Energy Consumption Analysis Of Clone Detection Approaches In Wireless Sensor Networks

Ravi .T*, 0**
* Student, Department of Electronics and Communication Engineering, SreeVidyanikethan Engineering College, Tirupathi, A.P., India.
** Professor of ECE and Dean (Academics), Department of Electronics and Communication Engineering, Sree Vidyanikethan Engineering College, Tirupathi, A.P., India.
Periodicity:July - September'2014
DOI : https://doi.org/10.26634/jwcn.3.2.2874

Abstract

Wireless Sensor Network (WSN) is a group of sensor nodes which acquaint themselves over wireless channels and adversary who tries to capture and compromise nodes of a network. An adversary introduces clone to compromise larger area and extracts the secret keys from the sensor node or reprogram them. Clone attack is very hazardous and should be detected as soon as possible to protect our network. Recently, different clone detection schemes where proposed for WSNs, taking into consideration various network configurations and deployment strategies. In this paper the analysis is done on the existing clone detection schemes with regard to their device type, detection methodology, deployment strategy, and detection ranges. Simulation experiments are conducted to show variations in their performance. Finally, the authors are concluding that Randomized, Efficient and Distributed (RED), and Parallel Multiple Probabilistic Cells (P-MPC) schemes have shown good results for static sensors (under random uniform deployment and grid deployment respectively) compared to other schemes which the authors have been taken into consideration. For mobile sensor networks there is no such efficiently working scheme with existing approaches because of its maneuverability.

Keywords

Clone Attack, Clone Detection, Network Security, Deployment Strategy, Wireless Sensor Network (WSN)

How to Cite this Article?

Theja, G.R., and Subhas, C. (2014). Energy Consumption Analysis Of Clone Detection Approaches In Wireless Sensor Networks. i-manager’s Journal on Wireless Communication Networks, 3(2), 10-16. https://doi.org/10.26634/jwcn.3.2.2874

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