Towards using physiological signals as cryptographic keys in body area networks

Karaoğlan Altop, Duygu and Levi, Albert and Tuzcu, Volkan (2015) Towards using physiological signals as cryptographic keys in body area networks. In: 9th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth 2015), İstanbul, Turkey

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Abstract

Body Area Networks (BANs) are the most important building stone of pervasive healthcare, which enables remote, continuous and real-time health monitoring. Biosensors, constituting the BANs, collect highly sensitive medical information from their hosts and communicate these data. Considering the nature of the wireless medium, the privacy requirements of the individuals and the extreme energy and storage limitations of the biosensors, BANs require a light-weight and secure key management infrastructure. It has been suggested that the security of a BAN can be guaranteed using the body itself as the communication channel by means of bio-cryptography. Explicitly, physiological parameters generated from different body parts are used to protect the data exchanged among the biosensors. In this paper, we (i) define a novel physiological parameter generation technique, and (ii) identify and evaluate an appropriate physiological parameter that can be used in a bio-cryptographic key management protocol, namely the inter-pulse interval (IPI). For experimental data analysis, we use the blood pressure (BP) signal, for the first time in the literature, together with the electrocardiogram (ECG) and photoplethysmogram (PPG) signals. Our results show that the IPI values derived from the ECG, PPG and BP signals are good candidates of physiological parameters that can be used as cryptographic keys in order to ensure secure key management in BANs.
Item Type: Papers in Conference Proceedings
Uncontrolled Keywords: Cryptographic Key Generation; Body Area Networks; Physiological Signals; Key Management; Network Security; Bio-cryptography
Divisions: Faculty of Engineering and Natural Sciences > Academic programs > Computer Science & Eng.
Faculty of Engineering and Natural Sciences
Depositing User: Albert Levi
Date Deposited: 23 Dec 2015 12:13
Last Modified: 26 Apr 2022 09:20
URI: https://research.sabanciuniv.edu/id/eprint/28433

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