Abstract
In the application domain of electronic commerce,
biometric authentication can provide one possible solution for
the key management problem. Besides server-based approaches,
methods of deriving digital keys directly from biometric measures
appear to be advantageous. In this paper, we analyze one of our
recently published specific algorithms of this category based on
behavioral biometrics of handwriting, the biometric hash. Our
interest is to investigate to which degree each of the underlying
feature parameters contributes to the overall intrapersonal
stability and interpersonal value space. We will briefly discuss
related work in feature evaluation and introduce a new
methodology based on three components: the intrapersonal scatter
(deviation), the interpersonal entropy, and the correlation
between both measures. Evaluation of the technique is presented
based on two data sets of different size. The method presented
will allow determination of effects of parameterization of the
biometric system, estimation of value space boundaries, and
comparison with other feature selection approaches.