Title data
Liebers, Jonathan ; Gruenefeld, Uwe ; Buschek, Daniel ; Alt, Florian ; Schneegass, Stefan:
Introduction to Authentication Using Behavioral Biometrics.
In:
Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems. -
New York, NY, USA
: Association for Computing Machinery
,
2023
. - 547
ISBN 978-1-4503-9422-2
DOI: https://doi.org/10.1145/3544549.3574190
Project information
| Project title: |
Project's official title Project's id AI Tools - Continuous Interaction with Computational Intelligence Tools No information |
|---|
Abstract in another language
The trend of ubiquitous computing goes in parallel with ubiquitous authentication, as users must confirm their identity several times a day on their devices. Passwords are increasingly superseded by biometrics for their inherent drawbacks, and Behavioral Biometrics are particularly promising for increased usability and user experience. This course provides participants with an introduction to the overall topic, covering all phases of creating novel authentication schemes. We introduce important aspects of evaluating Behavioral Biometrics and provide an overview of technical machine-learning techniques in a hands-on session, inviting practitioners and researchers to extend their knowledge of Behavioral Biometrics.
Further data
| Item Type: | Article in a book |
|---|---|
| Refereed: | Yes |
| Keywords: | usable security; authentication; identification; human-computer interaction; machine learning |
| Institutions of the University: | Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Chair Applied Computer Science IX > Chair Applied Computer Science - Univ.-Prof. Dr. Daniel Buschek |
| Result of work at the UBT: | Yes |
| DDC Subjects: | 000 Computer Science, information, general works > 004 Computer science |
| Date Deposited: | 30 Oct 2023 08:07 |
| Last Modified: | 30 Oct 2023 08:07 |
| URI: | https://eref.uni-bayreuth.de/id/eprint/87422 |

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