  In this paper, a new behavioral biometric password based on haptic
interaction is described. This "haptic password" system is built on a device
that has a force-sensitive screen. The user authentication process leverages
maximal overlap discrete wavelet transform (MODWT) based feature extraction
along with a customized classifier as well as an adaptive template scheme to
accommodate users' variations over time. An experimental study was conducted
with 29 subjects and we investigated the authentication performance with
multiple user postures under simulated forgery attacks. The performance of the
model is evaluated based on authentication accuracies. The results suggest that
this proposed haptic password system achieves robust high authentication
accuracy and scalability, as well as forgery-proof performance.
