This paper examines the application of the HBSI model to a range of dynamic signature verification capture digitizers. Behavioral biometrics (which considers the process by which a human performs a function) are inherently more complicated to analyze as they may contain a temporal modification as part of a valid capture interaction. In this study, a framework for the development of an HBSI model is outlined, based on two different signature digitizers. Both devices enabled the capture of both temporal data (dynamic) as well as an image of the completed (static) signature. Using this data, we propose a signature modality revision to the HBSI model with interaction errors classified into five categories. This study deals solely with genuine users, examining both correct and incorrect signature presentations.
(2016) An assessment of the usability of biometric signature systems using the human-biometric sensor interaction model'.International
AbstractSignature 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.
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