Authenticating the identity of computer users with typing biometrics and the fuzzy min-max neural network

Quteishat, Anas, Lim, Chee Peng, Loy, Chen Change and Lai, Weng Kin 2009, Authenticating the identity of computer users with typing biometrics and the fuzzy min-max neural network, International journal of biomedical soft computing and human sciences, vol. 14, no. 1, pp. 47-53.

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Title Authenticating the identity of computer users with typing biometrics and the fuzzy min-max neural network
Author(s) Quteishat, Anas
Lim, Chee Peng
Loy, Chen Change
Lai, Weng Kin
Journal name International journal of biomedical soft computing and human sciences
Volume number 14
Issue number 1
Start page 47
End page 53
Total pages 7
Publisher Baiomedikaru Faji Shisutemu Kenkyukai
Place of publication Fukuoka, Japan
Publication date 2009
ISSN 1345-1529
Keyword(s) typing biometrics
the fuzzy min-max neural network
keystroke pressure
keystroke latency
computer systems security
Summary In this paper, typing biometrics is applied as an additional security measure to the password-based or Personal Identification Number (PIN)-based systems to authenticate the identity of computer users. In particular, keystroke pressure and latency signals are analyzed using the Fuzzy Min-Max (FMM) neural network for authentication purposes. A special pressure-sensitive keyboard is designed to collect keystroke pressure signals, in addition to the latency signals, from computer users when they type their passwords. Based on the keystroke pressure and latency signals, the FMM network is employed to classify the computer users into two categories, i.e., genuine users or impostors. To assess the effectiveness of the proposed approach, two sets of experiments are conducted, and the results are compared with those from statistical methods and neural network models. The experimental outcomes positively demonstrate the potentials of using typing biometrics and the FMM network to provide an additional security layer for the current password-based or PIN-based methods in authenticating the identity of computer users.
Language eng
Field of Research 089999 Information and Computing Sciences not elsewhere classified
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category C1.1 Refereed article in a scholarly journal
Persistent URL http://hdl.handle.net/10536/DRO/DU:30048761

Document type: Journal Article
Collection: Institute for Frontier Materials
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