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Keystroke dynamics as part of lifelogging

Smeaton, Alan F. ORCID: 0000-0003-1028-8389, Krishnamurthy, Naveen Garaga and Suryanarayana, Amruth Hebbasuru (2021) Keystroke dynamics as part of lifelogging. In: 27th International Conference on Multimedia Modeling, MMM 2021, 22-24 June 2021, Prage, Czech Republic (Online). ISBN 978-3-030-67835-7

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Abstract

In this paper we present the case for including keystroke dynamics in lifelogging. We describe how we have used a simple keystroke logging application called Loggerman, to create a dataset of longitudinal keystroke timing data spanning a period of up to seven months for four participants. We perform a detailed analysis of this data by examining the timing information associated with bigrams or pairs of adjacently-typed alphabetic characters. We show how the amount of day-on-day variation of the keystroke timing among the top-200 bigrams for participants varies with the amount of typing each would do on a daily basis. We explore how daily variations could correlate with sleep score from the previous night but find no significant relationship between the two. Finally we describe the public release of a portion of this data and we include a series of pointers for future work including correlating keystroke dynamics with mood and fatigue during the day.

Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Additional Information:The final authenticated publication is available online at https://link.springer.com/chapter/10.1007/978-3-030-67835-7_16
Uncontrolled Keywords:Keystroke dynamics; Sleep logging
Subjects:Computer Science > Artificial intelligence
Computer Science > Multimedia systems
Computer Science > Lifelog
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Research Initiatives and Centres > INSIGHT Centre for Data Analytics
Published in: 27th International Conference on Multimedia Modeling (MMM 2021), Proceedings. Lecture Notes in Computer Science (LNCS) 12573. Springer. ISBN 978-3-030-67835-7
Publisher:Springer
Official URL:https://link.springer.com/chapter/10.1007/978-3-030-67835-7_16
Copyright Information:© The Authors
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
Funders:Science Foundation Ireland, Grant Number SFI/12/RC/2289 P2
ID Code:25133
Deposited On:29 Jan 2021 11:47 by Alan Smeaton . Last Modified 29 Jan 2021 11:47

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