Title: An assessment of the usability of biometric signature systems using the human-biometric sensor interaction model

Authors: Richard Guest; Michael Brockly; Stephen Elliott; James Scott

Addresses: School of Engineering and Digital Arts, University of Kent, Jennison Building, CT2 7NT, Canterbury, UK ' Biometrics Standards, Performance and Assurance Laboratory, Purdue University, 155 South Grant Street, 47907 West Lafayette, IN, USA ' Biometrics Standards, Performance and Assurance Laboratory, Purdue University, 155 South Grant Street, 47907 West Lafayette, IN, USA ' School of Engineering and Digital Arts, University of Kent, Jennison Building, CT2 7NT, Canterbury, UK

Abstract: Signature biometrics is a widely used form of user authentication. As a behavioural biometric, samples have inherent inconsistencies which must be accounted for within an automated system. Performance deterioration of a tuned biometric software system may be caused by an interaction error with a biometric capture device; however, using conventional error metrics, system and user interaction errors are combined, thereby masking the contribution by each element. In this paper we explore the application of the Human-Biometric Sensor Interaction (HBSI) model to signature as an exemplar of a behavioural biometric. Using observational data collected from a range of subjects, our study shows that usability issues can be identified specific to individual capture device technologies. While most interactions are successful, a range of common interaction errors need to be mitigated by design to reduce overall error rates.

Keywords: behavioural biometrics; signature verification; interaction assessment; HBSI; usability; biometric signature systems; human-biometric sensor interaction; modelling; user authentication; biometric capture devices; interaction errors.

DOI: 10.1504/IJCAT.2016.076810

International Journal of Computer Applications in Technology, 2016 Vol.53 No.4, pp.336 - 347

Received: 08 May 2021
Accepted: 12 May 2021

Published online: 24 May 2016 *

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