Dynamic keystroke analysis using AR model
The design and development of a pressure sensor based typing biometrics authentication system (BAS) is discussed in this paper. The dynamic keystroke, represented by its time duration and force generates a waveform, which when concatenated results in a user’s typing pattern for the typed passw...
| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2004
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/6951/ http://irep.iium.edu.my/6951/1/Dynamic_Keystroke_Analysis_Using_AR_Model.pdf |
| Summary: | The design and development of a pressure
sensor based typing biometrics authentication system
(BAS) is discussed in this paper. The dynamic
keystroke, represented by its time duration and force
generates a waveform, which when concatenated
results in a user’s typing pattern for the typed
password. The design of the BAS is in two stages,
whereby the hardware comprising the pressure sensor
and the associated data acquisition system (DAS) is
first implemented. The system DAS has been designed
using LabVIEW software. Furthermore several data
preprocessing techniques have been used to improve
the quality of the acquired waveforms. The second
stage involves a classifier to authenticate the users. This
paper discusses a new data classifier technique based
on Autoregressive signal modeling (AR), which has
been developed so as to correctly identify and
authenticate the users of the system. Some experiments
have been conducted to show the validity of the overall
BAS performance. The results obtained have shown
that this proposed system is reliable with many
potential applications for computer security. |
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