Automatic usability and stress analysis in mobile biometrics

Blanco-Gonzalo, Ramón; Sánchez-Reillo, Raúl; Miguel-Hurtado, Oscar; Bella-Pulgarin, Eric

doi:10.1016/j.imavis.2014.09.003

Cited by 16 publications

(8 citation statements)

References 14 publications

(13 reference statements)

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“…Furthermore, the HBSI framework defines metrics related to usability (satisfaction, eefficiency and effectiveness), cognitive (learnability and memorability), ergonomics (physical conditions) and signal processing (sample quality and processing capabilities) [4] to obtain a holistic view of the user's interaction with the biometric system. For further details about the HBSI please refer to [2][3][4][5][6][7]. This framework has been tested for a number of different modalities: hand geometry [5], fingerprint [4] and face [6].…”

Section: Biometric Interaction Analysismentioning

confidence: 99%

“…This framework has been tested for a number of different modalities: hand geometry [5], fingerprint [4] and face [6]. The HBSI has also been applied to mobile implementations for dynamic signature [7]. A novel and extended implementation was proposed in our previous work [2,8] which incorporates mobile analytic tools and server logs to ensure sufficient data is captured.…”

Section: Biometric Interaction Analysismentioning

confidence: 99%

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Voice and face interaction evaluation of a mobile authentication platform

Miguel-Hurtado

Guest

Lunerti

2017

2017 International Carnahan Conference on Security Technology (ICCST)

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Abstract-Biometric authentication in mobile devices has become a key aspect of application security. However, the use of dedicated sensors such as fingerprint/iris sensors may not always be feasible. As an alternative, the use of face and voice biometrics using the generic sensors integrated in smartphones is gaining momentum. This work applied the HBSI framework to analyise the user's interaction with the mobile PIDaaS platform that integrates voice and face authentication. Our analysis enables a thorough comparison between the user's interaction for these two modalities with the same population.

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Section: Biometric Interaction Analysismentioning

confidence: 99%

Section: Biometric Interaction Analysismentioning

confidence: 99%

Voice and face interaction evaluation of a mobile authentication platform

Miguel-Hurtado

Guest

Lunerti

2017

2017 International Carnahan Conference on Security Technology (ICCST)

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“…The HBSI has also been applied to mobile device implementations for dynamic signature [8]. The work presented in this article applies the HBSI framework to a voice recognition system within mobile environments.…”

Section: Biometric Interaction Analysismentioning

confidence: 99%

Interaction evaluation of a mobile voice authentication system

Miguel-Hurtado

Blanco-Gonzalo

Guest

et al. 2016

2016 IEEE International Carnahan Conference on Security Technology (ICCST)

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Abstract-Biometric recognition is nowadays widely used in smartphones, making the users' authentication easier and more transparent than PIN codes or patterns. Starting from this idea, the EU project PIDaaS aims to create a secure authentication system through mobile devices based on voice and face recognition as two of the most reliable and user-accepted modalities. This work introduces the project and the first PIDaaS usability evaluation carried out by means of the well-known HBSI model. In this experiment, participants interact with a mobile device using the PIDaaS system under laboratory conditions: video recorded and assisted by an operator. Our findings suggest variability among sessions in terms of usability and feed the next PIDaaS HCI design.

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“…In [5] the use of different styluses in dynamic signature verification on an iPad was studied reaching interesting outcomes regarding ergonomics. The stress as a key usability factor in biometric recognition was analysed in [6], where authors showed that mobile biometrics are reliable even when the user is under stressful situations (banks, shops, post office, etc.). The most relevant works providing feedback to users in biometrics are the experiments made by NIST.…”

Section: State Of the Art In Biometrics Usabilitymentioning

confidence: 99%

Time evolution of face recognition in accessible scenarios

Blanco-Gonzalo

Poh

Wong

et al. 2015

Hum. Cent. Comput. Inf. Sci.

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Up to now, biometric recognition has shown significant advantages as to be considered a reliable solution for security systems in mobile environments. Nevertheless, due to the short lifetime of biometrics in mobile devices, a handful of concerns regarding usability and accessibility need to be covered in order to meet users’ requirements. This work is focused on analysing the usability and accessibility of a face recognition system used by visually impaired people, focusing on the time spent in the process, which is a critical aspect. Specifically, we cover different key questions including which kind of feedback is more useful for visually impaired users and beneficial for performance and how is the performance evolution in contrast with the time spent in the recognition. Our findings suggest that several parameters improve along with the time spent in the process, including performance. The audio feedback provided in real time involves also better performance and user experience than instructions given previously.

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Automatic usability and stress analysis in mobile biometrics

Cited by 16 publications

References 14 publications

Voice and face interaction evaluation of a mobile authentication platform

Voice and face interaction evaluation of a mobile authentication platform

Interaction evaluation of a mobile voice authentication system

Time evolution of face recognition in accessible scenarios

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