Neural Network in Keystroke Dynamics in Biometric Authentication System

Abstract

Abstract: In the proposed approach writing speed can be improved by low over head techniques for screening key designs. It is fast and different ways are used to integrate to existing conventions. A more expensive scope of client is allowed to test for equivalent overhead. Proposed method potential predispositions are responsible, so they can be measured and balanced. The comparator has been used a existing standard layout. Mapping both layouts can eliminate differing familiarity and finger memory bias. Delineate it with two cell phone keypad formats: Sam-sung's variation of the basic ABC design, and another client particular design (PM). We rehash an examination beforehand attempted by a preparation based technique, which utilized 10 members, and evaluated a 54% speedup for PM (SD=35%). The new strategy utilized 116 members and assessed a 19.5% speedup (SD=7.5%). Wide confidence interval of the training-based methods, differences in test corpuses, and the inherent conservatism of the new method which is used to explain the Differences in speedup estimates. As a result of large test group the effects of user uniqueness tested significantly. There is no obvious effect on any of the measures. ABC and PM performance were significantly related age and keypad experience. Age and Keypad experience does not affect the relative speed. A different experience level of comparison bias has been removed by proposed approach. Keywords: ABC design, PM performance, Neural Network