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

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Earl, Sally, 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:	http://www.scopus.com/inward/record.url?... https://link.springer.com/10.1007/978-3-...
Depositing User:	LivePure Connector
Date Deposited:	01 Sep 2021 23:40
Last Modified:	14 Mar 2023 08:37
URI:	https://ueaeprints.uea.ac.uk/id/eprint/81261
DOI:	10.1007/978-3-030-79997-7_23

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