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

Xuran Li, Qiu Wang, Hong-Ning Dai and 1 more

Sensors · 2018

doi:10.3390/s18061938 (opens in a new tab)

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Abstract

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.

Abstract licence: CC BY

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