| Author | Stragapede, Giuseppe; Vera-Rodriguez, Ruben; Tolosana, Ruben; Morales, Aythami; DeAndres-Tame, Ivan; Damer, Naser; Fierrez, Julian; Ortega-Garcia, Javier; Acien, Alejandro; Gonzalez, Nahuel; Shadrikov, Andrei; Gordin, Dmitrii; Schmitt, Leon; Wimmer, Daniel; Großmann, Christoph; Krieger, Joerdis; Heinz, Florian; Krestel, Ron; Mayer, Christoffer; Haberl, Simon; Gschrey, Helena; Yamagishi, Yosuke; Wickramanayake, Sandareka; Saha, Sanjay; Rasnayaka, Sanka; Gutfeter, Weronika; Sim, Terence; Baran, Adam; Krzysztoń, Mateusz; Jaskóła, Przemysław |
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| Abstract | This article presents the Keystroke Verification Challenge - onGoing (KVC-onGoing)1, 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 CodaLab2 . |
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