On the shape of timings distributions in free-text keystroke dynamics profiles

Keystroke dynamics is a soft biometric trait. Although the shape of the timing distributions in keystroke dynamics profiles is a central element for the accurate modeling of the behavioral patterns of the user, a simplified approach has been to presuppose normality. Careful consideration of the indi...

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Autores principales:	Nahuel González, Enrique P. Calot, Jorge S. Ierache, Waldo Hasperué
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Soft biometrics Keystroke dynamics Free text Probability distribution Science (General) Q1-390 Social sciences (General) H1-99
Acceso en línea:	https://doaj.org/article/c54c349f5c0841a4882885f8a2473bd5
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spelling	oai:doaj.org-article:c54c349f5c0841a4882885f8a2473bd52021-12-02T05:03:06ZOn the shape of timings distributions in free-text keystroke dynamics profiles2405-844010.1016/j.heliyon.2021.e08413https://doaj.org/article/c54c349f5c0841a4882885f8a2473bd52021-11-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2405844021025160https://doaj.org/toc/2405-8440Keystroke dynamics is a soft biometric trait. Although the shape of the timing distributions in keystroke dynamics profiles is a central element for the accurate modeling of the behavioral patterns of the user, a simplified approach has been to presuppose normality. Careful consideration of the individual shapes for the timing models could lead to improvements in the error rates of current methods or possibly inspire new ones. The main objective of this study is to compare several heavy-tailed and positively skewed candidate distributions in order to rank them according to their merit for fitting timing histograms in keystroke dynamics profiles. Results are summarized in three ways: counting how many times each candidate distribution provides the best fit and ranking them in order of success, measuring average information content, and ranking candidate distributions according to the frequency of hypothesis rejection with an Anderson-Darling goodness of fit test. Seven distributions with two parameters and seven with three were evaluated against three publicly available free-text keystroke dynamics datasets. The results confirm the established use in the research community of the log-normal distribution, in its two- and three-parameter variations, as excellent choices for modeling the shape of timings histograms in keystroke dynamics profiles. However, the log-logistic distribution emerges as a clear winner among all two- and three-parameter candidates, consistently surpassing the log-normal and all the rest under the three evaluation criteria for both hold and flight times.Nahuel GonzálezEnrique P. CalotJorge S. IeracheWaldo HasperuéElsevierarticleSoft biometricsKeystroke dynamicsFree textProbability distributionScience (General)Q1-390Social sciences (General)H1-99ENHeliyon, Vol 7, Iss 11, Pp e08413- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Soft biometrics Keystroke dynamics Free text Probability distribution Science (General) Q1-390 Social sciences (General) H1-99
spellingShingle	Soft biometrics Keystroke dynamics Free text Probability distribution Science (General) Q1-390 Social sciences (General) H1-99 Nahuel González Enrique P. Calot Jorge S. Ierache Waldo Hasperué On the shape of timings distributions in free-text keystroke dynamics profiles
description	Keystroke dynamics is a soft biometric trait. Although the shape of the timing distributions in keystroke dynamics profiles is a central element for the accurate modeling of the behavioral patterns of the user, a simplified approach has been to presuppose normality. Careful consideration of the individual shapes for the timing models could lead to improvements in the error rates of current methods or possibly inspire new ones. The main objective of this study is to compare several heavy-tailed and positively skewed candidate distributions in order to rank them according to their merit for fitting timing histograms in keystroke dynamics profiles. Results are summarized in three ways: counting how many times each candidate distribution provides the best fit and ranking them in order of success, measuring average information content, and ranking candidate distributions according to the frequency of hypothesis rejection with an Anderson-Darling goodness of fit test. Seven distributions with two parameters and seven with three were evaluated against three publicly available free-text keystroke dynamics datasets. The results confirm the established use in the research community of the log-normal distribution, in its two- and three-parameter variations, as excellent choices for modeling the shape of timings histograms in keystroke dynamics profiles. However, the log-logistic distribution emerges as a clear winner among all two- and three-parameter candidates, consistently surpassing the log-normal and all the rest under the three evaluation criteria for both hold and flight times.
format	article
author	Nahuel González Enrique P. Calot Jorge S. Ierache Waldo Hasperué
author_facet	Nahuel González Enrique P. Calot Jorge S. Ierache Waldo Hasperué
author_sort	Nahuel González
title	On the shape of timings distributions in free-text keystroke dynamics profiles
title_short	On the shape of timings distributions in free-text keystroke dynamics profiles
title_full	On the shape of timings distributions in free-text keystroke dynamics profiles
title_fullStr	On the shape of timings distributions in free-text keystroke dynamics profiles
title_full_unstemmed	On the shape of timings distributions in free-text keystroke dynamics profiles
title_sort	on the shape of timings distributions in free-text keystroke dynamics profiles
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/c54c349f5c0841a4882885f8a2473bd5
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On the shape of timings distributions in free-text keystroke dynamics profiles

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