An investigation of biometric-based user predictability in the online game League of Legends

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dc.contributor.advisorAbreu, Marjory Cristiany da Costa
dc.contributor.advisorIDpt_BR
dc.contributor.authorSilva, Valmiro Ribeiro da
dc.contributor.authorIDpt_BR
dc.contributor.referees1Canuto, Anne Magaly de Paula
dc.contributor.referees1IDpt_BR
dc.contributor.referees2Souza Neto, Placido Antonio de
dc.contributor.referees2IDpt_BR
dc.date.accessioned2019-05-06T21:18:44Z
dc.date.available2019-05-06T21:18:44Z
dc.date.issued2019-02-07
dc.description.resumoComputer games have been consolidated as a favourite activity for years now. Although such games were created to promote competition and promote self-improvement, there are some recurrent issues. One that has received the least amount of attention so far is the problem of "account sharing" which is when a player shares his/her account with more experienced players in order to progress in the game. The companies running those games tend to punish this behaviour, but this specific case is hard to identify. Since, the popularity of machine learning techniques have never been higher, the aim of this study is to better understand how biometric data from online games behaves, to understand how the choice of character impacts a player and how different algorithms perform when we vary how frequently a sample is collected. The experiments showed through the use of statistic tests how consistent a player can be even when he/she changes characters or roles, what are the impacts of more training samples, how the tested machine learning algorithms results are affected by how often we collect our samples, and how dimensionality reduction techniques, such as Principal Component Analysis affect our data, all providing more information about how this state of art game database works.pt_BR
dc.identifier.citationSILVA, Valmiro Ribeiro da. An investigation of biometric-based user predictability in the online game League of Legends. 2019. 60f. Dissertação (Mestrado em Sistemas e Computação) - Centro de Ciências Exatas e da Terra, Universidade Federal do Rio Grande do Norte, Natal, 2019.pt_BR
dc.identifier.urihttps://repositorio.ufrn.br/jspui/handle/123456789/26974
dc.languagept_BRpt_BR
dc.publisher.countryBrasilpt_BR
dc.publisher.initialsUFRNpt_BR
dc.publisher.programPROGRAMA DE PÓS-GRADUAÇÃO EM SISTEMAS E COMPUTAÇÃOpt_BR
dc.rightsAcesso Abertopt_BR
dc.subjectBiometricspt_BR
dc.subjectKeystroke dynamicspt_BR
dc.subjectMouse dynamicspt_BR
dc.subjectDimensionality reductionpt_BR
dc.subjectUser verificationpt_BR
dc.subjectLeague of legendspt_BR
dc.subjectInsider treatpt_BR
dc.subject.cnpqCNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO::SISTEMAS DE COMPUTACAOpt_BR
dc.titleAn investigation of biometric-based user predictability in the online game League of Legendspt_BR
dc.typemasterThesispt_BR

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