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Detection and Avoidance of Clone Attack in IoT Based Smart Health Application

S. Vaishnavi1,*, T. Sethukarasi2

1 Department of Computer Science and Engineering, RMK College of Engineering and Technology, Chennai, 601206, India
2 Department of Computer Science and Engineering, RMK Engineering College, Chennai, 601206, India

* Corresponding Author: S. Vaishnavi. Email: email

Intelligent Automation & Soft Computing 2022, 31(3), 1919-1937. https://doi.org/10.32604/iasc.2022.021006

Abstract

The deployment of wireless sensors in the hostile environment makes them susceptible to malicious attacks. One of the most harmful attacks is the clone attack in which a malicious node illegitimately claims the identity of a genuine node in the network and eventually tries to capture the entire network. This attack is also termed as node replication attack. The mobile nature of wireless sensor network (WSN) in smart health environment increases the vulnerability of node replication attack. Since the data involved in smart health system are highly sensitive data, preserving the system from the attack by malicious nodes is a crucial task. In this research, we proposed a new scheme called Routing Protocol for Energy Efficient Networks (RPEEN) for the detection of clone attack in IoT-based smart health application. The main advantage of this scheme is the increase in the energy efficiency as the energy efficiency is the most important constraint in WSN systems. The performance of the proposed scheme is highlighted using parameters like time delay, residual energy, throughput, energy efficiency and error rate. Further, to portray the efficacy of the proposed algorithm, this algorithm is compared with the existing Hybrid Multi-Level Clustering (HMLC) algorithm. It has been found that the proposed RPEEN scheme achieves a time delay of 0.63 and 0.6 ms with 0 dead nodes and by avoiding clone attack respectively. Furthermore, the proposed scheme attains the highest residual energy of 49.5 J for the 2500 rounds. In addition, the proposed algorithm attains the highest throughput of 99.2% for the 50 nodes.

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Cite This Article

APA Style
Vaishnavi, S., Sethukarasi, T. (2022). Detection and avoidance of clone attack in iot based smart health application. Intelligent Automation & Soft Computing, 31(3), 1919-1937. https://doi.org/10.32604/iasc.2022.021006
Vancouver Style
Vaishnavi S, Sethukarasi T. Detection and avoidance of clone attack in iot based smart health application. Intell Automat Soft Comput . 2022;31(3):1919-1937 https://doi.org/10.32604/iasc.2022.021006
IEEE Style
S. Vaishnavi and T. Sethukarasi, "Detection and Avoidance of Clone Attack in IoT Based Smart Health Application," Intell. Automat. Soft Comput. , vol. 31, no. 3, pp. 1919-1937. 2022. https://doi.org/10.32604/iasc.2022.021006



cc Copyright © 2022 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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