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Assessing the Quality of Swipe Interactions for Mobile Biometric Systems

Assessing the Quality of Swipe Interactions for Mobile Biometric Systems
Assessing the Quality of Swipe Interactions for Mobile Biometric Systems
Quality estimation is a key study in biometrics, allowing optimisation and improvement of existing authentication systems by giving a prediction on the model performance based on the goodness of the sample or the user. In this paper, we propose a quality metric for swipe gestures on mobile devices. We evaluate a quality score for subjects on enrollment and for swipe samples, we estimate three quality groups and explore the correlation between our quality score and a state-of-art biometric authentication classifier performance. A further analysis based on the combined effects of subject quality and the amount of enrollment samples is conducted, investigating if increasing or decreasing enrollment size affects the authentication performance for different quality groups. Results are shown for three different public datasets, highlighting how higher quality users score a lower equal error rate compared to medium and low quality users, while high quality samples get a higher similarity score from the classifier.
Mobile biometrics, behavioural biometrics, swipe gestures, user quality, sample quality
IEEE
Santopietro, Marco
fcfe5a84-a740-4a15-898c-a170b48a8264
Vera-Rodriguez, Ruben
d9c7e17e-332c-47ac-a9a9-30cc75d26a3e
Guest, Richard
93533dbd-b101-491b-83cc-39ccfdc18165
Morales, Aythamy
158f3aeb-4e1d-49b2-854e-175946a4cb1f
Acien, Alejandro
6c1ed254-6c9e-4e15-98bb-8affdc8744d1
et al.
Santopietro, Marco
fcfe5a84-a740-4a15-898c-a170b48a8264
Vera-Rodriguez, Ruben
d9c7e17e-332c-47ac-a9a9-30cc75d26a3e
Guest, Richard
93533dbd-b101-491b-83cc-39ccfdc18165
Morales, Aythamy
158f3aeb-4e1d-49b2-854e-175946a4cb1f
Acien, Alejandro
6c1ed254-6c9e-4e15-98bb-8affdc8744d1

Santopietro, Marco, Vera-Rodriguez, Ruben and Guest, Richard , et al. (2021) Assessing the Quality of Swipe Interactions for Mobile Biometric Systems. In 2020 IEEE International Joint Conference on Biometrics (IJCB). IEEE. 8 pp . (doi:10.1109/IJCB48548.2020.9304858).

Record type: Conference or Workshop Item (Paper)

Abstract

Quality estimation is a key study in biometrics, allowing optimisation and improvement of existing authentication systems by giving a prediction on the model performance based on the goodness of the sample or the user. In this paper, we propose a quality metric for swipe gestures on mobile devices. We evaluate a quality score for subjects on enrollment and for swipe samples, we estimate three quality groups and explore the correlation between our quality score and a state-of-art biometric authentication classifier performance. A further analysis based on the combined effects of subject quality and the amount of enrollment samples is conducted, investigating if increasing or decreasing enrollment size affects the authentication performance for different quality groups. Results are shown for three different public datasets, highlighting how higher quality users score a lower equal error rate compared to medium and low quality users, while high quality samples get a higher similarity score from the classifier.

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More information

e-pub ahead of print date: 6 January 2021
Venue - Dates: 2020 International Joint Conference on Biometrics, Virtual, 2020-09-28 - 2020-10-01
Keywords: Mobile biometrics, behavioural biometrics, swipe gestures, user quality, sample quality

Identifiers

Local EPrints ID: 489779
URI: http://eprints.soton.ac.uk/id/eprint/489779
PURE UUID: 31b95786-9b35-40c9-96b8-ea60639108dc
ORCID for Richard Guest: ORCID iD orcid.org/0000-0001-7535-7336

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Date deposited: 02 May 2024 16:35
Last modified: 03 May 2024 02:07

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Contributors

Author: Marco Santopietro
Author: Ruben Vera-Rodriguez
Author: Richard Guest ORCID iD
Author: Aythamy Morales
Author: Alejandro Acien
Corporate Author: et al.

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