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Outlier detection for risk-based user authentication on mobile devices

Outlier detection for risk-based user authentication on mobile devices

Papaioannou, Maria, Zachos, Georgios, Mantas, Georgios ORCID logoORCID: https://orcid.org/0000-0002-8074-0417, Essop, Ismael ORCID logoORCID: https://orcid.org/0000-0002-5583-0306, Saghezchi, Firooz and Rodriguez, Jonathan (2024) Outlier detection for risk-based user authentication on mobile devices. In: GLOBECOM 2023 - 2023 IEEE Global Communications Conference, Kuala Lumpur, Malaysia, 2023. IEEE Xplore . Institute of Electrical and Electronics Engineers (IEEE), Piscataway, New York, pp. 2778-2783. ISBN 979-8350310900; 979-8350310917 ISSN 2576-6813 (Print), 1930-529X (Online) (doi:10.1109/GLOBECOM54140.2023.10437467)

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Abstract

Mobile user authentication is the primary means of verifying the claimed identity of a user before granting access to resources on a mobile device. Common user authentication methods include passwords and biometrics. Despite the fact that passwords have been the most popular user authentication method for several decades, recent research suggests that they are no longer secure or convenient for mobile users due to several limitations that compromise both device security and usability. Biometric-based user authentication, on the other hand, is gaining popularity because it appears to strike a balance between security and usability. Such methods rely on human physical traits (physiological biometrics) or user involuntary actions (behavioral biometrics) for authentication. Risk-based user authentication using behavioral biometrics is particularly promising for mobile user authentication enhancing mobile authentication security while maintaining usability. In this context, we present an overview of mobile user authentication and discuss risk-based user authentication for mobile devices as a suitable approach to deal with the security vs. usability challenge. Afterwards, we test and evaluate a set of outlier detection algorithms for risk estimation in order to identify the most suitable ones for risk-based user authentication on mobile devices in terms of their accuracy and efficiency.

Item Type: Conference Proceedings
Title of Proceedings: GLOBECOM 2023 - 2023 IEEE Global Communications Conference, Kuala Lumpur, Malaysia, 2023
Uncontrolled Keywords: outlier detection; behavioral biometric-based user authentication; risk-based user authentication; mobile devices
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
T Technology > T Technology (General)
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty / School / Research Centre / Research Group: Faculty of Engineering & Science
Faculty of Engineering & Science > School of Engineering (ENG)
Related URLs:
Last Modified: 14 Mar 2024 14:48
URI: http://gala.gre.ac.uk/id/eprint/44117

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