Free-Text Keystroke Dynamics for User Authentication
Contribution to a Book
Advances in Information Security
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.
Jianwei Li, Han Chih Chang, and Mark Stamp. "Free-Text Keystroke Dynamics for User Authentication" Advances in Information Security (2022): 357-380. https://doi.org/10.1007/978-3-030-97087-1_15