User Authentication through Typing Biometrics Features

Score normalization for keystroke dynamics biometrics

“…• Scaled Manhattan Distance [13]: based on the one proposed by Araujo et al [14]. The distance between a feature vector of the test sample and the enrollment set is calculated as:…”

Keystroke Dynamics Overview

“…We can obtain the character from this code (in order to verify if the list of characters corresponds to the password, for example). The key code is more interesting than the character, because it gives some information on the location of the key on the keyboard (which can be used by some keystroke dynamics recognition methods) and allows to differentiate different keys giving the same character (which is a discriminant information (Araujo et al, 2005)). This key code may be dependant of the platform and the language used.…”

Biometric Access Control Through Numerical Keyboards Based on Keystroke Dynamics

“…In [8] the authors suggest that the user template be composed of the mean and standard deviation of sample feature vector acquired during the enrollment. Every time a user needs to authenticate his password, the system calculates the distance of the target string to the template.…”

“…τ k (a) is a empirically defined threshold for user account a. In [8] an data updating mechanism for the model is considered similarly with [6]. The authors reported error rates are below 2%.…”