An Efficient Cluster Computing Mechanism for Wormhole Attack Detection in MANET

Abstract

Eventually a mobile adhoc network embeds flexibility, dynamic nature and topology independence.
It extends its scope as the characteristics of MANETs by itself are subjected to security threats.
Enumerable routing protocols using conventional methods are foreseen, which are prone to simple
attacking systems. An attacker can capture the packets at a node without any intricacy by the
network and retransmit to the destination, recognized as wormhole attack. It can create an
unpredictable threat with the routing protocols in a wireless security system. None of the efficient
technique is developed yet to thwart such type of attack in a competent manner. Attackers focus on
the node to tap the information by this wormhole attack, which can be defendable by using
mechanism like Euclidean distance with cluster computing. However the machine learning system is
introduced with the K-means algorithm, hands on with Euclidean distance to define the mechanism
of defence there by implemented with LGF protocol in MANET’s.