Intelligent keystroke pressure-based typing biometrics authentication system using radial basis function network
Security of an information system depends to a large extent on its ability to authenticate legitimate users as well as to withstand attacks of various kinds. Confidence in its ability to provide adequate authentication is, however, waning. This is largely due to the wrongful use of passwords by...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2009
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/8042/ http://irep.iium.edu.my/8042/ http://irep.iium.edu.my/8042/1/Intelligent_keystroke_pressure-based_typing_biometrics_authentication_system_using_radial_basis_function_network.pdf |
| Summary: | Security of an information system depends to a
large extent on its ability to authenticate legitimate users as well
as to withstand attacks of various kinds. Confidence in its ability
to provide adequate authentication is, however, waning. This is
largely due to the wrongful use of passwords by many users. In
this paper, the design and development of keystroke pressurebased
typing biometrics for individual user's verification which
based on the analysis of habitual typing of individuals is
discussed. The combination of maximum pressure exerted on the
keyboard and time latency between keystrokes is used as features
to create typing patterns for individual users so as to recognize
authentic users and to reject impostors. Radial basis function
network (RBFN), which is one of the artificial neural network, is
used as a pattern matching method. The effectiveness of the
proposed system is evaluated based upon False Reject Rate
and False Accept Rate A series of experiment
shows that the proposed system is effective for biometric-based
security system. |
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