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Paper Abstract
Biometrics is rapidly becoming the principal technology
for automatic people authentication. The main advantage in using
biometrics over traditional recognition approaches relies in the difficulty
of losing, stealing, or copying individual behavioral or physical
traits. The major weakness of biometrics-based systems relies in
their security: in order to avoid data stealing or corruption, storing
raw biometric data is not advised. The same problem occurs when
biometric templates are employed, since they can be used to recover
the original biometric data. We employ cryptographic techniques
to protect dynamic signature features, making it impossible
to derive the original biometrics from the stored templates, while
maintaining good recognition performances. Together with protection,
we also guarantee template cancellability and renewability.
Moreover, the proposed authentication scheme is tailored to the signature
variability of each user, thus obtaining a user adaptive system
with enhanced performances with respect to a nonadaptive
one. Experimental results show the effectiveness of our approach
when compared to both traditional nonsecure classifiers and other,
already proposed protection schemes.
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