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Fingerprint Recognition on Mobile Devices: Widely Deployed, Rarely Understood

Authors:

Farzaneh Karegar,

John Sören Pettersson,

Simone Fischer-HübnerAuthors Info & Claims

ARES '18: Proceedings of the 13th International Conference on Availability, Reliability and Security

Article No.: 39, Pages 1 - 9

https://doi.org/10.1145/3230833.3234514

Published: 27 August 2018 Publication History

Abstract

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.

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Cited By

Shuwandy MJouda AAhmed MSalih MAl-qaysi ZAlamoodi AGarfan SAlbahri OZaidan BAlbahri A(2024)Sensor-based authentication in smartphone: A systematic reviewJournal of Engineering Research10.1016/j.jer.2024.02.003Online publication date: Feb-2024
https://doi.org/10.1016/j.jer.2024.02.003
Kruzikova AMatyas V(2023)Fingerprint forgery training: Easy to learn, hard to performProceedings of the 18th International Conference on Availability, Reliability and Security10.1145/3600160.3604990(1-7)Online publication date: 29-Aug-2023
https://dl.acm.org/doi/10.1145/3600160.3604990
Contreras RNonato LBoaventura MBoaventura ISantos FZanin RViana M(2022)A New Multi-Filter Framework for Texture Image Representation Improvement Using Set of Pattern Descriptors to Fingerprint Liveness DetectionIEEE Access10.1109/ACCESS.2022.321833510(117681-117706)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2022.3218335
Show More Cited By

Index Terms

Fingerprint Recognition on Mobile Devices: Widely Deployed, Rarely Understood
1. Security and privacy
  1. Human and societal aspects of security and privacy

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cover image ACM Other conferences

ARES '18: Proceedings of the 13th International Conference on Availability, Reliability and Security

August 2018

603 pages

ISBN:9781450364485

DOI:10.1145/3230833

Copyright © 2018 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Universität Hamburg: Universität Hamburg

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 27 August 2018

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Research-article
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Refereed limited

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European Union's Horizon 2020 research and innovation programme

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ARES 2018

ARES 2018: International Conference on Availability, Reliability and Security

August 27 - 30, 2018

Hamburg, Germany

Acceptance Rates

ARES '18 Paper Acceptance Rate 128 of 260 submissions, 49%;

Overall Acceptance Rate 228 of 451 submissions, 51%

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Cited By

Shuwandy MJouda AAhmed MSalih MAl-qaysi ZAlamoodi AGarfan SAlbahri OZaidan BAlbahri A(2024)Sensor-based authentication in smartphone: A systematic reviewJournal of Engineering Research10.1016/j.jer.2024.02.003Online publication date: Feb-2024
https://doi.org/10.1016/j.jer.2024.02.003
Kruzikova AMatyas V(2023)Fingerprint forgery training: Easy to learn, hard to performProceedings of the 18th International Conference on Availability, Reliability and Security10.1145/3600160.3604990(1-7)Online publication date: 29-Aug-2023
https://dl.acm.org/doi/10.1145/3600160.3604990
Contreras RNonato LBoaventura MBoaventura ISantos FZanin RViana M(2022)A New Multi-Filter Framework for Texture Image Representation Improvement Using Set of Pattern Descriptors to Fingerprint Liveness DetectionIEEE Access10.1109/ACCESS.2022.321833510(117681-117706)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2022.3218335
Kauba CSöllinger DKirchgasser SWeissenfeld AFernández Domínguez GStrobl BUhl A(2021)Towards Using Police Officers’ Business Smartphones for Contactless Fingerprint Acquisition and Enabling Fingerprint Comparison against Contact-Based DatasetsSensors10.3390/s2107224821:7(2248)Online publication date: 24-Mar-2021
https://doi.org/10.3390/s21072248
Preuveneers DJoos SJoosen W(2021)AuthGuide: Analyzing Security, Privacy and Usability Trade-Offs in Multi-factor AuthenticationTrust, Privacy and Security in Digital Business10.1007/978-3-030-86586-3_11(155-170)Online publication date: 27-Sep-2021
https://dl.acm.org/doi/10.1007/978-3-030-86586-3_11
Kitkowska AShulman YMartucci LWastlund E(2020)Psychological Effects and Their Role in Online Privacy Interactions: A ReviewIEEE Access10.1109/ACCESS.2020.29695628(21236-21260)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.2969562
Lindegren DKaregar FKane BPettersson J(2019)An evaluation of three designs to engage users when providing their consent on smartphonesBehaviour & Information Technology10.1080/0144929X.2019.169789840:4(398-414)Online publication date: 17-Dec-2019
https://doi.org/10.1080/0144929X.2019.1697898

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