Please use this identifier to cite or link to this item: https://ktisis.cut.ac.cy/handle/10488/22755
Title: Behavioral biometrics & continuous user authentication on mobile devices: A survey
Authors: Stylios, Ioannis Chr 
Kokolakis, Spyros A. 
Thanou, Olga 
Chatzis, Sotirios P. 
Major Field of Science: Natural Sciences
Field Category: Computer and Information Sciences
Keywords: Machine learning;Behavioral biometrics;Continuous authentication;Mobile devices;Attacks;Defense;Survey
Issue Date: 1-Feb-2021
Source: Information Fusion, 2021, vol. 66, pp. 76-99
Volume: 66
Start page: 76
End page: 99
Journal: Information Fusion 
Abstract: 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://ktisis.cut.ac.cy/handle/10488/22755
ISSN: 1566-2535
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 
Appears in Collections:Άρθρα/Articles

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