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Article

A Framework for Continuous Authentication Based on Touch Dynamics Biometrics for Mobile Banking Applications

Cybersecurity INCT Unit 6, Decision Technologies Laboratory—LATITUDE, Electrical Engineering Department (ENE), Technology College, University of Brasília (UnB), Brasília 70910-900, Brazil
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Academic Editors: Ramon Alcarria and Borja Bordel
Sensors 2021, 21(12), 4212; https://doi.org/10.3390/s21124212
Received: 25 April 2021 / Revised: 12 June 2021 / Accepted: 13 June 2021 / Published: 19 June 2021
As smart devices have become commonly used to access internet banking applications, these devices constitute appealing targets for fraudsters. Impersonation attacks are an essential concern for internet banking providers. Therefore, user authentication countermeasures based on biometrics, whether physiological or behavioral, have been developed, including those based on touch dynamics biometrics. These measures take into account the unique behavior of a person when interacting with touchscreen devices, thus hindering identitification fraud because it is hard to impersonate natural user behaviors. Behavioral biometric measures also balance security and usability because they are important for human interfaces, thus requiring a measurement process that may be transparent to the user. This paper proposes an improvement to Biotouch, a supervised Machine Learning-based framework for continuous user authentication. The contributions of the proposal comprise the utilization of multiple scopes to create more resilient reasoning models and their respective datasets for the improved Biotouch framework. Another contribution highlighted is the testing of these models to evaluate the imposter False Acceptance Error (FAR). This proposal also improves the flow of data and computation within the improved framework. An evaluation of the multiple scope model proposed provides results between 90.68% and 97.05% for the harmonic mean between recall and precision (F1 Score). The percentages of unduly authenticated imposters and errors of legitimate user rejection (Equal Error Rate (EER)) are between 9.85% and 1.88% for static verification, login, user dynamics, and post-login. These results indicate the feasibility of the continuous multiple-scope authentication framework proposed as an effective layer of security for banking applications, eventually operating jointly with conventional measures such as password-based authentication. View Full-Text
Keywords: continuous authentication; touch dynamics biometrics; mobile security; mobile authentication continuous authentication; touch dynamics biometrics; mobile security; mobile authentication
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MDPI and ACS Style

Estrela, P.M.A.B.; Albuquerque, R.d.O.; Amaral, D.M.; Giozza, W.F.; Júnior, R.T.d.S. A Framework for Continuous Authentication Based on Touch Dynamics Biometrics for Mobile Banking Applications. Sensors 2021, 21, 4212. https://doi.org/10.3390/s21124212

AMA Style

Estrela PMAB, Albuquerque RdO, Amaral DM, Giozza WF, Júnior RTdS. A Framework for Continuous Authentication Based on Touch Dynamics Biometrics for Mobile Banking Applications. Sensors. 2021; 21(12):4212. https://doi.org/10.3390/s21124212

Chicago/Turabian Style

Estrela, Priscila M.A.B., Robson d.O. Albuquerque, Dino M. Amaral, William F. Giozza, and Rafael T.d.S. Júnior 2021. "A Framework for Continuous Authentication Based on Touch Dynamics Biometrics for Mobile Banking Applications" Sensors 21, no. 12: 4212. https://doi.org/10.3390/s21124212

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