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Identifying Misbehaving Greedy Nodes in IoT Networks
One of the central communication infrastructures of the Internet of Things (IoT) is the IEEE 802.15.4 standard, which defines Low Rate Wireless Personal Area Networks (LR- WPAN). In order to share the medium fairly in a non-beacon-enabled mode, the standard uses Carrier Sense Multiple Access with Co...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8348411/ https://www.ncbi.nlm.nih.gov/pubmed/34372364 http://dx.doi.org/10.3390/s21155127 |
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author | Sadek, Fatima Salma Belkadi, Khaled Abouaissa, Abdelhafid Lorenz, Pascal |
author_facet | Sadek, Fatima Salma Belkadi, Khaled Abouaissa, Abdelhafid Lorenz, Pascal |
author_sort | Sadek, Fatima Salma |
collection | PubMed |
description | One of the central communication infrastructures of the Internet of Things (IoT) is the IEEE 802.15.4 standard, which defines Low Rate Wireless Personal Area Networks (LR- WPAN). In order to share the medium fairly in a non-beacon-enabled mode, the standard uses Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA). The nature of connected objects with respect to various resource constraints makes them vulnerable to cyber attacks. One of the most aggressive DoS attacks is the greedy behaviour attack which aims to deprive legitimate nodes to access to the communication medium. The greedy or selfish node may violate the proper use of the CSMA/CA protocol, by tampering its parameters, in order to take as much bandwidth as possible on the network, and then monopolize access to the medium by depriving legitimate nodes of communication. Based on the analysis of the difference between parameters of greedy and legitimate nodes, we propose a method based on the threshold mechanism to identify greedy nodes. The simulation results show that the proposed mechanism provides a detection efficiency of 99.5%. |
format | Online Article Text |
id | pubmed-8348411 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-83484112021-08-08 Identifying Misbehaving Greedy Nodes in IoT Networks Sadek, Fatima Salma Belkadi, Khaled Abouaissa, Abdelhafid Lorenz, Pascal Sensors (Basel) Article One of the central communication infrastructures of the Internet of Things (IoT) is the IEEE 802.15.4 standard, which defines Low Rate Wireless Personal Area Networks (LR- WPAN). In order to share the medium fairly in a non-beacon-enabled mode, the standard uses Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA). The nature of connected objects with respect to various resource constraints makes them vulnerable to cyber attacks. One of the most aggressive DoS attacks is the greedy behaviour attack which aims to deprive legitimate nodes to access to the communication medium. The greedy or selfish node may violate the proper use of the CSMA/CA protocol, by tampering its parameters, in order to take as much bandwidth as possible on the network, and then monopolize access to the medium by depriving legitimate nodes of communication. Based on the analysis of the difference between parameters of greedy and legitimate nodes, we propose a method based on the threshold mechanism to identify greedy nodes. The simulation results show that the proposed mechanism provides a detection efficiency of 99.5%. MDPI 2021-07-29 /pmc/articles/PMC8348411/ /pubmed/34372364 http://dx.doi.org/10.3390/s21155127 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Sadek, Fatima Salma Belkadi, Khaled Abouaissa, Abdelhafid Lorenz, Pascal Identifying Misbehaving Greedy Nodes in IoT Networks |
title | Identifying Misbehaving Greedy Nodes in IoT Networks |
title_full | Identifying Misbehaving Greedy Nodes in IoT Networks |
title_fullStr | Identifying Misbehaving Greedy Nodes in IoT Networks |
title_full_unstemmed | Identifying Misbehaving Greedy Nodes in IoT Networks |
title_short | Identifying Misbehaving Greedy Nodes in IoT Networks |
title_sort | identifying misbehaving greedy nodes in iot networks |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8348411/ https://www.ncbi.nlm.nih.gov/pubmed/34372364 http://dx.doi.org/10.3390/s21155127 |
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