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Fingerprint Recognition on Mobile Devices: Widely Deployed, Rarely Understood
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013). (Privacy and Security, PRISEC)ORCID iD: 0000-0003-2823-3837
Karlstad University, Faculty of Arts and Social Sciences (starting 2013), Karlstad Business School (from 2013). (HumanIT)ORCID iD: 0000-0001-6826-3358
Karlstad University, Faculty of Health, Science and Technology (starting 2013), Department of Mathematics and Computer Science (from 2013). (Privacy and Security, PRISEC)ORCID iD: 0000-0002-6938-4466
2018 (English)In: ARES 2018 Proceedings of the 13th International Conference on Availability, Reliability and Security (ARES 2018)., New York, NY, USA: Association for Computing Machinery (ACM), 2018, article id 39Conference paper, Published paper (Refereed)
Abstract [en]

Only a few studies have addressed the users' conception of how fingerprint recognition used for different purposes on mobile devices works. This study contributes by investigating how different groups of individuals think that the fingerprint recognition works, why they think so, and also by pointing out differences in pin code and fingerprint issues. The study furthermore yields some results concerning individuals' attitudes towards how sensitive the use of fingerprint sensors is: non-users tended to be more afraid of third-party access than users. On the other hand, users tended to regard the fingerprint pattern as more sensitive than non-users.

This study also manages to give some methodological contributions, namely that mockup user interfaces do not bias the parameters studied in this paper (e.g. understanding of access to fingerprint data), and that self-estimation of knowledge in Computer Security is not a good indicator of respondents' understanding of fingerprint security and privacy. Moreover, people who connected a low degree of sensitivity to fingerprint patterns gave very different reasons for their estimation of sensitivity. This prompts for more research, as it is unclear if different groups would benefit from different information and modes of visualisation to understand what are the issues involved in fingerprint recognition on mobile devices.

Place, publisher, year, edition, pages
New York, NY, USA: Association for Computing Machinery (ACM), 2018. article id 39
Keywords [en]
Fingerprint Pattern, User Perception, Sensitive Information, Data Privacy
National Category
Computer Sciences Human Computer Interaction
Identifiers
URN: urn:nbn:se:kau:diva-70227DOI: 10.1145/3230833.3234514ISI: 000477981800077ISBN: 978-1-4503-6448-5 (electronic)OAI: oai:DiVA.org:kau-70227DiVA, id: diva2:1264903
Conference
The 3rd SECPID Workshop in the 13th International Conference on Availability, Reliability and Security (ARES 2018), August 27-30, 2018, Hamburg, Germany.
Projects
CREDENTIAL
Funder
EU, Horizon 2020, 653454Available from: 2018-11-21 Created: 2018-11-21 Last updated: 2019-11-01Bibliographically approved

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Karegar, FarzanehPettersson, John SörenFischer-Hübner, Simone

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