DEFT: A new distance-based feature set for keystroke dynamics
Nuwan Kaluarachchi Sevvandi Kandanaarachchi Kristen Moore Arathi Arakala
Keystroke dynamics is a behavioural biometric utilised for user
identification and authentication. We propose a new set of features based on
the distance between keys on the keyboard, a concept that has not been
considered before in keystroke dynamics. We combine flight times, a popular
metric, with the distance between keys on the keyboard and call them as
Distance Enhanced Flight Time features (DEFT). This novel approach provides
comprehensive insights into a person's typing behaviour, surpassing typing
velocity alone. We build a DEFT model by combining DEFT features with other
previously used keystroke dynamic features. The DEFT model is designed to be
device-agnostic, allowing us to evaluate its effectiveness across three
commonly used devices: desktop, mobile, and tablet. The DEFT model outperforms
the existing state-of-the-art methods when we evaluate its effectiveness across
two datasets. We obtain accuracy rates exceeding 99% and equal error rates
below 10% on all three devices.