KVC-onGoing: Keystroke Verification Challenge
Abstract
This article presents the Keystroke Verification Challenge - onGoing (KVC-onGoing), 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.
Cite
@article{arxiv.2412.20530,
title = {KVC-onGoing: Keystroke Verification Challenge},
author = {Giuseppe Stragapede and Ruben Vera-Rodriguez and Ruben Tolosana and Aythami Morales and Ivan DeAndres-Tame and Naser Damer and Julian Fierrez and Javier Ortega-Garcia and Alejandro Acien and Nahuel Gonzalez and Andrei Shadrikov and Dmitrii Gordin and Leon Schmitt and Daniel Wimmer and Christoph Großmann and Joerdis Krieger and Florian Heinz and Ron Krestel and Christoffer Mayer and Simon Haberl and Helena Gschrey and Yosuke Yamagishi and Sanjay Saha and Sanka Rasnayaka and Sandareka Wickramanayake and Terence Sim and Weronika Gutfeter and Adam Baran and Mateusz Krzysztoń and Przemysław Jaskóła},
journal= {arXiv preprint arXiv:2412.20530},
year = {2024}
}
Comments
arXiv admin note: substantial text overlap with arXiv:2401.16559, arXiv:2311.06000