Paper Details: Downloads: 493
Serial Number: P1141133721
Title: Lightweight and Distributed Wormhole Attack Detection for Wireless Sensor Networks Based on Graph Neuron
Authors: Moneer Alshaikh and Asad Khan
Abstract: Wormhole attack is a very serious issue as it threatens damage routing protocol functionality. Wormhole attack is also difficult to detect. Many studies have attempted to deal with wormhole attack detection, yet existing wormhole detection techniques remain ineffective because they either do not consider the resource constraints of WSNs or require special hardware. Hence, we attempted to design a distributed wormhole detection technique, implanted using GN theory.This paper proposed a distributed wormhole detection technique.The proposed detection technique utilises a GN algorithm to detect the attack tunnel. The network legal connectivity is represented as patterns. Then the network will be monitored by the GN application to detect any change in its legal connectivity graphs, which would indicate an attack. The system assumptions and network architecture for this detection technique were carefully developed to achieve better detection accuracy for the network than did previous attempts to improve WSN security. The results of the simulation demonstrate that our proposed detection technique enjoys reasonable accuracy.
Keywords: Wireless Sensor Networks (WSNs) , Graph Neuron(GN), Wormhole Attacks
Journal/Conference: ICGST Conference on Computer Science and Engineering, CSE-11
Volume:
Issue:
Submission Date: 8/14/2011 12:00:00 AM
Review Date: 9/21/2011 11:08:46 AM
Publishing Date: 12/19/2011 12:00:00 AM
Article Downloads: 493
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