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Non-conventional keystroke dynamics for user authentication

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Alsultan, A., Warwick, K. and Wei, H. (2017) Non-conventional keystroke dynamics for user authentication. Pattern Recognition Letters, 89 (1). pp. 53-59. ISSN 0167-8655

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To link to this item DOI: 10.1016/j.patrec.2017.02.010

Abstract/Summary

This paper introduces an approach for user authentication using free-text keystroke dynamics which incorporates the use of non-conventional keystroke features. Semi-timing features along with editing features are extracted from the user’s typing stream. Decision trees were exploited to classify each of the user’s data. In parallel for comparison, support vector machines (SVMs) were also used for classification in association with an ant colony optimization (ACO) feature selection technique. The results obtained from this study are encouraging as low false accept rates (FAR) and false reject rates (FRR) were achieved in the experimentation phase. This signifies that satisfactory overall system performance was achieved by using the typing attributes in the proposed approach. Thus, the use of non-conventional typing features improves the understanding of human typing behavior and therefore, provides significant contribution to the authentication system.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Science > School of Mathematical, Physical and Computational Sciences > Department of Computer Science
ID Code:69210
Publisher:Elsevier

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