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The MOBIKEY Keystroke Dynamics Password Database: Benchmark Results

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Software Engineering Perspectives and Application in Intelligent Systems ( ICTIS 2017, CSOC 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 465))

Abstract

In this paper we study keystroke dynamics as an authentication mechanism for touchscreen based devices. A data collection application was designed and implemented for Android devices in order to collect several types of password. Besides easy and strong passwords we propose a new type of password—logical strong—which is a strong password, but easy to remember due to the logic behind the password’s characters. Three main types of feature were used in the evaluation: time-based, touch-based and accelerometer-based. We propose a novel feature set—secondorder—which is independent of the length of the password. The preliminary results show that the lowest equal error rate (EER) is achieved by the logical strong password, followed by the strong password. The worst performance was achieved by the easy password; suggesting that the strong password is the best choice even in the case of keystroke dynamics based authentication systems.

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Acknowledgments

The research has been supported by the European Union and Hungary and co-financed by the European Social Fund through the project TAMOP–4.2.2.C–11/1/KONV–2012–0004–National Research Center for Development and Market Introduction of Advanced Information and Communication Technologies. The authors would like to thank all volunteers who participated in the data collection experiment.

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Authors and Affiliations

  1. Faculty of Technical and Human Sciences, Sapientia University, Soseaua Sighisoarei 1C, 540485, Tirgu Mures/Corunca, Romania

    Margit Antal & Lehel Nemes

Authors
  1. Margit Antal
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  2. Lehel Nemes
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Corresponding author

Correspondence to Margit Antal .

Editor information

Editors and Affiliations

  1. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlín, Czech Republic

    Radek Silhavy

  2. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlín, Czech Republic

    Roman Senkerik

  3. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlín, Czech Republic

    Zuzana Kominkova Oplatkova

  4. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlín, Czech Republic

    Petr Silhavy

  5. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlín, Czech Republic

    Zdenka Prokopova

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Antal, M., Nemes, L. (2016). The MOBIKEY Keystroke Dynamics Password Database: Benchmark Results. In: Silhavy, R., Senkerik, R., Oplatkova, Z.K., Silhavy, P., Prokopova, Z. (eds) Software Engineering Perspectives and Application in Intelligent Systems. ICTIS CSOC 2017 2016. Advances in Intelligent Systems and Computing, vol 465. Springer, Cham. https://doi.org/10.1007/978-3-319-33622-0_4

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  • DOI: https://doi.org/10.1007/978-3-319-33622-0_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-33620-6

  • Online ISBN: 978-3-319-33622-0

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