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

Research output: Journal PublicationsJournal Article (refereed)peer-review

12 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 languageEnglish
Article number1938
JournalSensors (Switzerland)
Volume18
Issue number6
DOIs
Publication statusPublished - 14 Jun 2018
Externally publishedYes

Bibliographical note

Funding Information:
Funding: 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.

Funding Information:
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.

Keywords

  • Crowdsensing
  • Friendly jamming
  • Industrial internet of things
  • Security

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