{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,7]],"date-time":"2026-05-07T18:47:50Z","timestamp":1778179670821,"version":"3.51.4"},"reference-count":47,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2021,6,19]],"date-time":"2021-06-19T00:00:00Z","timestamp":1624060800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>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.<\/jats:p>","DOI":"10.3390\/s21124212","type":"journal-article","created":{"date-parts":[[2021,6,20]],"date-time":"2021-06-20T21:50:15Z","timestamp":1624225815000},"page":"4212","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":26,"title":["A Framework for Continuous Authentication Based on Touch Dynamics Biometrics for Mobile Banking Applications"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9159-7647","authenticated-orcid":false,"given":"Priscila Morais Arg\u00f4lo Bonfim","family":"Estrela","sequence":"first","affiliation":[{"name":"Cybersecurity INCT Unit 6, Decision Technologies Laboratory\u2014LATITUDE, Electrical Engineering Department (ENE), Technology College, University of Bras\u00edlia (UnB), Bras\u00edlia 70910-900, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6717-3374","authenticated-orcid":false,"given":"Robson de Oliveira","family":"Albuquerque","sequence":"additional","affiliation":[{"name":"Cybersecurity INCT Unit 6, Decision Technologies Laboratory\u2014LATITUDE, Electrical Engineering Department (ENE), Technology College, University of Bras\u00edlia (UnB), Bras\u00edlia 70910-900, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8023-1057","authenticated-orcid":false,"given":"Dino Macedo","family":"Amaral","sequence":"additional","affiliation":[{"name":"Cybersecurity INCT Unit 6, Decision Technologies Laboratory\u2014LATITUDE, Electrical Engineering Department (ENE), Technology College, University of Bras\u00edlia (UnB), Bras\u00edlia 70910-900, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3003-3458","authenticated-orcid":false,"given":"William Ferreira","family":"Giozza","sequence":"additional","affiliation":[{"name":"Cybersecurity INCT Unit 6, Decision Technologies Laboratory\u2014LATITUDE, Electrical Engineering Department (ENE), Technology College, University of Bras\u00edlia (UnB), Bras\u00edlia 70910-900, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1101-3029","authenticated-orcid":false,"given":"Rafael Tim\u00f3teo de Sousa","family":"J\u00fanior","sequence":"additional","affiliation":[{"name":"Cybersecurity INCT Unit 6, Decision Technologies Laboratory\u2014LATITUDE, Electrical Engineering Department (ENE), Technology College, University of Bras\u00edlia (UnB), Bras\u00edlia 70910-900, Brazil"}]}],"member":"1968","published-online":{"date-parts":[[2021,6,19]]},"reference":[{"key":"ref_1","unstructured":"GSMA (2020, August 22). 2019 Mobile Industry Impact Report: Sustainable Development Goals Executive Summary. 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