2 research outputs found
Intrusion Detection Using Mouse Dynamics
Compared to other behavioural biometrics, mouse dynamics is a less explored
area. General purpose data sets containing unrestricted mouse usage data are
usually not available. The Balabit data set was released in 2016 for a data
science competition, which against the few subjects, can be considered the
first adequate publicly available one. This paper presents a performance
evaluation study on this data set for impostor detection. The existence of very
short test sessions makes this data set challenging. Raw data were segmented
into mouse move, point and click and drag and drop types of mouse actions, then
several features were extracted. In contrast to keystroke dynamics, mouse data
is not sensitive, therefore it is possible to collect negative mouse dynamics
data and to use two-class classifiers for impostor detection. Both action- and
set of actions-based evaluations were performed. Set of actions-based
evaluation achieves 0.92 AUC on the test part of the data set. However, the
same type of evaluation conducted on the training part of the data set resulted
in maximal AUC (1) using only 13 actions. Drag and drop mouse actions proved to
be the best actions for impostor detection.Comment: Submitted to IET Biometrics on 23 May 201