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Intelligent Multilevel Node Authentication in Mobile Computing Using Clone Node

Neha Malhotra1,2,*, Manju Bala3

1 I.K.Gujral Punjab Technical University, Kapurthala, 144603, India
2 Lovely Professional University, Phagwara, 144411, India
3 Khalsa College of Engineering and Technology, Amritsar, 143001, India

* Corresponding Author: Neha Malhotra. Email:

(This article belongs to this Special Issue: Emerging Applications of Artificial Intelligence, Machine learning and Data Science)

Computers, Materials & Continua 2022, 70(3), 5269-5284.


Nodes in a mobile computing system are vulnerable to clone attacks due to their mobility. In such attacks, an adversary accesses a few network nodes, generates replication, then inserts this replication into the network, potentially resulting in numerous internal network attacks. Most existing techniques use a central base station, which introduces several difficulties into the system due to the network's reliance on a single point, while other ways generate more overhead while jeopardising network lifetime. In this research, an intelligent double hashing-based clone node identification scheme was used, which reduces communication and memory costs while performing the clone detection procedure. The approach works in two stages: in the first, the network is deployed using an intelligent double hashing procedure to avoid any network collisions and then in the second, the clone node identification procedure searches for any clone node in the network. This first phase verifies the node prior to network deployment, and then, whenever a node wants to interact, it executes the second level of authentication. End-to-end delay, which is bound to increase owing to the injection of clone nodes, and packet loss, which is reduced by the double hashing technique, were used to evaluate the performance of the aforementioned approach.


Cite This Article

N. Malhotra and M. Bala, "Intelligent multilevel node authentication in mobile computing using clone node," Computers, Materials & Continua, vol. 70, no.3, pp. 5269–5284, 2022.

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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