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Behavioural Biometric Continuous User Authentication Using Multivariate Keystroke Streams in the Spectral Domain

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Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 976))

Abstract

Continuous authentication is significant with respect to many online applications where it is desirable to monitor a user’s identity throughout an entire session; not just at the beginning of the session. One example application domain, where this is a requirement, is in relation to Massive Open Online Courses (MOOCs) when users wish to obtain some kind of certification as evidence that they have successfully competed a course. Such continuous authentication can best be realised using some forms of biometric checking; traditional user credential checking methods, for example username and password checking, only provide for “entry” authentication. In this paper, we introduce a novel method for the continuous authentication of computer users founded on keystroke dynamics (keyboard behaviour patterns); a form of behavioural biometric. The proposed method conceptualises keyboard dynamics in terms of a Multivariate-Keystroke Time Series which in turn can be transformed into the spectral domain. The time series can then be monitored dynamically for typing patterns that are indicative of a claimed user. Two transforms are considered, the Discrete Fourier Transform and the Discrete Wavelet Transform. The proposed method is fully described and evaluated, in the context of impersonation detection, using real keystroke datasets. The reported results indicate that the proposed time series mechanism produced an excellent performance, outperforming the comparator approaches by a significant margin.

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Author information

Authors and Affiliations

  1. Department of Information Technology, Albaha University, Albaha, Saudi Arabia

    Abdullah Alshehri

  2. Department of Computer Science, University of Liverpool, Liverpool, UK

    Frans Coenen & Danushka Bollegala

Authors
  1. Abdullah Alshehri
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  2. Frans Coenen
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  3. Danushka Bollegala
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Corresponding author

Correspondence to Abdullah Alshehri .

Editor information

Editors and Affiliations

  1. Instituto de Telecomunicações, Lisbon, Portugal

    Ana Fred

  2. University of Madeira, Funchal, Portugal

    David Aveiro

  3. Delft University of Technology, Delft, The Netherlands

    Jan L. G. Dietz

  4. Henley Business School, University of Reading, Reading, UK

    Kecheng Liu

  5. University of Coimbra, Coimbra, Portugal

    Jorge Bernardino

  6. Federal University of Pernambuco, Recife, Brazil

    Ana Salgado

  7. INSTICC and Instituto Politecnico de Setúbal, Setúbal, Portugal

    Joaquim Filipe

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Alshehri, A., Coenen, F., Bollegala, D. (2019). Behavioural Biometric Continuous User Authentication Using Multivariate Keystroke Streams in the Spectral Domain. In: Fred, A., et al. Knowledge Discovery, Knowledge Engineering and Knowledge Management. IC3K 2017. Communications in Computer and Information Science, vol 976. Springer, Cham. https://doi.org/10.1007/978-3-030-15640-4_3

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  • DOI: https://doi.org/10.1007/978-3-030-15640-4_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-15639-8

  • Online ISBN: 978-3-030-15640-4

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