Machine Learning Cross Layer Technique to Detect Sink Hole Attacks in MANET

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G.Usha 1,* K.Mahalakshmi 1

1. Karpagam College of Engineering,Coimbatore,India

* Corresponding author.


Received: 3 Apr. 2016 / Revised: 1 May 2016 / Accepted: 10 Jun. 2016 / Published: 8 Jul. 2016

Index Terms

AODV (Adhoc on demand distance vector routing), Cross Layer Security, Mobile adhoc networks, Security


Adhoc networks uses mobile nodes to communicate among itself in which it does not have any fixed infrastructure like access point or base station. Due to dynamic network topology MANET security is a challenging task. Most of the routing protocols in MANET assumes a cooperative environment for communication. But, in the presence of malicious nodes, providing security to MANET is critical issue. Due to the increasing applications of MANET building an effective intrusion detection system are essential. This paper addresses using an intelligent approach for intrusion detection in MANET using cross layer technique. We show an paradigm of SVMs, FDAs and AIS approaches for intrusion detection in terms of classification accuracy.

Cite This Paper

G.Usha, K.Mahalakshmi, "Machine Learning Cross Layer Technique to Detect Sink Hole Attacks in MANET", International Journal of Modern Education and Computer Science(IJMECS), Vol.8, No.7, pp.61-67, 2016. DOI:10.5815/ijmecs.2016.07.07


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