Papaioannou, Maria ORCID: https://orcid.org/0000-0003-3830-7190, Zachos, Georgios ORCID: https://orcid.org/0000-0001-9130-4605, Mantas, Georgios ORCID: https://orcid.org/0000-0002-8074-0417, Panaousis, Emmanouil ORCID: https://orcid.org/0000-0001-7306-4062 and Rodriguez, Jonathan (2024) Prototyping a secure and usable user authentication mechanism for mobile passenger ID devices for land/sea border control. Sensors, 24 (16):5193. ISSN 1424-8220 (Online) (doi:10.3390/s24165193)

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Abstract

As the number of European Union (EU) visitors grows, implementing novel border control solutions, such as mobile devices for passenger identification for land and sea border control, becomes paramount to ensure the convenience and safety of passengers and officers. However, these devices, handling sensitive personal data, become attractive targets for malicious actors seeking to misuse or steal such data. Therefore, to increase the level of security of such devices without interrupting border control activities, robust user authentication mechanisms are essential. Toward this direction, we propose a risk-based adaptive user authentication mechanism for mobile passenger identification devices for land and sea border control, aiming to enhance device security without hindering usability. In this work, we present a comprehensive assessment of novelty and outlier detection algorithms and discern OneClassSVM, Local Outlier Factor (LOF), and Bayesian_GaussianMixtureModel (B_GMM) novelty detection algorithms as the most effective ones for risk estimation in the proposed mechanism. Furthermore, in this work, we develop the proposed risk-based adaptive user authentication mechanism as an application on a Raspberry Pi 4 Model B device (i.e., playing the role of the mobile device for passenger identification), where we evaluate the detection performance of the three best performing novelty detection algorithms (i.e., OneClassSVM, LOF, and B_GMM), with B_GMM surpassing the others in performance when deployed on the Raspberry Pi 4 device. Finally, we evaluate the risk estimation overhead of the proposed mechanism when the best performing B_GMM novelty detection algorithm is used for risk estimation, indicating efficient operation with minimal additional latency.

Item Type:	Article
Additional Information:	This article belongs to the Special Issue Feature Papers in the 'Sensor Networks' Section 2024.
Uncontrolled Keywords:	adaptive user authentication, risk-based user authentication, risk estimation, novelty detection, outlier detection, mobile passenger ID devices, prototype development
Subjects:	Q Science > Q Science (General) 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)
Last Modified:	14 Nov 2024 11:57
URI:	http://gala.gre.ac.uk/id/eprint/48619

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