Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/22755
DC FieldValueLanguage
dc.contributor.authorStylios, Ioannis Chr-
dc.contributor.authorKokolakis, Spyros A.-
dc.contributor.authorThanou, Olga-
dc.contributor.authorChatzis, Sotirios P.-
dc.date.accessioned2021-06-22T11:03:02Z-
dc.date.available2021-06-22T11:03:02Z-
dc.date.issued2021-02-01-
dc.identifier.citationInformation Fusion, 2021, vol. 66, pp. 76-99en_US
dc.identifier.issn15662535-
dc.identifier.urihttps://hdl.handle.net/20.500.14279/22755-
dc.description.abstractThis paper offers an up-to-date, comprehensive, extensive and targeted survey on Behavioral Biometrics and Continuous Authentication technologies for mobile devices. Our aim is to help interested researchers to effectively grasp the background in this field and to avoid pitfalls in their work. In our survey, we first present a classification of behavioral biometrics technologies and continuous authentication for mobile devices and an analysis for behavioral biometrics collection methodologies and feature extraction techniques. Then, we provide a state-of-the-art literature review focusing on the machine learning models performance in seven types of behavioral biometrics for continuous authentication. Further, we conduct another review that showed the vulnerability of machine learning models against well-designed adversarial attack vectors and we highlight relevant countermeasures. Finally, our discussions extend to lessons learned, current challenges and future trends.en_US
dc.formatpdfen_US
dc.language.isoenen_US
dc.relation.ispartofInformation Fusionen_US
dc.rights© Elsevieren_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectMachine learningen_US
dc.subjectBehavioral biometricsen_US
dc.subjectContinuous authenticationen_US
dc.subjectMobile devicesen_US
dc.subjectAttacksen_US
dc.subjectDefenseen_US
dc.subjectSurveyen_US
dc.titleBehavioral biometrics & continuous user authentication on mobile devices: A surveyen_US
dc.typeArticleen_US
dc.collaborationUniversity of the Aegeanen_US
dc.collaborationCyprus University of Technologyen_US
dc.subject.categoryComputer and Information Sciencesen_US
dc.journalsSubscriptionen_US
dc.countryGreeceen_US
dc.countryCyprusen_US
dc.subject.fieldNatural Sciencesen_US
dc.publicationPeer Revieweden_US
dc.identifier.doi10.1016/j.inffus.2020.08.021en_US
dc.identifier.scopus2-s2.0-85090859901-
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/85090859901-
dc.relation.volume66en_US
cut.common.academicyear2020-2021en_US
dc.identifier.spage76en_US
dc.identifier.epage99en_US
item.grantfulltextnone-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.openairetypearticle-
item.fulltextNo Fulltext-
crisitem.journal.journalissn1566-2535-
crisitem.journal.publisherElsevier-
crisitem.author.deptDepartment of Electrical Engineering, Computer Engineering and Informatics-
crisitem.author.facultyFaculty of Engineering and Technology-
crisitem.author.orcid0000-0002-4956-4013-
crisitem.author.parentorgFaculty of Engineering and Technology-
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