Next Article in Journal
An Improved Randomized Local Binary Features for Keypoints Recognition
Next Article in Special Issue
A Secure Transmission Scheme Based on Artificial Fading for Wireless CrowdSensing Networks
Previous Article in Journal
High-Speed Terahertz Waveform Measurement for Intense Terahertz Light Using 100-kHz Yb-Doped Fiber Laser
Previous Article in Special Issue
Data-Prefetching Scheme Based on Playback Delay and Positioning Satisfaction in Peer-To-Peer Video-On-Demand System
Open AccessArticle

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

by Xuran Li 1, Qiu Wang 1, Hong-Ning Dai 1,* and Hao Wang 2,*
1
Faculty of Information Technology, Macau University of Science and Technology, Macau SAR, China
2
Department of ICT and Natural Sciences, Faculty of Information Technology and Electrical Engineering, Norwegian University of Science and Technology, Postboks 1517, NO-6025 Aalesund, Norway
*
Authors to whom correspondence should be addressed.
Sensors 2018, 18(6), 1938; https://doi.org/10.3390/s18061938
Received: 10 May 2018 / Revised: 8 June 2018 / Accepted: 11 June 2018 / Published: 14 June 2018
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. View Full-Text
Keywords: friendly jamming; crowdsensing; industrial internet of things; security friendly jamming; crowdsensing; industrial internet of things; security
Show Figures

Figure 1

MDPI and ACS Style

Li, X.; Wang, Q.; Dai, H.-N.; Wang, H. A Novel Friendly Jamming Scheme in Industrial Crowdsensing Networks against Eavesdropping Attack. Sensors 2018, 18, 1938.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop