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Augmenting Authentication with Context-Specific Behavioral Biometrics

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Title:Augmenting Authentication with Context-Specific Behavioral Biometrics
Authors:Zhang, Haoruo
Singh, Digvijay
Li, Xiangyang
Keywords:Cybersecurity and Software Assurance
Software Technology
Behavioral Biometric, Continuous Authentication, Email Processing, Group Identity
Date Issued:08 Jan 2019
Abstract:Behavioral 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.
Pages/Duration:10 pages
URI:http://hdl.handle.net/10125/60165
ISBN:978-0-9981331-2-6
DOI:10.24251/HICSS.2019.875
Rights:Attribution-NonCommercial-NoDerivatives 4.0 International
https://creativecommons.org/licenses/by-nc-nd/4.0/
Appears in Collections: Cybersecurity and Software Assurance


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