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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 11 Issue 7, 2020.
Abstract: Underwater Wireless Sensor Networks (UWSN) is widely used in variety of applications but none of the applications have taken network security into considerations. Deployment of underwater network is a challenging task and because of the hash underwater environment, the network is vulnerable to large class of security attacks. Recent research on underwater communication focuses mainly on energy efficiency, network connectivity and maximum communication range. The nature of underwater sensor network makes it more attractive for the attackers. One of the most serious problems in underwater networks is wormhole attack. In this research work we concentrate on providing security to the underwater network against wormhole attacks. We introduce the wormhole attack in the network and propose a solution to detect this attack in underwater wireless networks. Energy Efficient Hybrid Optical - Acoustic Cluster Based Routing Protocol (EEHRCP) is incorporated and using the round trip time and other characteristics of wormhole attack, the presence of the wormhole attack in the network is identified. The simulation results depicts that the proposed wormhole detection mechanism increases throughput by 26%, reduces energy consumption by 3%, reduces end to end delay by 13% and increases packet delivery ratio by 3%.
Tejaswini R Murgod and S Meenakshi Sundaram, “Cluster based Detection and Reduction Techniques to Identify Wormhole Attacks in Underwater Wireless Sensor Networks” International Journal of Advanced Computer Science and Applications(IJACSA), 11(7), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0110708
@article{Murgod2020,
title = {Cluster based Detection and Reduction Techniques to Identify Wormhole Attacks in Underwater Wireless Sensor Networks},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2020.0110708},
url = {http://dx.doi.org/10.14569/IJACSA.2020.0110708},
year = {2020},
publisher = {The Science and Information Organization},
volume = {11},
number = {7},
author = {Tejaswini R Murgod and S Meenakshi Sundaram}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.