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Auflistung nach Autor:in "Tams, Benjamin"

1 - 5 von 5
  • Konferenzbeitrag
    Absolute fingerprint pre-alignment in minutiae-based cryptosystems
    (BIOSIG 2013, 2013) Tams, Benjamin
    Most biometric cryptosystems that have been proposed to protect fingerprint minutiae make use of public alignment helper data. This, however, has the inadvertent effect of information leakage about the protected templates. A countermeasure to avoid auxiliary alignment data is to protect absolutely pre-aligned fingerprints. As a proof of concept, we run performance evaluations of a minutiae fuzzy vault with an automatic method for absolute pre-alignment. Therefore, we propose a new method for estimating a fingerprint's directed reference point by modeling the local orientation around the core as a tented arch.1
  • Konferenzbeitrag
    Fusion of Face Demorphing and Deep Face Representations for Differential Morphing Attack Detection
    (BIOSIG 2022, 2022) Shiqerukaj, Elidona; Rathgeb, Christian; Merkle, Johannes; Drozdowski, Pawel; Tams, Benjamin
    Algorithm fusion is frequently employed to improve the accuracy of pattern recognition tasks. This particularly applies to biometrics including attack detection mechanisms. In this work, we apply a fusion of two differential morphing attack detection methods, i.e. Demorphing and Deep Face Representations. Experiments are performed in a cross-database scenario using high-quality face morphs along with realistic live captures. Obtained results reveal that a weighted sum-based score-level fusion of Demorphing and Deep Face Representations improves the morphing attack detection accuracy. With the proposed fusion, a detection equal error rate of 4.9% is achieved, compared to detection equal error rates of 5.6% and 5.8% of the best individual morphing attack detection methods, respectively.
  • Konferenzbeitrag
    The fuzzy vault for fingerprints is vulnerable to brute force attack
    (BIOSIG 2009: biometrics and electronic signatures, 2009) Mihǎilescu, Preda; Munk, Axel; Tams, Benjamin
    The fuzzy vault approach is one of the best studied and well accepted ideas for binding cryptographic security into biometric authentication. We present in this paper a brute force attack which improves on the one described by T. Charles Clancy et. al. in 2003 in an implementation of the vault for fingerprints. Based on this attack, we show that three implementations of the fingerprint vault are vulnerable and show that the vulnerability cannot be avoided by mere parameter selection in the actual frame of the protocol. We will report about our experiences with an implementation of such an attack. We also give several suggestions which can improve the fingerprint vault to become a cryptographically secure algorithm. In particular, we introduce the idea of fuzzy vault with quiz which draws upon information resources unused by the current version of the vault. This may bring important security improvements and can be adapted to the other biometric applications of the vault.
  • Konferenzbeitrag
    Improved fuzzy vault scheme for alignment-free fingerprint features
    (BIOSIG 2015, 2015) Tams, Benjamin; Merkle, Johannes; Rathgeb, Christian; Wagner, Johannes; Korte, Ulrike; Busch, Christoph
    The fuzzy vault scheme is one of the most prominent tools for protecting fingerprint templates, typically being minutiae-based. However, there exist two major problems. Firstly, the fuzzy vault scheme is vulnerable to attacks correlating different templates of the same user. Secondly, auxiliary alignment data may leak information about the protected fingerprints which negatively affects security and privacy. In this paper, we tackle both problems. Our implementation uses alignment-free fingerprint features and fusions thereof, thereby removing the need to store alignment parameters. Furthermore, the features are passed through a quantization scheme and then dispersed in a maximal number of chaff, thereby thwarting correlation attacks.
  • Konferenzbeitrag
    Simulation of Print-Scan Transformations for Face Images based on Conditional Adversarial Networks
    (BIOSIG 2020 - Proceedings of the 19th International Conference of the Biometrics Special Interest Group, 2020) Mitkovski, Aleksandar; Merkle, Johannes; Rathgeb, Christian; Tams, Benjamin; Bernardo, Kevin; Haryanto, Nathania E.; Busch, Christoph
    In many countries, printing and scanning of face images is frequently performed as part of the issuance process of electronic travel documents, e.g., ePassports. Image alterations induced by such print-scan transformations may negatively effect the performance of various biometric subsystems, in particular image manipulation detection. Consequently, according training data is needed in order to achieve robustness towards said transformations. However, manual printing and scanning is time-consuming and costly. In this work, we propose a simulation of print-scan transformations for face images based on a Conditional Generative Adversarial Network (cGAN). To this end, subsets of two public face databases are manually printed and scanned using different printer-scanner combinations. A cGAN is then trained to perform an image-to-image translation which simulates the corresponding print-scan transformations. The goodness of simulation is evaluated with respect to image quality, biometric sample quality and performance, as well as human assessment.