Securing health monitoring via body-centric time-frequency signature authorization

Zhao, N., Zhang, Z., Yang, X., Ren, A. , Zhao, J. and Ur Rehman, M. (2021) Securing health monitoring via body-centric time-frequency signature authorization. IEEE Internet of Things Journal, 8(6), pp. 4711-4722. (doi: 10.1109/JIOT.2020.3029075)

Abstract

Identity-based attacks serve as the basis of an intruder’s attempt to launch security infringements in mobile health monitoring scenarios. Wireless channel perturbations due to the presence of human body are a relative phenomenon depending heavily on the subject’s dielectric properties. A new Body-Centric Signature Authorization (B-CSAI) approach based on time-frequency domain characteristics was proposed. This method utilizes multiple millimeter wave bands of 27-28 GHz, 29-30 GHz, and 31-32 GHz, thereby enhancing the security in body-centric communications exploiting benefits of subject specific channel signature. The proposed bornprint method is based on the intrinsic identity related time-frequency domain information, which generated by the user’s natural hand motion signature and resulting creeping waves and space waves. It can meet the unconditional keyless authorization requirements. A detailed measurement campaign considering radiation efficiency (η = -25.8, -24.7, -26.4), pathloss exponent, and shadowing factor in three millimeter wave bands, using six human subjects confirm the usability and efficiency of the proposed approach. This also shows that there is a wide space for realizing security from physical mechanisms.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Ur Rehman, Dr Masood and Ren, Dr Aifeng
• Authors: Zhao, N., Zhang, Z., Yang, X., Ren, A., Zhao, J., and Ur Rehman, M.
• College/School: College of Science and Engineering > School of Engineering; College of Science and Engineering > School of Engineering > Systems Power and Energy
• Journal Name: IEEE Internet of Things Journal
• Publisher: IEEE
• ISSN: 2372-2541
• ISSN (Online): 2327-4662
• Published Online: 06 October 2020
• Copyright Holders: Copyright © 2020 IEEE
• First Published: First published in IEEE Internet of Things Journal 8(6): 4711-4722
• Publisher Policy: Reproduced in accordance with the publisher copyright policy