Augmenting Authentication with Context-Specific Behavioral Biometrics

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dc.contributor.authorZhang, Haoruo
dc.contributor.authorSingh, Digvijay
dc.contributor.authorLi, Xiangyang
dc.date.accessioned2019-01-03T00:59:00Z
dc.date.available2019-01-03T00:59:00Z
dc.date.issued2019-01-08
dc.description.abstractBehavioral biometrics, being non-intrusive and cost-efficient, have the potential to assist user identification and authentication. However, user behaviors can vary significantly for different hardware, software, and applications. Research of behavioral biometrics is needed in the context of a specific application. Moreover, it is hard to collect user data in real world settings to assess how well behavioral biometrics can discriminate users. This work aims to improving authentication by behavioral biometrics obtained for user groups. User data of a webmail application are collected in a large-scale user experiment conducted on Amazon Mechanical Turk. Used in a continuous authentication scheme based on user groups, off-line identity attribution and online authentication analytic schemes are proposed to study the applicability of application-specific behavioral biometrics. Our results suggest that the useful user group identity can be effectively inferred from users’ operational interaction with the email application.
dc.format.extent10 pages
dc.identifier.doi10.24251/HICSS.2019.875
dc.identifier.isbn978-0-9981331-2-6
dc.identifier.urihttp://hdl.handle.net/10125/60165
dc.language.isoeng
dc.relation.ispartofProceedings of the 52nd Hawaii International Conference on System Sciences
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectCybersecurity and Software Assurance
dc.subjectSoftware Technology
dc.subjectBehavioral Biometric, Continuous Authentication, Email Processing, Group Identity
dc.titleAugmenting Authentication with Context-Specific Behavioral Biometrics
dc.typeConference Paper
dc.type.dcmiText

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