# Towards Mitigating Jellyfish Attacks Based on Honesty Metrics in V2X Autonomous Networks
## 3 Related Literature
The results of the simulation show that the addition of the IDS algorithm increases the performance of the network based on the quality of service (QoS) parameters: packet delivery ratio (PDR), throughput, and end-to-end delay compared with conditions under attacks. [PERSON] et al. [38] proposed utilizing a genetic algorithm to improve overall network performance in terms of latency, throughput, PDR, and energy efficiency for detecting and combating Jellyfish attacks in MANETs. This strategy is quite effective at providing a defense against Jellyfish's periodic dropping attacks. In order to combat Jellyfish reorder attacks on MANETs, the authors of [39] presented a secure link formation mechanism. They investigated severe flaws and backdoors in multicast routing protocols and suggested a defense technique that is both secure and robust. The proposed approach improves the throughput and packet delivery ratio in MANETs, according to simulation results. By designing a secure routing protocol, [PERSON] and [PERSON] [40] proposed a security method to protect MANETs from Byzantine attacks. The reliability is improved and congestion is decreased by choosing secured multiple pathways with only the defective links (not the entire path) removed. The Byzantine faults are located using adaptive probe signals. When the loss rate goes above a certain point, searching for the attackers will begin. Next, the routes between the source and the destination are appraised, and the most reliable ones are chosen for continued communication. By ignoring the tunnel path, the impact of periodic dropping and the Wormhole issue is reduced. [PERSON] et al. [41] employed a friendship-based Jellyfish attack detection method to reduce Jellyfish attack activity in MANETs. A direct trust-based detection policy (DTD) is used to control packet collisions, congestion, and error spreading in the network. The results demonstrate that the malicious activities in the network are immediately and properly controlled. For the removal of Jellyfish attacks in the network, the authors of [42] developed an authenticated routing system based on an attack detection framework that used a genetic fuzzy logic rule-based system. Fuzzification, rule evaluation, the aggregation of rule outputs, and defuzzification on the network are all examples of how fuzzy logic is applied in this study. This method is used with AODV as well as dynamic source routing (DSR) routing protocols and compared to other existing methods. [PERSON] et al. [20] proposed a new technique to ensure the prevention and detection of Jellyfish attacks in MANETs. This technique is a fusion of an authenticated routing-based framework for detecting Jellyfish attacks and a support vector machine (SVM) for learning packet forwarding behavior. The suggested technique uses the hierarchical trust evaluation property of nodes to select trusted nodes in a network for packet routing. The simulation results prove that the technique is quite effective in detecting Jellyfish attacks. [PERSON] and [PERSON] [43] designed a clustering routing protocol on the basis of ant colony optimization. This protocol is a clustering of nodes that uses trust tables to determine a network's efficiency. This work produces beneficial results by increasing secure communication in a network and by detecting Jellyfish attacks in a highly effective manner. [PERSON] and [PERSON] [44] implemented a delay-sensitive multipath selection algorithm to mitigate the Rushing attack in VANETs. The Rushing attack is an extreme and advanced sort of attack that can lead to Jellyfish or Byzantine attacks. In this work, they calculated each path delay by taking into account each vehicle's transmission, propagation, processing, and queuing delays, as well as geographical position. By checking the various delays, this approach successfully prevents Rushing attackers from entering the route discovery phase. [PERSON] et al. [45] discussed security attacks and their related solutions.