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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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