Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/349634
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dc.contributor.CRUESPUNIVERSIDADE ESTADUAL DE CAMPINASpt_BR
dc.contributor.authorunicampSantos, Geise-
dc.contributor.authorunicampTavares, Tiago Fernandes-
dc.contributor.authorunicampRocha, Anderson Pires-
dc.typeArtigopt_BR
dc.titleManifold learning for user profiling and identity verification using motion sensorspt_BR
dc.contributor.authorSantos, Geise-
dc.contributor.authorPisani, Paulo Henrique-
dc.contributor.authorLeyva, Roberto-
dc.contributor.authorLi, Chang-Tsun-
dc.contributor.authorTavares, Tiago-
dc.contributor.authorRocha, Anderson-
dc.subjectAprendizado manifoldpt_BR
dc.subject.otherlanguageManifold learningpt_BR
dc.description.abstractMobile devices are becoming ubiquitous and being increasingly used for data-sensitive activities such as communication, personal media storage, and banking. The protection of such data commonly relies on passwords and biometric traits such as fingerprints. These methods perform the user authentication sporadically and often require action from the user, which may make them susceptible to spoofing attacks. This scenario can be mitigated if we bring to bear motion-sensing based methods for authentication, which operate continuously and without requiring user action, hence are harder to attack. Such methods could be used allied with traditional authentication methods or on their own. This paper explores this idea in a novel user-agnostic approach for identity verification based on motion traits acquired by mobile sensors. The proposed approach does not require user-specific training before deployment in mobile devices nor does it require any extra sensor in the device. This solution is capable of learning a user profiling manifold from a small user subset and extend it to unknown users. We validated the proposal on two public datasets. The reported experiments demonstrate remarkable results under a cross-dataset protocol and an open-set setup. Moreover, we performed several analyses aiming at answering critical questions of a biometric method and the presented solutionpt_BR
dc.relation.ispartofPattern recognitionpt_BR
dc.relation.ispartofabbreviationPattern recognit.pt_BR
dc.publisher.cityAmsterdampt_BR
dc.publisher.countryPaíses Baixospt_BR
dc.publisherElsevierpt_BR
dc.date.issued2020-
dc.date.monthofcirculationOct.pt_BR
dc.language.isoengpt_BR
dc.description.volume106pt_BR
dc.rightsFechadopt_BR
dc.sourceWOSpt_BR
dc.identifier.issn0031-3203pt_BR
dc.identifier.eissn1873-5142pt_BR
dc.identifier.doi10.1016/j.patcog.2020.107408pt_BR
dc.identifier.urlhttps://www.sciencedirect.com/science/article/pii/S0031320320302119pt_BR
dc.description.sponsorshipCOORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIOR - CAPESpt_BR
dc.description.sponsorshipFUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESPpt_BR
dc.description.sponsordocumentnumber88882.160443/2014-01pt_BR
dc.description.sponsordocumentnumber2017/12646-3pt_BR
dc.date.available2020-09-18T18:49:41Z-
dc.date.accessioned2020-09-18T18:49:41Z-
dc.description.provenanceSubmitted by Mariana Aparecida Azevedo (mary1@unicamp.br) on 2020-09-18T18:49:41Z No. of bitstreams: 0. Added 1 bitstream(s) on 2021-01-08T19:03:24Z : No. of bitstreams: 1 000541777200010.pdf: 3802278 bytes, checksum: 9bf2801f560ded265f6e73b39650b299 (MD5)en
dc.description.provenanceMade available in DSpace on 2020-09-18T18:49:41Z (GMT). No. of bitstreams: 0 Previous issue date: 2020en
dc.identifier.urihttp://repositorio.unicamp.br/jspui/handle/REPOSIP/349634-
dc.contributor.departmentsem informaçãopt_BR
dc.contributor.departmentDepartamento de Engenharia de Computação e Automação Industrialpt_BR
dc.contributor.departmentsem informaçãopt_BR
dc.contributor.unidadeInstituto de Computaçãopt_BR
dc.contributor.unidadeFaculdade de Engenharia Elétrica e de Computaçãopt_BR
dc.contributor.unidadeInstituto de Computaçãopt_BR
dc.subject.keywordUser profilingpt_BR
dc.subject.keywordMotion sensorpt_BR
dc.subject.keywordGaitpt_BR
dc.subject.keywordOpen-set user profilingpt_BR
dc.subject.keywordCross-dataset user profilingpt_BR
dc.identifier.source000541777200010pt_BR
dc.creator.orcid0000-0002-0178-5482pt_BR
dc.creator.orcid0000-0002-9104-613Xpt_BR
dc.creator.orcidsem informaçãopt_BR
dc.type.formArtigopt_BR
dc.identifier.articleid107408pt_BR
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