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

  • Abdullah AlshehriEmail author
  • Frans Coenen
  • Danushka Bollegala
Conference paper
Part of the Communications in Computer and Information Science book series (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.

Keywords

Biometrics Continuous authentication Keystroke dynamics Keystroke time series 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Abdullah Alshehri
    • 1
    Email author
  • Frans Coenen
    • 2
  • Danushka Bollegala
    • 2
  1. 1.Department of Information TechnologyAlbaha UniversityAlbahaSaudi Arabia
  2. 2.Department of Computer ScienceUniversity of LiverpoolLiverpoolUK

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