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Τίτλος: Behavioral biometrics & continuous user authentication on mobile devices: A survey
Συγγραφείς: Stylios, Ioannis Chr 
Kokolakis, Spyros A. 
Thanou, Olga 
Chatzis, Sotirios P. 
Major Field of Science: Natural Sciences
Field Category: Computer and Information Sciences
Λέξεις-κλειδιά: Machine learning;Behavioral biometrics;Continuous authentication;Mobile devices;Attacks;Defense;Survey
Ημερομηνία Έκδοσης: 1-Φεβ-2021
Πηγή: Information Fusion, 2021, vol. 66, pp. 76-99
Volume: 66
Start page: 76
End page: 99
Περιοδικό: Information Fusion 
Περίληψη: This paper offers an up-to-date, comprehensive, extensive and targeted survey on Behavioral Biometrics and Continuous Authentication technologies for mobile devices. Our aim is to help interested researchers to effectively grasp the background in this field and to avoid pitfalls in their work. In our survey, we first present a classification of behavioral biometrics technologies and continuous authentication for mobile devices and an analysis for behavioral biometrics collection methodologies and feature extraction techniques. Then, we provide a state-of-the-art literature review focusing on the machine learning models performance in seven types of behavioral biometrics for continuous authentication. Further, we conduct another review that showed the vulnerability of machine learning models against well-designed adversarial attack vectors and we highlight relevant countermeasures. Finally, our discussions extend to lessons learned, current challenges and future trends.
URI: https://hdl.handle.net/20.500.14279/22755
ISSN: 15662535
DOI: 10.1016/j.inffus.2020.08.021
Rights: © Elsevier
Attribution-NonCommercial-NoDerivatives 4.0 International
Type: Article
Affiliation: University of the Aegean 
Cyprus University of Technology 
Publication Type: Peer Reviewed
Εμφανίζεται στις συλλογές:Άρθρα/Articles

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