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Dataset of human-written and synthesized samples of keystroke dynamics features for free-text inputs
The data presented in this article comprises human-written samples of keystroke dynamic features for free-text inputs, in the form of sentences written in natural language, together with synthesized samples that share the same text sequences. The human-written samples originate in three publicly ava...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10139888/ https://www.ncbi.nlm.nih.gov/pubmed/37122930 http://dx.doi.org/10.1016/j.dib.2023.109125 |
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author | González, Nahuel Calot, Enrique P. |
author_facet | González, Nahuel Calot, Enrique P. |
author_sort | González, Nahuel |
collection | PubMed |
description | The data presented in this article comprises human-written samples of keystroke dynamic features for free-text inputs, in the form of sentences written in natural language, together with synthesized samples that share the same text sequences. The human-written samples originate in three publicly available datasets that have been previously used in several keystroke dynamics studies; the corresponding synthesized samples, which have been forged as detailed in the companion article, share the same keystroke sequences as the human-written ones to facilitate comparison. The human-written samples were collected, and the synthesized samples created, with the objective of training and evaluating a liveness detection model. For each human-written sample of each source dataset and each method, 25 synthetic samples were included in the dataset here presented; these were forged using five different methods, a between-subject profile (only samples from users other than the target were available to the attacker) or with varying partial knowledge of the legitimate users’ keystroke dynamics that ranged from only 100 keystrokes to all the available information. This dataset can be used by researchers to evaluate the performance of liveness detection methods for keystroke dynamics against a variety of state-of-the-art methods of sample synthesis. |
format | Online Article Text |
id | pubmed-10139888 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-101398882023-04-29 Dataset of human-written and synthesized samples of keystroke dynamics features for free-text inputs González, Nahuel Calot, Enrique P. Data Brief Data Article The data presented in this article comprises human-written samples of keystroke dynamic features for free-text inputs, in the form of sentences written in natural language, together with synthesized samples that share the same text sequences. The human-written samples originate in three publicly available datasets that have been previously used in several keystroke dynamics studies; the corresponding synthesized samples, which have been forged as detailed in the companion article, share the same keystroke sequences as the human-written ones to facilitate comparison. The human-written samples were collected, and the synthesized samples created, with the objective of training and evaluating a liveness detection model. For each human-written sample of each source dataset and each method, 25 synthetic samples were included in the dataset here presented; these were forged using five different methods, a between-subject profile (only samples from users other than the target were available to the attacker) or with varying partial knowledge of the legitimate users’ keystroke dynamics that ranged from only 100 keystrokes to all the available information. This dataset can be used by researchers to evaluate the performance of liveness detection methods for keystroke dynamics against a variety of state-of-the-art methods of sample synthesis. Elsevier 2023-04-07 /pmc/articles/PMC10139888/ /pubmed/37122930 http://dx.doi.org/10.1016/j.dib.2023.109125 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Data Article González, Nahuel Calot, Enrique P. Dataset of human-written and synthesized samples of keystroke dynamics features for free-text inputs |
title | Dataset of human-written and synthesized samples of keystroke dynamics features for free-text inputs |
title_full | Dataset of human-written and synthesized samples of keystroke dynamics features for free-text inputs |
title_fullStr | Dataset of human-written and synthesized samples of keystroke dynamics features for free-text inputs |
title_full_unstemmed | Dataset of human-written and synthesized samples of keystroke dynamics features for free-text inputs |
title_short | Dataset of human-written and synthesized samples of keystroke dynamics features for free-text inputs |
title_sort | dataset of human-written and synthesized samples of keystroke dynamics features for free-text inputs |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10139888/ https://www.ncbi.nlm.nih.gov/pubmed/37122930 http://dx.doi.org/10.1016/j.dib.2023.109125 |
work_keys_str_mv | AT gonzaleznahuel datasetofhumanwrittenandsynthesizedsamplesofkeystrokedynamicsfeaturesforfreetextinputs AT calotenriquep datasetofhumanwrittenandsynthesizedsamplesofkeystrokedynamicsfeaturesforfreetextinputs |