2 research outputs found
Kernel Deep Regression Network for Touch-Stroke Dynamics Authentication
—Touch-stroke dynamics is an emerging behavioral
biometrics justified feasible for mobile identity management. A
touch-stroke dynamics authentication system is composed of a
hand-engineered feature extractor and a classifier separately. In
this letter, we propose a stacking-based deep learning network that
performs feature extraction and classification, collectively dubbed
Kernel Deep Regression Network (KDRN). The KDRN is built on
multiple kernel ridge regressions (KRR) hierarchically, where each
is trained analytically and independently. In principal, KDRN does
not mean to learn directly from the raw touch-stroke data like other
deep learning models, but it relearns from the pre-extracted features to yield a richer and a relatively more discriminative feature
set. Subsequent to that, the authentication is carried out by KRR.
Overall, KDRN achieves an equal error rate of 0.013% for intrasession authentication, 0.023% for intersession authentication, and
0.121% for interweek authentication on the Touchlaytics datase
Kernel Deep Regression Network for Touch-Stroke Dynamics Authentication
—Touch-stroke dynamics is an emerging behavioral
biometrics justified feasible for mobile identity management. A
touch-stroke dynamics authentication system is composed of a
hand-engineered feature extractor and a classifier separately. In
this letter, we propose a stacking-based deep learning network that
performs feature extraction and classification, collectively dubbed
Kernel Deep Regression Network (KDRN). The KDRN is built on
multiple kernel ridge regressions (KRR) hierarchically, where each
is trained analytically and independently. In principal, KDRN does
not mean to learn directly from the raw touch-stroke data like other
deep learning models, but it relearns from the pre-extracted features to yield a richer and a relatively more discriminative feature
set. Subsequent to that, the authentication is carried out by KRR.
Overall, KDRN achieves an equal error rate of 0.013% for intrasession authentication, 0.023% for intersession authentication, and
0.121% for interweek authentication on the Touchlaytics datase