Eavesdropping is a critical threat to the security of industrial Internet of things (IIoT) since many malicious attacks often follow eavesdropping activities. In this paper, we present an anti-eavesdropping scheme based on multiple unmanned aerial vehicles (UAVs) who emit jamming signals to disturb eavesdropping activities. We name such friendly UAV-enabled jamming scheme as Fri-UJ scheme. In particular, UAV-enabled jammers (UJs) emit artificial noise to mitigate the signal to interference plus noise ratio (SINR) at eavesdroppers consequently reducing the eavesdropping probability. In order to evaluate the performance of the proposed Fri-UJ scheme, we establish a theoretical framework to analyze both the local eavesdropping probability and the overall eavesdropping probability. Our analytical results show that the Fri-UJ scheme can significantly reduce the eavesdropping risk while having nearly no impact on legitimate communications. Meanwhile, the simulation results also agree with the analytical results, verifying the accuracy of the proposed model. The merits of Fri-UJ scheme include the deployment flexibility and no impact on legitimate communications.
Bibliographical noteFunding Information:
Manuscript received February, 17, 2019. This paper was supported by Macao Science and Technology Development Fund under Grant No. 0026/2018/A1, the State Key Development Program of China under Grant No. 2017YFE0111900, National Science Foundation of China under Grant No. 61572355, 61672170, U1736115. The authors would like to thank G. K.-T. Hon for his suggestions. Q. Wang and H.-N. Dai are with the Faculty of Information Technology, Macau University of Science and Technology, Macau SAR, email: firstname.lastname@example.org and email@example.com. H. Wang is Department of Computer Science, Norwegian University of Science and Technology, Gjøvik, Norway, email: firstname.lastname@example.org. G. Xu is College of Intelligence and Computing, Tianjin University, Tianjin, China, email: email@example.com. A. K. Sangaiah is School of Computing Science and Engineering, VIT University, Vellore, India, email: firstname.lastname@example.org. H.-N. Dai and H. Wang are the corresponding authors. Digital Object Identifier: 10.1109/JCN.2019.000042
© 2011 KICS.
- Internet of things
- unmanned aerial vehicles