A Comparative Analysis of Features Selection Techniques Using Genetic Algorithm in Keystroke Dynamics

Bibliographic Details
Main Author: Nascimento, Tuany Mariah Lima do
Publication Date: 2019
Format: Bachelor thesis
Language: eng
Source: Repositório Institucional da UFRN
dARK ID: ark:/41046/001300000qw8x
Download full: https://repositorio.ufrn.br/handle/123456789/37908
Summary: CNPq
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oai_identifier_str oai:repositorio.ufrn.br:123456789/37908
network_acronym_str UFRN
network_name_str Repositório Institucional da UFRN
repository_id_str
spelling A Comparative Analysis of Features Selection Techniques Using Genetic Algorithm in Keystroke Dynamicsgender recognitionfeatures selectiongenetic algorithmsCNPqDue to the continuous use of social networks, users can be vulnerable to situations such as paedophilia treats. One of the ways to do the investigation of an alleged paedophile is to verify the legitimacy of the genre that it is said to be. One possible technique to adopt is keystroke dynamics analysis. However, this technique can extract many attributes, causing a negative impact on the accuracy of the classifier due to the presence of redundant and irrelevant attributes. Therefore, the present work presents a comparative analysis between two attribute selection approaches, wrapper and hybrid (wrapper + filter), using the metaheuristic genetic algorithm, as KNN, SVM, and Naive Bayes classifiers and as Correlation and Relief filter. Bringing the best SVM classifier using the wrapper approach, for both databases.Universidade Federal do Rio Grande do NorteBrasilUFRNAnálise e Desenvolvimento de SistemasOliveira, Laura Emmanuella Alves dos Santos Santana deMárjory Da Costa AbreuOliveira, Josenalde Barbosa deAraújo, Daniel Sabino Amorim deNascimento, Tuany Mariah Lima do2019-07-01T12:07:15Z2021-09-22T14:24:47Z2019-07-01T12:07:15Z2021-09-22T14:24:47Z2019-06-10info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/bachelorThesisapplication/pdf20160144419NASCIMENTO, Tuany Mariah Lima do. A Comparative Analysis of Features Selection Techniques Using Genetic Algorithm in Keystroke Dynamics. 2019. 36f. Trabalho de Conclusão de Curso (Graduação em Análise e Desenvolvimento de Sistemas) - Unidade Acadêmica Especializada em Ciências Agrárias, Universidade Federal do Rio Grande do Norte, Macaíba, 2019.https://repositorio.ufrn.br/handle/123456789/37908ark:/41046/001300000qw8xengreponame:Repositório Institucional da UFRNinstname:Universidade Federal do Rio Grande do Norte (UFRN)instacron:UFRNinfo:eu-repo/semantics/openAccess2024-11-29T17:46:24Zoai:repositorio.ufrn.br:123456789/37908Repositório InstitucionalPUBhttp://repositorio.ufrn.br/oai/repositorio@bczm.ufrn.bropendoar:2024-11-29T17:46:24Repositório Institucional da UFRN - Universidade Federal do Rio Grande do Norte (UFRN)false
dc.title.none.fl_str_mv A Comparative Analysis of Features Selection Techniques Using Genetic Algorithm in Keystroke Dynamics
title A Comparative Analysis of Features Selection Techniques Using Genetic Algorithm in Keystroke Dynamics
spellingShingle A Comparative Analysis of Features Selection Techniques Using Genetic Algorithm in Keystroke Dynamics
Nascimento, Tuany Mariah Lima do
gender recognition
features selection
genetic algorithms
title_short A Comparative Analysis of Features Selection Techniques Using Genetic Algorithm in Keystroke Dynamics
title_full A Comparative Analysis of Features Selection Techniques Using Genetic Algorithm in Keystroke Dynamics
title_fullStr A Comparative Analysis of Features Selection Techniques Using Genetic Algorithm in Keystroke Dynamics
title_full_unstemmed A Comparative Analysis of Features Selection Techniques Using Genetic Algorithm in Keystroke Dynamics
title_sort A Comparative Analysis of Features Selection Techniques Using Genetic Algorithm in Keystroke Dynamics
author Nascimento, Tuany Mariah Lima do
author_facet Nascimento, Tuany Mariah Lima do
author_role author
dc.contributor.none.fl_str_mv Oliveira, Laura Emmanuella Alves dos Santos Santana de
Márjory Da Costa Abreu
Oliveira, Josenalde Barbosa de
Araújo, Daniel Sabino Amorim de
dc.contributor.author.fl_str_mv Nascimento, Tuany Mariah Lima do
dc.subject.por.fl_str_mv gender recognition
features selection
genetic algorithms
topic gender recognition
features selection
genetic algorithms
description CNPq
publishDate 2019
dc.date.none.fl_str_mv 2019-07-01T12:07:15Z
2019-07-01T12:07:15Z
2019-06-10
2021-09-22T14:24:47Z
2021-09-22T14:24:47Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/bachelorThesis
format bachelorThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv 20160144419
NASCIMENTO, Tuany Mariah Lima do. A Comparative Analysis of Features Selection Techniques Using Genetic Algorithm in Keystroke Dynamics. 2019. 36f. Trabalho de Conclusão de Curso (Graduação em Análise e Desenvolvimento de Sistemas) - Unidade Acadêmica Especializada em Ciências Agrárias, Universidade Federal do Rio Grande do Norte, Macaíba, 2019.
https://repositorio.ufrn.br/handle/123456789/37908
dc.identifier.dark.fl_str_mv ark:/41046/001300000qw8x
identifier_str_mv 20160144419
NASCIMENTO, Tuany Mariah Lima do. A Comparative Analysis of Features Selection Techniques Using Genetic Algorithm in Keystroke Dynamics. 2019. 36f. Trabalho de Conclusão de Curso (Graduação em Análise e Desenvolvimento de Sistemas) - Unidade Acadêmica Especializada em Ciências Agrárias, Universidade Federal do Rio Grande do Norte, Macaíba, 2019.
ark:/41046/001300000qw8x
url https://repositorio.ufrn.br/handle/123456789/37908
dc.language.iso.fl_str_mv eng
language eng
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Federal do Rio Grande do Norte
Brasil
UFRN
Análise e Desenvolvimento de Sistemas
publisher.none.fl_str_mv Universidade Federal do Rio Grande do Norte
Brasil
UFRN
Análise e Desenvolvimento de Sistemas
dc.source.none.fl_str_mv reponame:Repositório Institucional da UFRN
instname:Universidade Federal do Rio Grande do Norte (UFRN)
instacron:UFRN
instname_str Universidade Federal do Rio Grande do Norte (UFRN)
instacron_str UFRN
institution UFRN
reponame_str Repositório Institucional da UFRN
collection Repositório Institucional da UFRN
repository.name.fl_str_mv Repositório Institucional da UFRN - Universidade Federal do Rio Grande do Norte (UFRN)
repository.mail.fl_str_mv repositorio@bczm.ufrn.br
_version_ 1839178754300051456

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