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Keystroke Data Classification for Computer User Profiling and Verification

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Computational Collective Intelligence

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9330))

Abstract

The article addresses the issues of behavioral biometrics. Presented research concerns an analysis of a user activity related to a keyboard use in a computer system. A method of computer user profiling based on encrypted keystrokes is introduced to ensure a high level of users data protection. User’s continuous work in a computer system is analyzed. This type of analysis constitutes a type of free-text analysis. Additionally, an attempt to user verification in order to detect intruders is performed. Intrusion detection is based on a modified k-NN classifier and different distance measures.

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Authors and Affiliations

  1. Institute of Computer Science, University of Silesia, Bedzinska 39, 41-200, Sosnowiec, Poland

    Tomasz Emanuel Wesołowski & Piotr Porwik

Authors
  1. Tomasz Emanuel Wesołowski
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  2. Piotr Porwik
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Corresponding author

Correspondence to Tomasz Emanuel Wesołowski .

Editor information

Editors and Affiliations

  1. Universidad Complutense de Madrid, Madrid, Spain

    Manuel Núñez

  2. Wroclaw University of Technology, Wroclaw, Poland

    Ngoc Thanh Nguyen

  3. Computer Science Department, Universidad Autónoma De Madrid, Madrid, Spain

    David Camacho

  4. Wroclaw University of Technology, Wroclaw, Poland

    Bogdan Trawiński

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Wesołowski, T.E., Porwik, P. (2015). Keystroke Data Classification for Computer User Profiling and Verification. In: Núñez, M., Nguyen, N., Camacho, D., Trawiński, B. (eds) Computational Collective Intelligence. Lecture Notes in Computer Science(), vol 9330. Springer, Cham. https://doi.org/10.1007/978-3-319-24306-1_57

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  • DOI: https://doi.org/10.1007/978-3-319-24306-1_57

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-24305-4

  • Online ISBN: 978-3-319-24306-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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