KVC-onGoing: Keystroke Verification Challenge
Giuseppe Stragapede, Rubén Vera-Rodríguez, Rubén Tolosana, Aythami Morales, Ivan DeAndres-Tame, Naser Damer, Julián Fiérrez, Javier-Ortega Garcia, Alejandro Acien, Nahuel González, Andrei Shadrikov, Dmitrii Gordin, Leon Schmitt, Daniel Wimmer, Christoph Großmann, Joerdis Krieger, Florian Heinz, Ron Krestel, Christoffer Mayer, Simon Haberl · Pattern Recognition · 2024
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.