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Auflistung nach Schlagwort "Biometric Template Protection"

1 - 4 von 4
  • Konferenzbeitrag
    Application of affine-based reconstruction to retinal point patterns
    (BIOSIG 2020 - Proceedings of the 19th International Conference of the Biometrics Special Interest Group, 2020) Sadeghpour, Mahshid; Arakala, Arathi; Davis, Stephen A.; Horadam, Kathy J.
    Inverse biometrics that exploit the information of biometric references from comparison scores can compromise sensitive personal information of the users in biometric recognition systems. One inverse biometric method that has been very successful in regenerating face images applies an affine transformation to model the face recognition algorithm. This method is general and could apply to templates extracted from other biometric characteristics. This research proposes two formats to apply this method to spatial point patterns extracted from retina images and tests its performance on reconstructing such sparse templates. The results show that the quality of the reconstructed retina point pattern templates is lower than would be accepted by the system as mated.
  • Konferenzbeitrag
    Efficiency Analysis of Post-quantum-secure Face Template Protection Schemes based on Homomorphic Encryption
    (BIOSIG 2020 - Proceedings of the 19th International Conference of the Biometrics Special Interest Group, 2020) Kolberg, Jascha; Drozdowski, Pawel; Gomez-Barrero, Marta; Rathgeb, Christian; Busch, Christoph
    Since biometric characteristics are not revocable and biometric data is sensitive, privacypreserving methods are essential to operate a biometric recognition system. More precisely, the biometric information protection standard ISO/IEC IS 24745 requires that biometric templates are stored and compared in a secure domain. Using homomorphic encryption (HE), we can ensure permanent protection since mathematical operations on the ciphertexts directly correspond to those on the plaintexts. Thus, HE allows to compute the distance between two protected templates in the encrypted domain without a degradation of biometric performance with respect to the corresponding system. In this paper, we benchmark three post-quantum-secure HE schemes, and thereby show that a face verification in the encrypted domain requires only 50 ms transaction time and a template size of 5.5 KB.
  • Konferenzbeitrag
    A Quantum-Resistant Face Template Protection Scheme using Kyber and Saber Public Key Encryption Algorithms
    (BIOSIG 2022, 2022) Roberto Román, Rosario Arjona
    Considered sensitive information by the ISO/IEC 24745, biometric data should be stored and used in a protected way. If not, privacy and security of end-users can be compromised. Also, the advent of quantum computers demands quantum-resistant solutions. This work proposes the use of Kyber and Saber public key encryption (PKE) algorithms together with homomorphic encryption (HE) in a face recognition system. Kyber and Saber, both based on lattice cryptography, were two finalists of the third round of NIST post-quantum cryptography standardization process. After the third round was completed, Kyber was selected as the PKE algorithm to be standardized. Experimental results show that recognition performance of the non-protected face recognition system is preserved with the protection, achieving smaller sizes of protected templates and keys, and shorter execution times than other HE schemes reported in literature that employ lattices. The parameter sets considered achieve security levels of 128, 192 and 256 bits.
  • Textdokument
    xTARP: Improving the Tented Arch Reference Point Detection Algorithm
    (BIOSIG 2017, 2017) Merkle,Johannes; Tams,Benjamin; Dieckmann,Benjamin; Korte,Ulrike
    In 2013, Tams et al. proposed a method to determine directed reference points in fingerprints based on a mathematical model of typical orientation fields of tented arch type fingerprints. Although this Tented Arch Reference Point (TARP) method has been used successfully for prealignment in biometric cryptosystems, its accuracy does not yet ensure satisfactory error rates for single finger systems. In this paper, we improve the TARP algorithm by deploying an improved orientation field computation and by integrating an additional mathematical model for arch type fingerprints. The resulting Extended Tented Arch Reference Point (xTARP) method combines the arch model with the tented arch model and achieves a significantly better accuracy than the original TARP algorithm. When deploying the xTARP method in the Fuzzy Vault construction of Butt et al., the false non-match rate (FNMR) at a security level of 20 bits is reduced from 7:4% to 1:7%.