Protecting the ECG Signal in Cloud-based User Identification System

Diana Batista, Diana Batista, Helena Aidos, Ana Fred, Ana Fred, Joana Santos, Rui Cruz Ferreira, Rui César das Neves

2018

Abstract

Biometric recognition has become a popular approach for user identification and authentication. However, since in ECG-based biometrics users cannot change their authentication/identification signal (unlike in password-based methods), its applicability is seriously constrained for cloud-based systems: a hacker could potentially retrieve the stored ECG signal, eternally disabling ECG-based biometrics for the attacked user. To overcome such an issue, new methodologies must be devised to enable cloud-based authentication/ identification systems without requiring the transmission and storage of the user’s ECG signal on remote servers. In this paper we propose an ECG biometric approach that relies on non-linear irreversible dissimilarity spaces to encode (encrypt) the user’s ECG. We show how to construct the dissimilarity space, and also evaluate the system’s accuracy with the dimensionality of the dissimilarity space. We show that the proposed biometric system retains similar identification errors as an equivalent system relying on the Euclidean space, while the latter can potentially be broken by using triangulation techniques to uncover the users original ECG signal.

Paper Citation

in Harvard Style

Batista D., Aidos H., Fred A., Santos J., Ferreira R. and das Neves R. (2018). Protecting the ECG Signal in Cloud-based User Identification System. In Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2018) - Volume 4: BIOSIGNALS; ISBN 978-989-758-279-0, SciTePress, pages 78-86. DOI: 10.5220/0006723900780086

in Bibtex Style

@conference{biosignals18,
author={Diana Batista and Helena Aidos and Ana Fred and Joana Santos and Rui Cruz Ferreira and Rui César das Neves},
title={Protecting the ECG Signal in Cloud-based User Identification System},
booktitle={Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2018) - Volume 4: BIOSIGNALS},
year={2018},
pages={78-86},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006723900780086},
isbn={978-989-758-279-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2018) - Volume 4: BIOSIGNALS
TI - Protecting the ECG Signal in Cloud-based User Identification System
SN - 978-989-758-279-0
AU - Batista D.
AU - Aidos H.
AU - Fred A.
AU - Santos J.
AU - Ferreira R.
AU - das Neves R.
PY - 2018
SP - 78
EP - 86
DO - 10.5220/0006723900780086
PB - SciTePress