Abstract
ABSTRACTIn this paper, we propose a novel approach termed as fingerprint dynamics, targeted for multi-instance authentication system. Inspired by the concept of keystroke dynamics, the technique analyses the behavioural characteristics associated with multi-instance fingerprint acquisition. To capture the user data, an acquisition set-up (hardware) is devised. Data-set of genuine users and imposters are created using time-derived information, collected for unique fixed length sequences by 32 volunteers. Systematic evaluation of features and feature subset selection is performed. Goal of this paper is to determine potential of fingerprint dynamics and establish it as a successful biometric trait for the purpose of robust user authentication. The technique can be implemented as a part of multifactor authentication system or standalone alternative. Statistical analysis of classifier outputs for different kernels, by performing classification cross validation, and assessment of verification accuracies confirms the discriminating capability of proposed technique.
Published Version
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