Konferenzbeitrag
Fast and Accurate Continuous User Authentication by Fusion of Instance-based, Free-text Keystroke Dynamics
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Datum
2019
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Gesellschaft für Informatik e.V.
Zusammenfassung
Keystroke dynamics study the way in which users input text via their keyboards, which is
unique to each individual, and can form a component of a behavioral biometric system to improve
existing account security. Keystroke dynamics systems on free-text data use n-graphs that measure
the timing between consecutive keystrokes to distinguish between users. Many algorithms require
500, 1,000, or more keystrokes to achieve EERs of below 10%. In this paper, we propose an instancebased
graph comparison algorithm to reduce the number of keystrokes required to authenticate users.
Commonly used features such as monographs and digraphs are investigated. Feature importance
is determined and used to construct a fused classifier. Detection error tradeoff (DET) curves are
produced with different numbers of keystrokes. The fused classifier outperforms the state-of-the-art
with EERs of 7.9%, 5.7%, 3.4%, and 2.7% for test samples of 50, 100, 200, and 500 keystrokes.