A survey on applying machine learning to enhance trust in mobile adhoc networks

Abstract

Mobile ad-hoc networks (MANETs) play a vital role in the increasingly networked world where it has many applications in plenty of important fields including military sector, business applications, social networks such as Vehicular Networks (VANETs), and other intelligent systems. Because of the dynamic nature of mobile ad-hoc networks, they are more tent to be objected to the various malicious attacks. Over the recent past decades, a certain amount of researches has been done to increase reliable and trustworthy communications in a MANET environment. Over the proposed solutions, Machine learning applications have significant results. Hence based on those, a critical analysis of existing machine learning-based trust approaches for mobile ad-hoc networks are presented here. The focus of this survey is to classify and evaluate the existing trust mechanisms and to provide guidance for future research work in the area.