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A Novel Friendly Jamming Scheme in Industrial Crowdsensing Networks against Eavesdropping Attack

Eavesdropping attack is one of the most serious threats in industrial crowdsensing networks. In this paper, we propose a novel anti-eavesdropping scheme by introducing friendly jammers to an industrial crowdsensing network. In particular, we establish a theoretical framework considering both the pro...

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Detalles Bibliográficos
Autores principales: Li, Xuran, Wang, Qiu, Dai, Hong-Ning, Wang, Hao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6022160/
https://www.ncbi.nlm.nih.gov/pubmed/29904003
http://dx.doi.org/10.3390/s18061938
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author Li, Xuran
Wang, Qiu
Dai, Hong-Ning
Wang, Hao
author_facet Li, Xuran
Wang, Qiu
Dai, Hong-Ning
Wang, Hao
author_sort Li, Xuran
collection PubMed
description Eavesdropping attack is one of the most serious threats in industrial crowdsensing networks. In this paper, we propose a novel anti-eavesdropping scheme by introducing friendly jammers to an industrial crowdsensing network. In particular, we establish a theoretical framework considering both the probability of eavesdropping attacks and the probability of successful transmission to evaluate the effectiveness of our scheme. Our framework takes into account various channel conditions such as path loss, Rayleigh fading, and the antenna type of friendly jammers. Our results show that using jammers in industrial crowdsensing networks can effectively reduce the eavesdropping risk while having no significant influence on legitimate communications.
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spelling pubmed-60221602018-07-02 A Novel Friendly Jamming Scheme in Industrial Crowdsensing Networks against Eavesdropping Attack Li, Xuran Wang, Qiu Dai, Hong-Ning Wang, Hao Sensors (Basel) Article Eavesdropping attack is one of the most serious threats in industrial crowdsensing networks. In this paper, we propose a novel anti-eavesdropping scheme by introducing friendly jammers to an industrial crowdsensing network. In particular, we establish a theoretical framework considering both the probability of eavesdropping attacks and the probability of successful transmission to evaluate the effectiveness of our scheme. Our framework takes into account various channel conditions such as path loss, Rayleigh fading, and the antenna type of friendly jammers. Our results show that using jammers in industrial crowdsensing networks can effectively reduce the eavesdropping risk while having no significant influence on legitimate communications. MDPI 2018-06-14 /pmc/articles/PMC6022160/ /pubmed/29904003 http://dx.doi.org/10.3390/s18061938 Text en © 2018 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Li, Xuran
Wang, Qiu
Dai, Hong-Ning
Wang, Hao
A Novel Friendly Jamming Scheme in Industrial Crowdsensing Networks against Eavesdropping Attack
title A Novel Friendly Jamming Scheme in Industrial Crowdsensing Networks against Eavesdropping Attack
title_full A Novel Friendly Jamming Scheme in Industrial Crowdsensing Networks against Eavesdropping Attack
title_fullStr A Novel Friendly Jamming Scheme in Industrial Crowdsensing Networks against Eavesdropping Attack
title_full_unstemmed A Novel Friendly Jamming Scheme in Industrial Crowdsensing Networks against Eavesdropping Attack
title_short A Novel Friendly Jamming Scheme in Industrial Crowdsensing Networks against Eavesdropping Attack
title_sort novel friendly jamming scheme in industrial crowdsensing networks against eavesdropping attack
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6022160/
https://www.ncbi.nlm.nih.gov/pubmed/29904003
http://dx.doi.org/10.3390/s18061938
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