intrusion detection approaches incorporating ML techniques for securing VANETs. In VANET, vehicles are connected together using both V2V and V2I communication through RSUs and mobile broadband such as 4G/LTE [7]. VANET services comprise vehicular and road security services, efficiency and traffic control services, as well as info services. The safety services for vehicles and roads are to reduce traffic accidents and the death of vehicle users [8]. Efficiency and traffic control services focus on the improvement of traffic flow, traffic management, as well as providing location and mapping information. The objective of information services is to ensure the accessibility of the data, including the transfer of multimedia data and the connection to the Internet [9; 10]. The VANET communication architecture may be categorized as Wi-Fi-based ad hoc and hybrid wireless access in vehicle environments (WAVE). In the Wi-Fi-based WAVE architecture, RSUs locatedalong roadways are used as wireless access nodes which provide communication service to vehicles in their area of coverage. In ad hoc architecture, a group of vehicles are forming ad hoc networks by utilizing WAVE. Those networks work in an autonomous way, with no infrastructure. For hybrid architecture, the cellular and ad hoc architectures employing WAVE execute tasks in collaboration [11]. Initially, VANETs utilized Dedicated Short Range Communications (DSRC), using 75 MHz of bandwidth. The previous standards were not adapted to the expected functions and uses of VANETs. Additional enabling communication is improving the reach of VANETs and enhancing connectivity to more types of supporting technologies such as the Internet of Things (IoT) [12] and cloud computing [13]. Vehicular networks share the same characteristics as predictable ad hoc sensor networks, such as self-structuring and lack of central control [14]. VANETs have some exclusive challenges that force the design of the communication system and the security of its protocol [15]. VANETs constitute the technical basis for the visualization of Intelligent Transport Systems (ITS). The vehicles are characterized by their V2V and V2I communication capabilities [16]. The large number of nodes circulating inside the VANET network, with a high degree of mobility and a high frequency of topological changes, constitute a major challenge for this type of network as the nodes potentially move at high speed. In addition, the challenge of the complexity of keeping the confidentiality of the information related to the security is also a critical challenge, as the data contained in the messages exchanged in the network are broadcasted to all the users of this network and must not be confidential. Finally, vehicle communication capabilities can expose driver or user information such as ID, speed, location, and mobility patterns, which poses a privacy issue. Regardless of the need for message authentication and non-repudiation of safety messages, user and driver privacy must be valued, especially location privacy and ambiguity [15]. Figure 1 presents the architecture of VANET network, illustrating the different forms of communication. VANETs have a direct connection to the Internet, which makes them susceptible to many security problems. As a result, Intrusion Detection Systems IDSs are identified as one of the leading strategies to address the challenges of VANET security. Specifically, IDSs might be used to protect any network against attacks. IDS is used to detect abnormal activities over a network [17; 18; 19]. IDSs are suggested to detect attacks that are internal and not detectable by cryptographic systems. An IDS is generally implemented as the second layer of security following cryptography methods [20; 21]. There are two different approaches of intrusion detection: the anomaly detection and the misuse detection.