H2K: A Heartbeat-Based Key Generation Framework for ECG and PPG Signals

Zhang, Junqing ORCID: 0000-0002-3502-2926, Zheng, Yushi, Xu, Weitao and Chen, Yingying (2023) H2K: A Heartbeat-Based Key Generation Framework for ECG and PPG Signals. IEEE TRANSACTIONS ON MOBILE COMPUTING, 22 (2). pp. 923-934.

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Official URL: http://dx.doi.org/10.1109/tmc.2021.3096384

Abstract

Wireless body area network is a key enabler for connected healthcare but recent cyberattacks have compromised its security and trustworthiness. This paper investigates heartbeat-based key generation to secure body area networks. The interpulse intervals (IPIs) between any two adjacent peaks of heartbeat signals are random and state-of-The-Art literature has demonstrated that IPI is a good random source to be extracted as cryptographic keys. Heartbeat signals can be measured by electrocardiography (ECG) and photoplethysmography (PPG) sensors. A general heartbeat-based key generation framework applicable to both ECG and PPG signals is proposed. A robust peak detection algorithm is designed to capture noisy peaks and a simple yet efficient IPI alignment algorithm to align the common IPIs. A key establishment protocol is used to convert analog IPIs to digital binaries and reconcile them between legitimate devices. We evaluate the performance for both ECG signals from an online public database, MIT PhysioBank, and PPG signals collected from our testbed. The results demonstrate that our algorithm is robust and heartbeat-based key generation can be completed for both ECG and PPG signals. We finally create a PPG-based prototype and a demonstration video to show the practicality of our framework.

Item Type:	Article
Uncontrolled Keywords:	Electrocardiography, Heart beat, Wireless communication, Protocols, Databases, Implants, Encryption, Body area networks, key generation, biometrics, electrocardiography (ECG), photoplethysmography (PPG), interpulse interval
Divisions:	Faculty of Science and Engineering > School of Electrical Engineering, Electronics and Computer Science
Depositing User:	Symplectic Admin
Date Deposited:	09 Jul 2021 07:18
Last Modified:	15 Mar 2024 14:44
DOI:	10.1109/TMC.2021.3096384
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3129301