On the discriminability of keystroke feature vectors used in fixed text keystroke authentication

Contributions to empirical analysis of keystroke dynamics in passwords

“…Moreover, if we take for training the very first samples (1)(2)(3)(4)(5), instead of samples from 196 to 200 (where we believe the user got used to the password), the resulting EER increases from 5.6 ± 1.3% to 35.2 ± 5.5% . A related conclusion was put forward by Syed et al [22] concerning the significant improvement of classifiers rebuilt after users were habituated to the password.…”

“…Following similar ideas, many approaches have been proposed since then, ranging from mean and covariance-based strategies [1] to artificial neural networks [16]. More recently, a study [2] was conducted concerning the discriminability of keystroke feature vectors for authentication from fixed texts. There, it was shown, first theoretically and then experimentally, that heterogeneous vectors can provide higher discriminability than aggregate ones.…”

Advanced Authentication Scheme Using a Predefined Keystroke Structure

“…Additionally, [4] describes preliminary experimental results describing using keystroke timing as a basic of authentication system in which a textual material and a statistical model was developed and used within an experimental study. Most keystroke dynamics studies had been evaluated using datasets where users typed the same fixed string [7], [6], while very few of them used different strings for each user [11].…”

Keystroke Dynamics Overview

“…A recent paper Balagani et al (2011) discusses on the way of using these extracted features in order to improve the recognition rate of keystroke dynamics systems. Other kinds of data can be encountered in various papers Ilonen (2003).…”