Identifying Soft Biometric Features from a Combination of Keystroke and Mouse Dynamics

Earl, Sally, Campbell, James and Buckley, Oliver (2021) Identifying Soft Biometric Features from a Combination of Keystroke and Mouse Dynamics. In: Advances in Human Factors in Robots, Unmanned Systems and Cybersecurity - Proceedings of the AHFE 2021. Lecture Notes in Networks and Systems . Springer, Cham, pp. 184-190. ISBN 978-3-030-79996-0

[img] PDF (KDMD) - Accepted Version
Restricted to Repository staff only until 27 June 2022.

Download (137kB) | Request a copy

Abstract

In this preliminary paper, we investigate the use of keystroke and mouse dynamics as a means of identifying soft biometric features. We present evidence that combining features from both provides a more accurate means of identifying all of the soft biometric traits investigated, regardless of the machine learning method used. The data presented in this paper gives a thorough breakdown of accuracy scores from multiple machine learning methods and numbers of features used.

Item Type: Book Section
Uncontrolled Keywords: keystroke dynamics,mouse dynamics,soft biometrics,control and systems engineering,signal processing,computer networks and communications ,/dk/atira/pure/subjectarea/asjc/2200/2207
Faculty \ School: Faculty of Science > School of Computing Sciences
Related URLs:
Depositing User: LivePure Connector
Date Deposited: 01 Sep 2021 23:40
Last Modified: 01 Sep 2021 23:40
URI: https://ueaeprints.uea.ac.uk/id/eprint/81261
DOI: 10.1007/978-3-030-79997-7_23

Actions (login required)

View Item View Item