IET Biometrics (Jan 2023)

An empirical analysis of keystroke dynamics in passwords: A longitudinal study

  • Simon Parkinson,
  • Saad Khan,
  • Alexandru‐Mihai Badea,
  • Andrew Crampton,
  • Na Liu,
  • Qing Xu

DOI
https://doi.org/10.1049/bme2.12087
Journal volume & issue
Vol. 12, no. 1
pp. 25 – 37

Abstract

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Abstract The use of keystroke timings as a behavioural biometric in fixed‐text authentication mechanisms has been extensively studied. Previous research has investigated in isolation the effect of password length, character substitution, and participant repetition. These studies have used publicly available datasets, containing a small number of passwords with timings acquired from different experiments. Multiple experiments have also used the participant's first and last name as the password; however, this is not realistic of a password system. Not only is the user's name considered a weak password, but their familiarity with typing the phrase minimises variation in acquired samples as they become more familiar with the new password. Furthermore, no study has considered the combined impact of length, substitution, and repetition using the same participant pool. This is explored in this work, where the authors collected timings for 65 participants, when typing 40 passwords with varying characteristics, 4 times per week for 8 weeks. A total of 81,920 timing samples were processed using an instance‐based distance and threshold matching approach. Results of this study provide empirical insight into how a password policy should be created to maximise the accuracy of the biometric system when considering substitution type and longitudinal effects.