Covert lie detection using keyboard dynamics

Abstract Identifying the true identity of a subject in the absence of external verification criteria (documents, DNA, fingerprints, etc.) is an unresolved issue. Here, we report an experiment on the verification of fake identities, identified by means of their specific keystroke dynamics as analysed...

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Autores principales:	Merylin Monaro, Chiara Galante, Riccardo Spolaor, Qian Qian Li, Luciano Gamberini, Mauro Conti, Giuseppe Sartori
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2018
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/34c4d7637f5241c1babb76a3475f6646
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spelling	oai:doaj.org-article:34c4d7637f5241c1babb76a3475f66462021-12-02T15:05:41ZCovert lie detection using keyboard dynamics10.1038/s41598-018-20462-62045-2322https://doaj.org/article/34c4d7637f5241c1babb76a3475f66462018-01-01T00:00:00Zhttps://doi.org/10.1038/s41598-018-20462-6https://doaj.org/toc/2045-2322Abstract Identifying the true identity of a subject in the absence of external verification criteria (documents, DNA, fingerprints, etc.) is an unresolved issue. Here, we report an experiment on the verification of fake identities, identified by means of their specific keystroke dynamics as analysed in their written response using a computer keyboard. Results indicate that keystroke analysis can distinguish liars from truth tellers with a high degree of accuracy - around 95% - thanks to the use of unexpected questions that efficiently facilitate the emergence of deception clues.Merylin MonaroChiara GalanteRiccardo SpolaorQian Qian LiLuciano GamberiniMauro ContiGiuseppe SartoriNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 8, Iss 1, Pp 1-10 (2018)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Merylin Monaro Chiara Galante Riccardo Spolaor Qian Qian Li Luciano Gamberini Mauro Conti Giuseppe Sartori Covert lie detection using keyboard dynamics
description	Abstract Identifying the true identity of a subject in the absence of external verification criteria (documents, DNA, fingerprints, etc.) is an unresolved issue. Here, we report an experiment on the verification of fake identities, identified by means of their specific keystroke dynamics as analysed in their written response using a computer keyboard. Results indicate that keystroke analysis can distinguish liars from truth tellers with a high degree of accuracy - around 95% - thanks to the use of unexpected questions that efficiently facilitate the emergence of deception clues.
format	article
author	Merylin Monaro Chiara Galante Riccardo Spolaor Qian Qian Li Luciano Gamberini Mauro Conti Giuseppe Sartori
author_facet	Merylin Monaro Chiara Galante Riccardo Spolaor Qian Qian Li Luciano Gamberini Mauro Conti Giuseppe Sartori
author_sort	Merylin Monaro
title	Covert lie detection using keyboard dynamics
title_short	Covert lie detection using keyboard dynamics
title_full	Covert lie detection using keyboard dynamics
title_fullStr	Covert lie detection using keyboard dynamics
title_full_unstemmed	Covert lie detection using keyboard dynamics
title_sort	covert lie detection using keyboard dynamics
publisher	Nature Portfolio
publishDate	2018
url	https://doaj.org/article/34c4d7637f5241c1babb76a3475f6646
work_keys_str_mv	AT merylinmonaro covertliedetectionusingkeyboarddynamics AT chiaragalante covertliedetectionusingkeyboarddynamics AT riccardospolaor covertliedetectionusingkeyboarddynamics AT qianqianli covertliedetectionusingkeyboarddynamics AT lucianogamberini covertliedetectionusingkeyboarddynamics AT mauroconti covertliedetectionusingkeyboarddynamics AT giuseppesartori covertliedetectionusingkeyboarddynamics
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Covert lie detection using keyboard dynamics

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