  In this research, we consider the problem of verifying user identity based on
keystroke dynamics obtained from free-text. We employ a novel feature
engineering method that generates image-like transition matrices. For this
image-like feature, a convolution neural network (CNN) with cutout achieves the
best results. A hybrid model consisting of a CNN and a recurrent neural network
(RNN) is also shown to outperform previous research in this field.
