Improving versatility in keystroke dynamic systems
- Autores
- Calot, Enrique; Rodríguez, Juan Manuel
- Año de publicación
- 2013
- Idioma
- español castellano
- Tipo de recurso
- documento de conferencia
- Estado
- versión publicada
- Descripción
- Keystroke dynamics is a biometric technique to identify users based on analyzing habitual rhythm patterns in the way they type. In order to implement this technique di erent algorithms to di erentiate an impostor from an authorized user were suggested. One of the most pre- cise method is the Mahalanobis distance which requires to calculate the covariance matrix with all that this implies: time processing and track each individual keystroke event. The hypothesis of this research was to nd an algorithm as good as Mahalanobis which does not require track every single keystroke event and improve, where possible, the process- ing time. To make an experimental comparison between Mahalanobis distance and euclidean normalized, a distance which only requires calcu- late the variance, an already studied dataset was used. The results were that use normalized euclidean distance is almost as good as Mahalanobis distance even in some cases could work better.
WSI - II Workshop de seguridad informática
Red de Universidades con Carreras en Informática (RedUNCI) - Materia
-
Ciencias Informáticas
keystroke dynamics
web based authentication
mahalanobis distance
biometrics
typing biometrics - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
- Repositorio
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/32428
Ver los metadatos del registro completo
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Improving versatility in keystroke dynamic systemsCalot, EnriqueRodríguez, Juan ManuelCiencias Informáticaskeystroke dynamicsweb based authenticationmahalanobis distancebiometricstyping biometricsKeystroke dynamics is a biometric technique to identify users based on analyzing habitual rhythm patterns in the way they type. In order to implement this technique di erent algorithms to di erentiate an impostor from an authorized user were suggested. One of the most pre- cise method is the Mahalanobis distance which requires to calculate the covariance matrix with all that this implies: time processing and track each individual keystroke event. The hypothesis of this research was to nd an algorithm as good as Mahalanobis which does not require track every single keystroke event and improve, where possible, the process- ing time. To make an experimental comparison between Mahalanobis distance and euclidean normalized, a distance which only requires calcu- late the variance, an already studied dataset was used. The results were that use normalized euclidean distance is almost as good as Mahalanobis distance even in some cases could work better.WSI - II Workshop de seguridad informáticaRed de Universidades con Carreras en Informática (RedUNCI)2013-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/32428spainfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/2.5/ar/Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-10-22T16:39:51Zoai:sedici.unlp.edu.ar:10915/32428Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-22 16:39:51.998SEDICI (UNLP) - Universidad Nacional de La Platafalse |
dc.title.none.fl_str_mv |
Improving versatility in keystroke dynamic systems |
title |
Improving versatility in keystroke dynamic systems |
spellingShingle |
Improving versatility in keystroke dynamic systems Calot, Enrique Ciencias Informáticas keystroke dynamics web based authentication mahalanobis distance biometrics typing biometrics |
title_short |
Improving versatility in keystroke dynamic systems |
title_full |
Improving versatility in keystroke dynamic systems |
title_fullStr |
Improving versatility in keystroke dynamic systems |
title_full_unstemmed |
Improving versatility in keystroke dynamic systems |
title_sort |
Improving versatility in keystroke dynamic systems |
dc.creator.none.fl_str_mv |
Calot, Enrique Rodríguez, Juan Manuel |
author |
Calot, Enrique |
author_facet |
Calot, Enrique Rodríguez, Juan Manuel |
author_role |
author |
author2 |
Rodríguez, Juan Manuel |
author2_role |
author |
dc.subject.none.fl_str_mv |
Ciencias Informáticas keystroke dynamics web based authentication mahalanobis distance biometrics typing biometrics |
topic |
Ciencias Informáticas keystroke dynamics web based authentication mahalanobis distance biometrics typing biometrics |
dc.description.none.fl_txt_mv |
Keystroke dynamics is a biometric technique to identify users based on analyzing habitual rhythm patterns in the way they type. In order to implement this technique di erent algorithms to di erentiate an impostor from an authorized user were suggested. One of the most pre- cise method is the Mahalanobis distance which requires to calculate the covariance matrix with all that this implies: time processing and track each individual keystroke event. The hypothesis of this research was to nd an algorithm as good as Mahalanobis which does not require track every single keystroke event and improve, where possible, the process- ing time. To make an experimental comparison between Mahalanobis distance and euclidean normalized, a distance which only requires calcu- late the variance, an already studied dataset was used. The results were that use normalized euclidean distance is almost as good as Mahalanobis distance even in some cases could work better. WSI - II Workshop de seguridad informática Red de Universidades con Carreras en Informática (RedUNCI) |
description |
Keystroke dynamics is a biometric technique to identify users based on analyzing habitual rhythm patterns in the way they type. In order to implement this technique di erent algorithms to di erentiate an impostor from an authorized user were suggested. One of the most pre- cise method is the Mahalanobis distance which requires to calculate the covariance matrix with all that this implies: time processing and track each individual keystroke event. The hypothesis of this research was to nd an algorithm as good as Mahalanobis which does not require track every single keystroke event and improve, where possible, the process- ing time. To make an experimental comparison between Mahalanobis distance and euclidean normalized, a distance which only requires calcu- late the variance, an already studied dataset was used. The results were that use normalized euclidean distance is almost as good as Mahalanobis distance even in some cases could work better. |
publishDate |
2013 |
dc.date.none.fl_str_mv |
2013-10 |
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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 |
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info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/2.5/ar/ Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5) |
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openAccess |
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http://creativecommons.org/licenses/by-nc-sa/2.5/ar/ Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5) |
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