Biologic verification based on pressure sensor keyboards and classifier fusion techniques

This paper presents a novel biologic verification method based on pressure sensor keyboards and classifier fusion techniques. The pressure sensor keyboard is a new product that occurs in the market recently. It produces a pressure sequence when keystroke occurs. The analysis of the pressure sequence should be a novel research area. In this paper, we use the pressure sequence and traditional keystroke dynamics in user authentication. Three methods (global features of pressure sequences, dynamic time warping, and traditional keystroke dynamics) are proposed for the authentication task. We combined the three methods together using a classifier fusion technique at last. Several experiments were performed on a database containing 5000 samples of 100 individuals and the best result were achieved utilizing all the method, obtaining an equal error rate of 1.41%. To make a comparison, the equal error rate is 2.04% when we use only the traditional keystroke dynamics. This approach can be used to improve the usual login-password authentication when the password is no more a secret