Exploring capacitive swipe gesture for user authentication using a new large dataset

Abstract

We investigate the viability of the capacitive swipe gesture as a biometric modality. While the regular swipe gesture and the capacitive image have been widely explored in biometric literature, the capacitive swipe gesture is fairly new in this line of research. To our knowledge, only one recent study has explored the capacitive swipe gesture, and demonstrated its promise. However, that study is limited by a number of factors, such as using a very small data set in the experiments, collecting data in a single session, allowing the same impostor in both training and testing phases of authentication models, etc. In our paper, we address all these limitations, and rigorously explore the capacitive swipe gesture by creating a new large data set. Additionally, we develop a new technique to preprocess capacitive swipe gesture data, and demonstrate its effectiveness by comparing with existing techniques. A large set of experiments with four machine learning classifiers and two swipe directions prove that the capacitive swipe gesture can be effectively used for user authentication in smartphones.