Securing Internet of Medical Things with Friendly-jamming schemes

Xuran LI, Hong Ning DAI*, Qubeijian WANG, Muhammad IMRAN, Dengwang LI, Muhammad Ali IMRAN

*Corresponding author for this work

Research output: Journal PublicationsReview articlepeer-review

13 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)431-442
Number of pages12
JournalComputer Communications
Early online date26 Jun 2020
Publication statusPublished - 1 Jul 2020
Externally publishedYes

Bibliographical note

Funding Information:
This work was supported in part by Macao Science and Technology Development Fund under Grant No. 0026/2018/A1 , the National Natural Science Foundation of China ( 61971271 ), the Taishan Scholars Project of Shandong Province ( Tsqn20161023 ) and the Primary Research and Development Plan of Shandong Province (No. 2018GGX101018 , No. 2019QYTPY020 ). 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 .

Publisher Copyright:
© 2020


  • Friendly jamming
  • Internet of medical things
  • Network security


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