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IEEE BigData 2023 Keystroke Verification Challenge (KVC)

Authors :
Stragapede, Giuseppe
Vera-Rodriguez, Ruben
Tolosana, Ruben
Morales, Aythami
DeAndres-Tame, Ivan
Damer, Naser
Fierrez, Julian
Garcia, Javier-Ortega
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
Saha, Sanjay
Rasnayaka, Sanka
Wickramanayake, Sandareka
Sim, Terence
Gutfeter, Weronika
Baran, Adam
Krzyszton, Mateusz
Jaskola, Przemyslaw
Publication Year :
2024

Abstract

This paper describes the results of the IEEE BigData 2023 Keystroke Verification Challenge (KVC), that considers the biometric verification performance of Keystroke Dynamics (KD), captured as tweet-long sequences of variable transcript text from over 185,000 subjects. The data are obtained from two of the largest public databases of KD up to date, the Aalto Desktop and Mobile Keystroke Databases, guaranteeing a minimum amount of data per subject, age and gender annotations, absence of corrupted data, and avoiding excessively unbalanced subject distributions with respect to the considered demographic attributes. Several neural architectures were proposed by the participants, leading to global Equal Error Rates (EERs) as low as 3.33% and 3.61% achieved by the best team respectively in the desktop and mobile scenario, outperforming the current state of the art biometric verification performance for KD. Hosted on CodaLab, the KVC will be made ongoing to represent a useful tool for the research community to compare different approaches under the same experimental conditions and to deepen the knowledge of the field.<br />Comment: 9 pages, 10 pages, 2 figures. arXiv admin note: text overlap with arXiv:2311.06000

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2401.16559
Document Type :
Working Paper