Qubeijian Wang, Hong-Ning Dai, Hao Wang, Guangquan Xu, Arun Kumar Sangaiah
Journal of Communications and Networks, vol. 21, no. 5, pp. 481 - 490
Publication year: 2019


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.


    • Internet of Things
    • Unmanned aerial vehicles
    • Security
    • Eavesdropping
    • Jamming


  title={UAV-enabled Friendly Jamming Scheme to Secure Industrial Internet of Things},
  author={Qubeijian Wang and Hong-Ning Dai and Hao Wang and Guangquan Xu and Arun Kumar Sangaiah},
  journal={Journal of Communications and Networks},
  pages={481 - 490},

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