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Abstract

MANET is an infrastructure-less ad-hoc network.It is a collection of mobile nodes that are connected in an arbitrary and dynamic manner.ANN (Artificial Neural Network) is a type of Machine Learning scientific and statistical model that is used by computer systems in order to perform a task without involvement of explicit intrusion, rather than relying on interference and patterns instead.As there is node mobility that can impose different security issues, MANETs are found more susceptible in security provision.In order to resolve this security issue, some authentication and encryption techniques can be proposed for the first-line defence in order to mitigate the security risks.However, complete eradication of these types of risks is next to impossible.For the second-line defence, the necessity of an Intrusion Detection System (IDS) is essential in this case.IDS can be referred as a method tool or resource that can help to detect access and warn for any activity of unapproved or unauthorised network activity.Thus, it is important to deploy a hybrid network using ANN based and data mining based IDS systems that can enable the system in making decisions on intrusion in a mobile environment.This paper is going to present a hybrid model for IDS using ANN and data mining approaches.