Towards Keystroke Continuous Authentication Using Time Series Analytics

Alshehri, Abdullah, Coenen, Frans ORCID: 0000-0003-1026-6649 and Bollegala, Danushka ORCID: 0000-0003-4476-7003 (2016) Towards Keystroke Continuous Authentication Using Time Series Analytics In: Artificial Intelligence 2016, 2016-9-12 - 2016-12-14, Cambridge.

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Abstract

An approach to Keystroke Continuous Authentication (KCA) is described founded on a time series analysis based approach that, unlike previous work on KCA (using feature vector representations), takes the sequencing of keystrokes into consideration. The significance of KCA is in the context of online assessments and examinations used in eLearning environments and MOOCs, which are becoming increasingly popular. The process is fully described and analysed, including comparison with established feature vector approaches. Our proposed method outperforms these other approaches to KCA (with a detection accuracy of 94 %, compared to 79.53 %), a clear indicator that the proposed time series analysis based KCA has significant potential.

Item Type:	Conference Item (Unspecified)
Uncontrolled Keywords:	4605 Data Management and Data Science, 46 Information and Computing Sciences
Depositing User:	Symplectic Admin
Date Deposited:	27 Oct 2016 16:02
Last Modified:	23 May 2026 00:11
DOI:	10.1007/978-3-319-47175-4_24
Related Websites:	Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3003963
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