Published Paper Details:

Machine learning (ML) approaches, based on several logical and statistical processes, provide a system the ability to learn and promote adaptability to the environment. Recognizing complicated patterns and making judgments based on the findings is the main objective of machine learning. Different machine learning methods are used to protect mobile ad hoc networks. The lack of infrastructure in MANETs makes it extremely difficult to build security measures. The security strategies used in MANETs primarily concentrate on routing path security, outlier/bad-behaviour/selfish node removal, intrusion detection, and the mitigation of malicious assaults. In order to provide effective security solutions, the researchers have been utilizing cutting-edge technologies while taking into account the dynamic environment of MANETs. These technologies include machine learning, artificial intelligence (AI), approaches based on genetic algorithms, algorithms inspired by biological processes, and others. This examination of several contemporary methods for enhancing security in MANETs is thorough and methodical, and it is presented in this paper.