HCCVDec 29, 2024

KVC-onGoing: Keystroke Verification Challenge

arXiv:2412.20530v12 citationsh-index: 42Pattern Recognition
Originality Synthesis-oriented
AI Analysis

This provides a standardized benchmark for researchers in biometrics and security, though it is incremental as it builds on existing keystroke dynamics methods.

The paper tackles the problem of keystroke verification by introducing a challenge platform with large-scale public databases, achieving state-of-the-art results such as 3.33% EER on desktop and 3.61% EER on mobile.

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.

Code Implementations1 repo
Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes