Development and Analysis of a Better AODV Routing Protocol for Improved Network Performance in Manets Using a Machine Learning Model
摘要
A MANET is a self-configurable wireless ad hoc network that does not support demobilization. The route is susceptible to many security vulnerabilities because of its adaptability. IDS performance should be changed as a result to remedy this. In this study, a method for increasing IDS’s precision and rate of identification for the AODV routing protocol is presented. It relies on the Machine Learning (ML) method. In contrast to previous assaults, wormhole assaults use a secret, out-of-band channel to initiate the attack, making detection more difficult. This kind of assault does not involve any cryptographic weaknesses on the part of the attacker. One type of Denial of Service assault is the wormhole assault.