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Pattern Password Authentication Based on Touching Location

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Intelligent Data Engineering and Automated Learning – IDEAL 2015 (IDEAL 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9375))

Abstract

Pattern passwords are one of the embedded authentication method of touchscreen devices, however it has some major drawbacks which briefly are identifiability and imitability. The password of the user is noticeable when entering the pattern due to shining circles. Therefore, what we put forward in this paper is a novel biometric implementation of a hidden system to pattern password authentication for increasing password security. As opposed to general research concept which extracts touch or keystroke durations, we focused on the touching coordinates calculated the distance of the line between the constant pattern node and the touched place as well as the angle. Using these inputs, we trained the neural network by Gauss-Newton and Levenberg-Marquardt algorithms and conducted the experiments with these trained classifiers.

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Acknowledgment

This work and the contribution were supported by project “SP/2014/05 - Smart Solutions for Ubiquitous Computing Environments” from University of Hradec Kralove, Faculty of Informatics and Management.

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Authors and Affiliations

  1. Faculty of Informatics and Management, Center for Basic and Applied Research, University of Hradec Kralove, Rokitanskeho 62, 500 03, Hradec Kralove, Czech Republic

    Orcan Alpar & Ondrej Krejcar

Authors
  1. Orcan Alpar
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  2. Ondrej Krejcar
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Corresponding author

Correspondence to Ondrej Krejcar .

Editor information

Editors and Affiliations

  1. Wroclaw University of Technology, Wroclaw, Poland

    Konrad Jackowski

  2. Department of Systems, Wroclaw University of Technology, Wroclaw, Poland

    Robert Burduk

  3. Wroclaw Univ of Tech, Wroclaw, Poland

    Krzysztof Walkowiak

  4. Wroclaw University of Technology, Faculty of Electronics, Wroclaw, Poland

    Michal Wozniak

  5. School of Electrical & Electronic E, University of Manchester, Manchester, United Kingdom

    Hujun Yin

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Alpar, O., Krejcar, O. (2015). Pattern Password Authentication Based on Touching Location. In: Jackowski, K., Burduk, R., Walkowiak, K., Wozniak, M., Yin, H. (eds) Intelligent Data Engineering and Automated Learning – IDEAL 2015. IDEAL 2015. Lecture Notes in Computer Science(), vol 9375. Springer, Cham. https://doi.org/10.1007/978-3-319-24834-9_46

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  • DOI: https://doi.org/10.1007/978-3-319-24834-9_46

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-24833-2

  • Online ISBN: 978-3-319-24834-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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