A Literature Survey on Intrusion Detection System in Manets using Machine Learning Techniques

Abstract

Since, a decade of time Mobile Ad hoc Networks (MANETs) have come with wireless networking technology. Due to its dynamic in nature of MANETs, these are vulnerable to various attacks in all the OSI layers but research shows that in Network layer the attacks are effectively done by intruders. In this survey many of the attacks at Network layer are identified in MANETs by most of the researchers which is outlined in this paper. Mostly, AODV routing protocols and other protocols are used for transferring packets in the direction of the destination. These transferred packets data is then deposited within the log files, to surveillance these routing of packets from these Log files, the techniques used in MANETs are Data mining, Support Vector Machines (SVM), Genetic algorithms (GA) and other Machine learning approaches. Further, the methodologies and techniques proposed for detecting and predicting these attacks from various kinds of intrusions within the MANETS is discussed.