Spectral Keyboard Streams: Towards Effective and Continuous Authentication

Coenen, FP ORCID: 0000-0003-1026-6649, alshehri, ORCID: 0000-0003-0008-9394 and bollegala, ORCID: 0000-0003-4476-7003 (2017) Spectral Keyboard Streams: Towards Effective and Continuous Authentication. In: 2017 IEEE International Conference on Data Mining Workshops (ICDMW), 2017-11-18 - 2017-11-21.

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Abstract

In this paper, an innovative approach to keyboard user monitoring (authentication), using keyboard dynamics and founded on the concept of time series analysis, is presented. The work is motivated by the need for robust authentication mechanisms in the context of on-line assessment such as those featured in many online learning platforms. Four analysis mechanisms are considered: analysis of keystroke time series in their raw form (without any translation), analysis consequent to translating the time series into a more compact form using either the Discrete Fourier Transform or the Discrete Wavelet Transform, and a 'benchmark' feature vector representation of the form typically used in previous related work. All four mechanisms are fully described and evaluated. A best authentication accuracy of 99% was obtained using the wavelet transform.

Item Type:	Conference or Workshop Item (Unspecified)
Uncontrolled Keywords:	Behavioral Biometric, Continuous Authentication, Keystroke Dynamics, Keystroke Streams
Depositing User:	Symplectic Admin
Date Deposited:	13 Sep 2017 07:21
Last Modified:	19 Jan 2023 06:54
DOI:	10.1109/ICDMW.2017.38
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3009433