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IFIP International Conference on Communications and Multimedia Security

CMS 2012: Communications and Multimedia Security pp 16–25Cite as

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Feature Selection on Handwriting Biometrics: Security Aspects of Artificial Forgeries

Feature Selection on Handwriting Biometrics: Security Aspects of Artificial Forgeries

  • Karl Kümmel18,19,
  • Tobias Scheidat18,19,
  • Claus Vielhauer18 &
  • …
  • Jana Dittmann19 
  • Conference paper
  • 992 Accesses

Part of the Lecture Notes in Computer Science book series (LNSC,volume 7394)

Abstract

A lot of improvements were introduced lately in order to increase the verification performance of biometric user authentication systems. One method, besides many others, is the selection of specific features for each user during the verification process. In this paper we present a security analysis of a user specific bit mask vector, which was originally introduced to improve verification performance on a Biometric Hash algorithm for dynamic handwriting. Therefore, we use a reverse engineering attack method to generate artificial handwriting data and calculate error rates to examine the impact on the verification performance. Our goal is to study the effect of a feature selection by a mask vector on artificial data in comparison to genuine handwriting data. Our first experimental results show an average decrease of the equal error rate, generate by the artificial data, by approx. 64%. In comparison, equal error rates of random attacks, using verification data of another user, decreases by an average of approx. 27%.

Keywords

  • Biometrics
  • dynamic handwriting
  • feature selection
  • security analysis
  • reverse engineering

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Author information

Authors and Affiliations

  1. Brandenburg University of Applied Sciences, Germany

    Karl Kümmel, Tobias Scheidat & Claus Vielhauer

  2. Otto-von-Guericke University Magdeburg, Germany

    Karl Kümmel, Tobias Scheidat & Jana Dittmann

Authors
  1. Karl Kümmel
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  2. Tobias Scheidat
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  3. Claus Vielhauer
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  4. Jana Dittmann
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Editor information

Editors and Affiliations

  1. Department of Computer Science, IBBT-DistriNet, K.U. Leuven, Celestijnenlaan 200A, 3001, Leuven, Belgium

    Bart De Decker

  2. School of Computing, University of Kent, CT2 7NZ, Canterbury, Kent, UK

    David W. Chadwick

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© 2012 IFIP International Federation for Information Processing

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Cite this paper

Kümmel, K., Scheidat, T., Vielhauer, C., Dittmann, J. (2012). Feature Selection on Handwriting Biometrics: Security Aspects of Artificial Forgeries. In: De Decker, B., Chadwick, D.W. (eds) Communications and Multimedia Security. CMS 2012. Lecture Notes in Computer Science, vol 7394. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32805-3_2

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  • DOI: https://doi.org/10.1007/978-3-642-32805-3_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32804-6

  • Online ISBN: 978-3-642-32805-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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