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

Xuran Li; Qiu Wang; Hong Ning Dai; Hao Wang

doi:10.3390/s18061938

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

Xuran Li, Qiu Wang, Hong Ning Dai^*, Hao Wang

^*Corresponding author for this work

Department of Computer Science

Research output: Contribution to journal › Journal article › peer-review

14 Citations (Scopus)

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.

Original language	English
Article number	1938
Number of pages	23
Journal	Sensors (Switzerland)
Volume	18
Issue number	6
DOIs	https://doi.org/10.3390/s18061938
Publication status	Published - 14 Jun 2018

Scopus Subject Areas

Analytical Chemistry
Biochemistry
Atomic and Molecular Physics, and Optics
Instrumentation
Electrical and Electronic Engineering

User-Defined Keywords

Crowdsensing
Friendly jamming
Industrial internet of things
Security

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.3390/s18061938

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title = "A Novel Friendly Jamming Scheme in Industrial Crowdsensing Networks against Eavesdropping Attack",

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.",

keywords = "Crowdsensing, Friendly jamming, Industrial internet of things, Security",

author = "Xuran Li and Qiu Wang and Dai, {Hong Ning} and Hao Wang",

note = "The work described in this paper was partially supported by Macao Science and Technology Development Fund under Grant No. 0026/2018/A1, the National Natural Science Foundation of China under Grant No. 61672170 and the Science and Technology Planning Project of Guangdong Province under Grant No. 2017A050501035. The authors would like to express their appreciation for Gordon K.-T. Hon for his thoughtful discussions. The authors would also like to thank the anonymous reviewers for their constructive comments. Publisher Copyright: {\textcopyright} 2018 by the authors. Licensee MDPI, Basel, Switzerland.",

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doi = "10.3390/s18061938",

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AU - Li, Xuran

AU - Wang, Qiu

AU - Dai, Hong Ning

AU - Wang, Hao

N1 - The work described in this paper was partially supported by Macao Science and Technology Development Fund under Grant No. 0026/2018/A1, the National Natural Science Foundation of China under Grant No. 61672170 and the Science and Technology Planning Project of Guangdong Province under Grant No. 2017A050501035. The authors would like to express their appreciation for Gordon K.-T. Hon for his thoughtful discussions. The authors would also like to thank the anonymous reviewers for their constructive comments. Publisher Copyright: © 2018 by the authors. Licensee MDPI, Basel, Switzerland.

PY - 2018/6/14

Y1 - 2018/6/14

N2 - 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.

AB - 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.

KW - Crowdsensing

KW - Friendly jamming

KW - Industrial internet of things

KW - Security

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

Abstract

Scopus Subject Areas

User-Defined Keywords

UN SDGs

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