# A New Multivariate Approach for Real Time Detection of Routing Security Attacks in VANETs
## 3 Related Works  
Numerous studies in the literature have proposed methods to detect and countermeasure the black hole attack in VANETs. In one paper [19], a secure version of the AODV routing protocol was evolved to detect the black hole attack, relying on improvements of the RREQ and RREP routing packets. Further, cryptography function-based encryption and decryption were included to check the legitimacy of the source and the destination nodes. The reliability of the proposed approach was tested in terms of the following performance metrics: drop packets, end-to-end delay, packet delivery ratio (PDR), and routing request overhead. The researchers outlined that their proposed algorithm outperformed the original version of AODV. However, the improved version suffers from higher overheads and requires modifications of the AODV routing protocol's current version. Authors of [20] presented an intelligent scheme for black hole attack detection called IDBA that uses four main parameters: the sequence number, the hop count, the packet delivery ratio, and the end to end delay. First, an algorithm was proposed to pre-calculate the so-called thresholds regarding the future actions of the black hole based on the two first parameters, while a second algorithm was presented to compute thresholds for the two other performance metrics. The detection process floods alarms whenever these parameters are out of the predefined thresholds. The proposed IDBA was compared against AODV under black hole, Intrusion Detection System, and EAODV algorithms and showed its outperformance. A new approach for protecting VANET from black and gray hole attackers was developed in [21] named dual attack detection for black and gray hole attacks (DDBG). The suggested DDBG method employs the connected dominating set (CDS) method and two extra characteristics: the energy and the node's absence from the blacklist. The CDS technique is an efficacious, distinct, and confined method for recognizing nearly connected dominating sets of nodes within a small range. The selected IDS nodes broadcast a kind of status packet inside a size of the dominant set in order to obtain complete behavioral information from their nodes. Later, IDS nodes utilize the DDBG approach to examine the behavioral data obtained to identify malicious nodes and put them on the blacklist if the activity is suspicious. The authors of [22] suggested a novel IDS to detect black hole attack in mobile ad hoc networks based on a hybrid approach that makes use of both Adaptive Fuzzy Neuro Inference System (ANFIS) and Particle Swarm Optimization (PSO). The PSO is used to increase the efficiency of ANFIS by changing the membership functions and then reducing the error. The ANFIS predictions allow the attacker's future behavior to be modeled and detected. A database is extracted from the network by creating a neighbor table, which captures all the neighbors' activities. Afterward, the input parameters are calculated using this database. The authors used NS-2 simulation to demonstrate the effectiveness of their approach. Authors of [23] proposed a heuristic strategy for identifying black hole attacks in MANETs. The approach is based on a fake RREQ message format similar to RREP, which is frequently employed to transmit faked packets in the AODV route discovery mechanism. Hence, a black hole is entrapped by replying to the requested fake destination IP address,which never existed in the network. This allowed for the identification of single and cooperative black hole intrusions. In their paper [24], the authors presented a new intrusion detection system (IDS) for mitigating black hole attack. This solution, based on the two algorithms Integrated Cross Interior (ICI) and Preset Time Interval Algorithm (PTIA), enables the security of routing nodes by eliminating malicious activities. One of the most challenging tasks is to reduce routing costs while improving performance by reducing reaction time.