User adaptive fuzzy commitment for signature template

Emanuele Maiorana; Patrizio Campisi; Alessandro Neri

doi:10.1117/1.2885239

1 January 2008 User adaptive fuzzy commitment for signature template protection and renewability

Emanuele Maiorana, Patrizio Campisi, Alessandro Neri

Author Affiliations +

Journal of Electronic Imaging, Vol. 17, Issue 1, 011011 (January 2008). https://doi.org/10.1117/1.2885239

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.

©(2008) Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation Download Citation

Emanuele Maiorana, Patrizio Campisi, and Alessandro Neri "User adaptive fuzzy commitment for signature template protection and renewability," Journal of Electronic Imaging 17(1), 011011 (1 January 2008). https://doi.org/10.1117/1.2885239

Published: 1 January 2008

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available