Recurrent Neural Networks are powerful machine learning frameworks that allow for data to
be saved and referenced in a temporal sequence. This opens many new possibilities in …

Reliably identifying and authenticating users remains integral to computer system security.
Various novel authentication tenchniques such as biometric authentication systems have …

We study the performance of Long Short-Term Memory networks for keystroke biometric
authentication at large scale in free-text scenarios. For this we explore the performance of …

In this paper we list the sensors commonly available in modern smartphones and provide a
general outlook of the different ways these sensors can be used for modeling the interaction …

We study the suitability of keystroke dynamics to authenticate 100 K users typing free-text.
For this, we first analyze to what extent our method based on a Siamese Recurrent Neural …

Background Objective measures of screen time are necessary to better understand the
complex relationship between screen time and health outcomes. However, current objective …

We introduce a novel multimodal mobile database called HuMIdb (Human Mobile
Interaction database) that comprises 14 mobile sensors acquired from 600 users. The …

Background: Mental fatigue is a common and potentially debilitating state that can affect
individuals' health and quality of life. In some cases, its manifestation can precede or mask …

Mobile applications are widely used for online services sharing a large amount of personal
data online. One-time authentication techniques such as passwords and physiological …

Keystroke dynamics is a soft biometric based on the assumption that humans always type in
uniquely characteristic manners. Previous works mainly focused on analyzing the key press …