Wearable security : Key derivation for Body Area sensor Networks based on host movement

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

13 Scopus Citations
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Author(s)

  • Dhruv Oberoi
  • Wing Yan Sou
  • Yin Yi Lui
  • Roy Fisher

Detail(s)

Original languageEnglish
Title of host publicationIEEE International Symposium on Industrial Electronics
PublisherIEEE
Pages1116-1121
ISBN (Electronic)2163-5145
ISBN (Print)9781509008735
Publication statusPublished - Nov 2016

Publication series

NameProceedings of the IEEE International Symposium on Industrial Electronics
PublisherIEEE
ISSN (Print)2163-5137

Conference

Title25th IEEE International Symposium on Industrial Electronics, ISIE 2016
PlaceUnited States
CitySanta Clara
Period8 - 10 June 2016

Abstract

The Internet-of-Things relies on ad-hoc connections, which also requires an on-demand approach to the negotiation of security parameters. We propose a new approach to shared key derivation for Body Area Networks (BANs). Body area networks are quickly becoming increasingly important in the world of healthcare with wide application in the treatment and monitoring of chronic patients using on-body devices. Advancements in the field will result in quicker response times in emergency situations, and detect complications in patients at a much earlier stage potentially saving many lives. In this paper, we have used motion sensors instead of the more common physiological signals that need physical access to the body, like electrocardiograms (ECG), to pair devices and secure communication in Body Area Networks. Our method considers the acceleration of the devices that needs to communicate. These measurements tend to be similar as devices are deployed on the same host body, which means that these could be used to derive shared keys. We show that these measurements results in derived keys that are unpredictable and exhibit significant difference with previous keys. This is an improvement over existing schemes where keys vary for different hosts but tend to be similar over time.

Research Area(s)

  • Authentication, Key Derivation, Physiology, Internet-of-Things, User-Centric, Security

Bibliographic Note

Full text of this publication does not contain sufficient affiliation information. Related Research Unit(s) information for this record is supplemented by the author(s) concerned.

Citation Format(s)

Wearable security: Key derivation for Body Area sensor Networks based on host movement. / Oberoi, Dhruv; Sou, Wing Yan; Lui, Yin Yi et al.
IEEE International Symposium on Industrial Electronics. IEEE, 2016. p. 1116-1121 7745050 (Proceedings of the IEEE International Symposium on Industrial Electronics).

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review