Papaioannou, Maria, Zachos, Georgios, Mantas, Georgios ORCID: https://orcid.org/0000-0002-8074-0417, Essop, Aliyah ORCID: https://orcid.org/0000-0002-6978-9359, Karasuwa, Abdulkareem and Rodriguez, Jonathan (2022) Generating datasets based on the HuMIdb dataset for risk-based user authentication on Smartphones. In: 2022 IEEE 27th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD). 02-03 November 2022. Paris, France. IEEE Xplore . Institute of Electrical and Electronics Engineers (IEEE), Piscataway, New Jersey, pp. 134-139. ISBN 978-1665461290; 978-1665461306 ISSN 2378-4873 (Print), 2378-4865 (Online) (doi:10.1109/CAMAD55695.2022.9966901)

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Abstract

User authentication acts as the first line of defense verifying the identity of a mobile user, often as a prerequisite to allow access to resources in a mobile device. Risk-based user authentication based on behavioral biometrics appears to have the potential to increase mobile authentication security without sacrificing usability. Nevertheless, in order to precisely evaluate classification and/or novelty detection algorithms for risk-based user authentication, it is of utmost importance to make use of quality datasets to train and test these algorithms. To the best of our knowledge, there is a lack of up-to-date, representative and comprehensive datasets that are publicly available to the research community for effective training and evaluation of classification and/or novelty detection algorithms suitable for risk-based user authentication. Toward this direction, in this paper, the aim is to provide details on how we generate datasets based on HuMIdb dataset for training and testing classification and novelty detection algorithms for risk-based adaptive user authentication. The HuMIdb dataset is the most recent and publicly available dataset for behavioral user authentication.

Item Type:	Conference Proceedings
Title of Proceedings:	2022 IEEE 27th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD). 02-03 November 2022. Paris, France
Uncontrolled Keywords:	mobile device security; risk-based adaptive user authentication; dataset generation; record selection
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > T Technology (General)
Faculty / School / Research Centre / Research Group:	Faculty of Engineering & Science Faculty of Engineering & Science > School of Engineering (ENG)
Last Modified:	13 Dec 2022 17:02
URI:	http://gala.gre.ac.uk/id/eprint/38257

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