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BioPrivacy: a behavioral biometrics continuous authentication system based on keystroke dynamics and touch gestures

Ioannis Stylios (Department of Information and Communication Systems Engineering, University of the Aegean, Mytilene, Greece)
Andreas Skalkos (Department of Information and Communication Systems Engineering, University of the Aegean, Mytilene, Greece)
Spyros Kokolakis (Department of Information and Communication Systems Engineering, University of the Aegean, Mytilene, Greece)
Maria Karyda (Department of Information and Communication Systems Engineering, University of the Aegean, Mytilene, Greece)

Information and Computer Security

ISSN: 2056-4961

Article publication date: 26 May 2022

Issue publication date: 7 November 2022

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Abstract

Purpose

This research aims to build a system that will continuously. This paper is an extended version of SECPRE 2021 paper and presents a research on the development and validation of a behavioral biometrics continuous authentication (BBCA) system that is based on users keystroke dynamics and touch gestures on mobile devices. This paper aims to build a system that will continuously authenticate the user of a smartphone.

Design/methodology/approach

Session authentication schemes establish the identity of the user only at the beginning of the session, so they are vulnerable to attacks that tamper with communications after the establishment of the authenticated session. Moreover, smartphones themselves are used as authentication means, especially in two-factor authentication schemes, which are often required by several services. Whether the smartphone is in the hands of the legitimate user constitutes a great concern and correspondingly whether the legitimate user is the one who uses the services. In response to these concerns, BBCA technologies have been proposed on a large corpus of literature. This paper presents a research on the development and validation of a BBCA system (named BioPrivacy), which is based on the user’s keystroke dynamics and touch gestures, using a multi-layer perceptron (MLP). Also, this paper introduces a new BB collection tool and proposes a methodology for the selection of an appropriate set of BB.

Findings

The system achieved the best results for keystroke dynamics which are 97.18% accuracy, 0.02% equal error rate, 97.2% true acceptance rate and 0.02% false acceptance rate.

Originality/value

This paper develops a new BB collection tool, named BioPrivacy, by which behavioral data of users on mobile devices can be collected. This paper proposes a methodology for the selection of an appropriate set of BB. This paper presents the development of a BBCA system based on MLP.

Keywords

Acknowledgements

This research is co-financed by Greece and the European Union (European Social Fund- ESF) through the Operational Programme «Human Resources Development, Education and Lifelong Learning 2014–2020» in the context of the project “BioPrivacy: Development and validation of a Behavioral Biometrics Continuous Authenti-cation System” (MIS 5052062).

Citation

Stylios, I., Skalkos, A., Kokolakis, S. and Karyda, M. (2022), "BioPrivacy: a behavioral biometrics continuous authentication system based on keystroke dynamics and touch gestures", Information and Computer Security, Vol. 30 No. 5, pp. 687-704. https://doi.org/10.1108/ICS-12-2021-0212

Publisher

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Emerald Publishing Limited

Copyright © 2020, Emerald Publishing Limited

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