Application of Keystroke Dynamics Modelling Techniques to Strengthen the User Identification in the Context of E-commerce

Autores
Concilio, Germán M.; Calot, Enrique; Ierache, Jorge Salvador; Merlino, Hernán
Año de publicación
2018
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Keystroke dynamics is a biometric technique to identify users based on analysing habitual rhythm patterns in their typing behaviour. In e-commerce, this technique brings benefits to both security and the analysis of patterns of consumer behaviour. This paper focuses on analysing the keystroke dynamics against an e-commerce site for personal identification. This paper is an empirical reinforcement of previous works, with data extracted from realistic conditions that are of most interest for the practical application of modelling keystroke dynamics in free texts. It was a collaborative work with one of the leading e-commerce companies in Latin America. Experimental results showed that it was possible to identify typists with an accuracy of 89% from a sampling of 300 randomly selected users just by reading comment field keystrokes.
VII Workshop Seguridad Informática (WSI)
Red de Universidades con Carreras en Informática (RedUNCI)
Materia
Ciencias Informáticas
keystroke dynamics
biometrics
e-commerce
user identification
user classification
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/73628
Acceder
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repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Application of Keystroke Dynamics Modelling Techniques to Strengthen the User Identification in the Context of E-commerceConcilio, Germán M.Calot, EnriqueIerache, Jorge SalvadorMerlino, HernánCiencias Informáticaskeystroke dynamicsbiometricse-commerceuser identificationuser classificationKeystroke dynamics is a biometric technique to identify users based on analysing habitual rhythm patterns in their typing behaviour. In e-commerce, this technique brings benefits to both security and the analysis of patterns of consumer behaviour. This paper focuses on analysing the keystroke dynamics against an e-commerce site for personal identification. This paper is an empirical reinforcement of previous works, with data extracted from realistic conditions that are of most interest for the practical application of modelling keystroke dynamics in free texts. It was a collaborative work with one of the leading e-commerce companies in Latin America. Experimental results showed that it was possible to identify typists with an accuracy of 89% from a sampling of 300 randomly selected users just by reading comment field keystrokes.VII Workshop Seguridad Informática (WSI)Red de Universidades con Carreras en Informática (RedUNCI)2018-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf1051-1059http://sedici.unlp.edu.ar/handle/10915/73628enginfo:eu-repo/semantics/altIdentifier/isbn/978-950-658-472-6info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-03T10:44:34Zoai:sedici.unlp.edu.ar:10915/73628Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-03 10:44:34.623SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Application of Keystroke Dynamics Modelling Techniques to Strengthen the User Identification in the Context of E-commerce
title Application of Keystroke Dynamics Modelling Techniques to Strengthen the User Identification in the Context of E-commerce
spellingShingle Application of Keystroke Dynamics Modelling Techniques to Strengthen the User Identification in the Context of E-commerce
Concilio, Germán M.
Ciencias Informáticas
keystroke dynamics
biometrics
e-commerce
user identification
user classification
title_short Application of Keystroke Dynamics Modelling Techniques to Strengthen the User Identification in the Context of E-commerce
title_full Application of Keystroke Dynamics Modelling Techniques to Strengthen the User Identification in the Context of E-commerce
title_fullStr Application of Keystroke Dynamics Modelling Techniques to Strengthen the User Identification in the Context of E-commerce
title_full_unstemmed Application of Keystroke Dynamics Modelling Techniques to Strengthen the User Identification in the Context of E-commerce
title_sort Application of Keystroke Dynamics Modelling Techniques to Strengthen the User Identification in the Context of E-commerce
dc.creator.none.fl_str_mv Concilio, Germán M.
Calot, Enrique
Ierache, Jorge Salvador
Merlino, Hernán
author Concilio, Germán M.
author_facet Concilio, Germán M.
Calot, Enrique
Ierache, Jorge Salvador
Merlino, Hernán
author_role author
author2 Calot, Enrique
Ierache, Jorge Salvador
Merlino, Hernán
author2_role author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
keystroke dynamics
biometrics
e-commerce
user identification
user classification
topic Ciencias Informáticas
keystroke dynamics
biometrics
e-commerce
user identification
user classification
dc.description.none.fl_txt_mv Keystroke dynamics is a biometric technique to identify users based on analysing habitual rhythm patterns in their typing behaviour. In e-commerce, this technique brings benefits to both security and the analysis of patterns of consumer behaviour. This paper focuses on analysing the keystroke dynamics against an e-commerce site for personal identification. This paper is an empirical reinforcement of previous works, with data extracted from realistic conditions that are of most interest for the practical application of modelling keystroke dynamics in free texts. It was a collaborative work with one of the leading e-commerce companies in Latin America. Experimental results showed that it was possible to identify typists with an accuracy of 89% from a sampling of 300 randomly selected users just by reading comment field keystrokes.
VII Workshop Seguridad Informática (WSI)
Red de Universidades con Carreras en Informática (RedUNCI)
description Keystroke dynamics is a biometric technique to identify users based on analysing habitual rhythm patterns in their typing behaviour. In e-commerce, this technique brings benefits to both security and the analysis of patterns of consumer behaviour. This paper focuses on analysing the keystroke dynamics against an e-commerce site for personal identification. This paper is an empirical reinforcement of previous works, with data extracted from realistic conditions that are of most interest for the practical application of modelling keystroke dynamics in free texts. It was a collaborative work with one of the leading e-commerce companies in Latin America. Experimental results showed that it was possible to identify typists with an accuracy of 89% from a sampling of 300 randomly selected users just by reading comment field keystrokes.
publishDate 2018
dc.date.none.fl_str_mv 2018-10
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
Objeto de conferencia
http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
format conferenceObject
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/73628
url http://sedici.unlp.edu.ar/handle/10915/73628
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/isbn/978-950-658-472-6
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
1051-1059
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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