Tools
Tools
Earl, Sally 
ORCID: https://orcid.org/0000-0002-3283-0274, Campbell, James and Buckley, Oliver ORCID: https://orcid.org/0000-0003-1502-5721
(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, pp. 184-190.
ISBN 978-3-030-79996-0
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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 |
| UEA Research Groups: | Faculty of Science > Research Groups > Smart Emerging Technologies Faculty of Science > Research Groups > Cyber Security Privacy and Trust Laboratory |
| Related URLs: | |
| Depositing User: | LivePure Connector |
| Date Deposited: | 01 Sep 2021 23:40 |
| Last Modified: | 13 Oct 2024 06:30 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/81261 |
| DOI: | 10.1007/978-3-030-79997-7_23 |
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