Evaluation of Motion-based Touch-typing Biometrics in Online Financial Environments

Abstract

This paper presents a bimodal scheme, the mechanism which contemplates the way a user enters an 8-digit PIN/password and the phone-movements while doing so, for user authentication in mobile banking/financial applications (apps). The scheme authenticates the user based on the timing differences of the entered strokes. Additionally, it enhances the security by introducing a transparent layer utilizing the phone-movements made by the user. The scheme is assumed to be highly secure as mimicking the invisible touch-timings and the phone-movements could be extremely onerous. Our analysis is based on 2850 samples collected from 95 users through a 3-day unsupervised field experiment and using 3 multi-class classifiers. Random Forest (RF) classifier out-performed other two classifiers and provided a True Acceptance Rate (TAR) of 96%.