KVC-onGoing: Keystroke Verification Challenge
This article presents the Keystroke Verification Challenge - onGoing (KVC-onGoing) 1 1 https://sites.google.com/view/bida-kvc/ . , on which researchers can easily benchmark their systems in a common platform using large-scale public databases, the Aalto University Keystroke databases, and a standard experimental protocol. The keystroke data consist of tweet-long sequences of variable transcript text from over 185,000 subjects, acquired through desktop and mobile keyboards simulating real-life conditions. The results on the evaluation set of KVC-onGoing have proved the high discriminative power of keystroke dynamics, reaching values as low as 3.33% of Equal Error Rate (EER) and 11.96% of False Non-Match Rate (FNMR) @1% False Match Rate (FMR) in the desktop scenario, and 3.61% of EER and 17.44% of FNMR @1% at FMR in the mobile scenario, significantly improving previous state-of-the-art results. Concerning demographic fairness, the analyzed scores reflect the subjects’ age and gender to various extents, not negligible in a few cases. The framework runs on CodaLab 2 2 https://codalab.lisn.upsaclay.fr/competitions/14063 . . • We set up a novel framework for developing and evaluating keystroke biometrics. • We designed a unified experimental protocol with desktop and mobile scenarios. • We employ the biggest databases of keystroke dynamics, with over 185,000 subjects. • We provide a competitive performance baseline based on a limited-time challenge. • We provide a first exploration of the biometric fairness of keystroke dynamics.
Authors
- Nahuel González
- Rubén Tolosana (ORCID: https://orcid.org/0000-0002-9393-3066)
- Giuseppe Stragapede (ORCID: https://orcid.org/0000-0002-5949-8574)
- Yosuke Yamagishi (ORCID: https://orcid.org/0009-0006-7688-3075)
- Adam Baran (ORCID: https://orcid.org/0009-0002-0883-4352)
- Przemysław Jaskóła (ORCID: https://orcid.org/0000-0002-0562-1602)
- Sanka Rasnayaka (ORCID: https://orcid.org/0000-0002-5186-1957)
- Mateusz Krzysztoń (ORCID: https://orcid.org/0000-0002-6020-406X)
- Rubén Vera-Rodríguez (ORCID: https://orcid.org/0000-0002-6338-8511)
- Naser Damer (ORCID: https://orcid.org/0000-0001-7910-7895)
- Weronika Gutfeter (ORCID: https://orcid.org/0000-0001-6359-8220)
- Terence Sim (ORCID: https://orcid.org/0000-0002-0198-094X)
- Sandareka Wickramanayake (ORCID: https://orcid.org/0000-0003-0314-5988)
- Julián Fiérrez (ORCID: https://orcid.org/0000-0002-6343-5656)
- Alejandro Acien (ORCID: https://orcid.org/0000-0002-2689-1257)
- Andrei Shadrikov (ORCID: https://orcid.org/0000-0003-0229-9184)
- Aythami Morales (ORCID: https://orcid.org/0000-0002-7268-4785)
- Florian Heinz (ORCID: https://orcid.org/0000-0002-5380-5692)
- Ivan DeAndres-Tame (ORCID: https://orcid.org/0009-0008-5402-1153)
- Dmitrii Gordin
- Daniel Wimmer
- Simon Haberl
- Helena Gschrey
- Leon Schmitt
- Christoph Großmann
- Joerdis Krieger
- Ron Krestel (ORCID: https://orcid.org/0009-0005-5472-261X)
- Christoffer Mayer
- Javier-Ortega Garcia
- Sanjay Saha (ORCID: https://orcid.org/0009-0003-5386-0768)
Institutions
- OTH Regensburg (DE)
- Citrix (Switzerland) (CH)
- Universidad de Buenos Aires (AR)
- Fraunhofer Institute for Computer Graphics Research (DE)
- Technische Universität Darmstadt (DE)
- Universidad Autónoma de Madrid (ES)
Publication Details
- Journal
- Pattern Recognition
- Published
- 2024-12-20
- DOI
- https://doi.org/10.1016/j.patcog.2024.111287
- Citations
- 1
- Primary Topic
- User Authentication and Security Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.78