Adaptive algorithms applied to accelerometer biometrics in a data stream context

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dc.citation.issue2
dc.citation.volume21
dc.contributor.authorPisani, Paulo Henrique
dc.contributor.authorLorena, Ana Carolina[UNIFESP]
dc.contributor.authorde Carvalho, Andre C. P. L. F.
dc.coverageAmsterdam
dc.date.accessioned2020-07-31T12:46:46Z
dc.date.available2020-07-31T12:46:46Z
dc.date.issued2017
dc.description.abstractThe use of smartphone devices has increased over the last years, as illustrated by the growth in smartphone sales. These devices are currently used for several services, such as bank account access, social networks and storage of personal information. In view of this scenario, an important question arises: does authentication mechanisms already present in these devices provide enough security? Recently, a new authentication method, named accelerometer biometrics, has been proposed. This method allows the authentication of users using accelerometer data, which can be obtained from accelerometers usually present in modern smartphones. This is a clear advantage of this biometric modality, as there would be no additional cost with hardware. However, as a behavioral biometric technology, user models induced from accelerometer data may become outdated over time. This paper investigates the use of adaptation mechanisms to update user models in accelerometer biometrics in a data stream context. Practical issues regarding the usage of accelerometer data are also discussed.en
dc.description.affiliationUniv Sao Paulo, Inst Ciencias Matemat & Comp, BR-05508 Sao Paulo, SP, Brazil
dc.description.affiliationUniv Fed Sao Paulo, Inst Ciencia & Tecnol, Sao Paulo, SP, Brazil
dc.description.affiliationUnifespInstituto de Ciência e Tecnologia, Universidade Federal de São Paulo, SP, Brazil
dc.description.sourceWeb of Science
dc.description.sponsorshipCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.description.sponsorshipFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.description.sponsorshipIDFAPESP: 2012/25032-0
dc.description.sponsorshipIDFAPESP: 2012/22608-8
dc.description.sponsorshipIDFAPESP: 2013/07375-0
dc.format.extent353-370
dc.identifierhttp://dx.doi.org/10.3233/IDA-150403
dc.identifier.citationIntelligent Data Analysis. Amsterdam, v. 21, n. 2, p. 353-370, 2017.
dc.identifier.doi10.3233/IDA-150403
dc.identifier.issn1088-467X
dc.identifier.urihttps://repositorio.unifesp.br/handle/11600/56354
dc.identifier.wosWOS:000396260500008
dc.language.isoeng
dc.publisherIos Press
dc.relation.ispartofIntelligent Data Analysis
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.subjectAdaptive biometric systemsen
dc.subjectaccelerometer biometricsen
dc.subjectpositive selectionen
dc.subjectbiometric data streamsen
dc.titleAdaptive algorithms applied to accelerometer biometrics in a data stream contexten
dc.typeinfo:eu-repo/semantics/article
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