Machine learning algorithms for improving security on touch screen devices: a survey, challenges and new perspectives

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dc.contributor.authorBello, Auwal Ahmed
dc.contributor.authorChiroma, Haruna
dc.contributor.authorGital, Abdulsalam Ya’u
dc.date.accessioned2023-09-04T11:53:17Z
dc.date.available2023-09-04T11:53:17Z
dc.date.issued2020
dc.description.abstract
dc.description.sponsorshipACE: Technology Enhanced Learningen_US
dc.identifier.issn0941-0643
dc.identifier.urihttp://hdl.handle.net/123456789/2115
dc.language.isoenen_US
dc.publisherNeural Computing and Applicationsen_US
dc.relation.ispartofseriesNeural Computing and Applications;(2020) 32
dc.subjectMachine learning algorithmsen_US
dc.subjectDeep learningen_US
dc.subjectMobile phone touch screenen_US
dc.subjectAndroiden_US
dc.subjectSupport vector machineen_US
dc.subjectSecurityen_US
dc.subjectACE: Technology Enhanced Learningen_US
dc.subjectACETELen_US
dc.subjectNational open university of Nigeria (NOUN)en_US
dc.subjectNigeriaen_US
dc.subjectDigital Developmenten_US
dc.titleMachine learning algorithms for improving security on touch screen devices: a survey, challenges and new perspectivesen_US
dc.typeArticleen_US
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