- Title
- Artificial noise aided scheme to secure UAV-assisted internet of things with wireless power transfer
- Creator
- Wang, Qubeijian; Dai, Hong-Ning; Li, Xuran; Shukla, Mahendra; Imran, Muhammad
- Date
- 2020
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/185366
- Identifier
- vital:16684
- Identifier
-
https://doi.org/10.1016/j.comcom.2020.09.017
- Identifier
- ISBN:0140-3664 (ISSN)
- Abstract
- The proliferation of massive Internet of Things (IoT) devices poses research challenges especially in unmanned aerial vehicles(UAV)-assisted IoT. In particular, the limited battery capacity not only restricts the life time of UAV-assisted IoT but also brings security vulnerabilities since computation-complex cryptographic algorithms cannot be adopted in UAV-assisted IoT systems. In this paper, artificial noise and wireless power transfer technologies are integrated to secure communications in UAV-assisted IoT (particularly in secret key distribution). We present the artificial noise aided scheme to secure UAV-assisted IoT communications by letting UAV gateway transfer energy to a number of helpers who will generate artificial noise to interfere with the eavesdroppers while the legitimate nodes can decode the information by canceling additive artificial noise. We introduce the eavesdropping probability and the security rate to validate the effectiveness of our proposed scheme. We further formulate an eavesdropping probability constrained security rate maximization problem to investigate the optimal power allocation. Moreover, analytical and numerical results are provided to obtain some useful insights, and to demonstrate the effect of crucial parameters (e.g., the transmit power, the main channel gain) on the eavesdropping probability, the security rate, and the optimal power allocation. © 2020 Elsevier B.V.
- Publisher
- Elsevier B.V.
- Relation
- Computer Communications Vol. 164, no. (2020), p. 1-12
- Rights
- All metadata describing materials held in, or linked to, the repository is freely available under a CC0 licence
- Rights
- Copyright © 2020 Elsevier B.V.
- Subject
- 4006 Communications engineering; 4009 Electronics, sensors and digital hardware; 4606 Distributed computing and systems software; Artificial noise; Internet of Things; Security; Unmanned aerial vehicles; Wireless energy transfer
- Reviewed
- Funder
- This work was supported in part by Macao Science and Technology Development Fund under Grant No. 0026/2018/A1 . M. Imran’s work is supported by the Deanship of Scientific Research at King Saud University through the research group project number RG-1435-051
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