Li, X., Dai, H.-N., Wang, Q., Imran, M., Li, D. and Imran, M. A. (2020) Securing internet of medical things with friendly-jamming schemes. Computer Communications, 160, pp. 431-442. (doi: 10.1016/j.comcom.2020.06.026)
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Abstract
The Internet of Medical Things (IoMT)-enabled e-healthcare can complement traditional medical treatments in a flexible and convenient manner. However, security and privacy become the main concerns of IoMT due to the limited computational capability, memory space and energy constraint of medical sensors, leading to the in-feasibility for conventional cryptographic approaches, which are often computationally-complicated. In contrast to cryptographic approaches, friendly jamming (Fri-jam) schemes will not cause extra computing cost to medical sensors, thereby becoming potential countermeasures to ensure security of IoMT. In this paper, we present a study on using Fri-jam schemes in IoMT. We first analyze the data security in IoMT and discuss the challenges. We then propose using Fri-jam schemes to protect the confidential medical data of patients collected by medical sensors from being eavesdropped. We also discuss the integration of Fri-jam schemes with various communication technologies, including beamforming, Simultaneous Wireless Information and Power Transfer (SWIPT) and full duplexity. Moreover, we present two case studies of Fri-jam schemes in IoMT. The results of these two case studies indicate that the Fri-jam method will significantly decrease the eavesdropping risk while leading to no significant influence on legitimate transmission.
Item Type: | Articles |
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Keywords: | Internet of medical things, network security, friendly jamming. |
Status: | Published |
Refereed: | Yes |
Glasgow Author(s) Enlighten ID: | Imran, Professor Muhammad |
Authors: | Li, X., Dai, H.-N., Wang, Q., Imran, M., Li, D., and Imran, M. A. |
College/School: | College of Science and Engineering > School of Engineering > Systems Power and Energy |
Journal Name: | Computer Communications |
Publisher: | Elsevier |
ISSN: | 0140-3664 |
ISSN (Online): | 1873-703X |
Published Online: | 26 June 2020 |
Copyright Holders: | Copyright © 2020 Elsevier B.V. |
First Published: | First published in Computer Communications 160: 431-442 |
Publisher Policy: | Reproduced in accordance with the publisher copyright policy |
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