Wells, Alec (2021) Trust and Voice Biometric Authentication: Understanding the Levels of User’s Trust on Authentication Methods. Masters thesis, York St John University.

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Abstract

Due to the singularity of the distinct biometric traits, biometric authentication factors have become increasingly prevalent in daily life and are predicted to target future authentication methods. Previous studies established that the human voice is one of the most natural, non-intrusive, and convenient behavioral biometric factors compared to other biometric authentication methods. Despite the non-intrusive characteristics of voice biometric authentication, it has been brought under scrutiny for many reasons, including the accuracy of biometric data, a general societal trust and distrust with technology and the risk of theft and imitation. Although, when it comes to trusting technology, users’ perceptions change with time through continued use of technology, and thus allowing perceptions and opinions to change. However, there are fundamental factors that can contribute to how users develop trust with technologies over time. This study derived a realistic trust evaluation model that incorporates security, privacy, safety, usability, reliability, and availability factors into a trust vector for a flexible measurement of trust in the user accessing the technology. Based on the derived trust model, we experiment using quantitative method whether the users are willing to trust voice biometric authentication method over PIN, fingerprint, and token-based authentication and hence would be inclined to adopt and utilize it as a means of user authentication to access technology. We applied the Kruskal-Wallis H test and the post-hoc test to understand which authentication method the user trusts, based on statistical significance and which groups were found to have that statistical difference.

The result of the study suggests that users have less trust with voice compared to other authentication methods especially traditional means of knowledge-based authentication such as PIN’s which consistently ranked much higher than voice in pairwise comparisons.

Item Type:	Thesis (Masters)
Status:	Published
Subjects:	T Technology > T Technology (General)
School/Department:	School of Science, Technology and Health
URI:	https://ray.yorksj.ac.uk/id/eprint/5466

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