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Evolutionary Intelligence
Erschienen in: Evolutionary Intelligence 2/2021

05.09.2020 | Special Issue

A node to node security for sensor nodes implanted in cross cover multi-layer architecture using Mc-Nie algorithm

verfasst von: Kumar Babu Batta, Venkateswara Rao Gurrala, Vishnu Srinivasa Murthy Yarlagadda

Erschienen in: Evolutionary Intelligence | Ausgabe 2/2021

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Abstract

Security, and lifetime enhancement are the two key factors in the field of wireless sensor networks. Since the sensor nodes are placed in critical regions and are irreplaceable, it is essential to improve their lifetime through avoiding the energy consumption unnecessarily. Moreover, it is found that the sensor nodes are easily vulnerable due to their random placement. We propose a cross covered multi-layer architecture with an efficient Mc-Nie security algorithm. Moreover, the details of various attacks are also given in this paper. It is found that the proposed approach is performing well when compared to the recent state-of-the-art approaches. We have considered various parameters such as energy consumption, detecting the attacks, attack detection percentage, packet loss, and packet overhead in order to evaluate the performance of the proposed system. The improvement in energy consumption rate is around 81% when compared to the non-cross covered architecture.
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Fußnoten
1
Stack follows the principle of last-in-first-out (LIFO). The presented model layers also work with the top-down approach. Hence, we have used the term stack here.
 
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Metadaten
Titel
A node to node security for sensor nodes implanted in cross cover multi-layer architecture using Mc-Nie algorithm
verfasst von
Kumar Babu Batta
Venkateswara Rao Gurrala
Vishnu Srinivasa Murthy Yarlagadda
Publikationsdatum
05.09.2020
Verlag
Springer Berlin Heidelberg
Erschienen in
Evolutionary Intelligence / Ausgabe 2/2021
Print ISSN: 1864-5909
Elektronische ISSN: 1864-5917
DOI
https://doi.org/10.1007/s12065-020-00478-6

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