Auflistung nach Autor:in "Kevenaar, Tom"
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- KonferenzbeitragMulti-modal and multi-instance fusion for biometric cryptosystems(BIOSIG 2012, 2012) Merkle, Johannes; Kevenaar, Tom; Korte, UlrikeBiometric cryptosystems allow cryptographic privacy protection for biometric reference data without storing a secret key. However, their security is inherently limited by the discriminative information content of the biometric feature data. Given the currently exploitable entropy of biometric features, one of the most promising approaches to achieve high privacy levels is to combine several biometric modalities or several instances of the same biometric modality. In this contribution, we theoretically analyze multibiometric fusion strategies for biometric cryptosystems with respect to their impact on security and recognition accuracy. We also introduce hash level as a new fusion level. Furthermore, we give a more detailed analysis for the most prominent schemes, the Fuzzy Commitment Scheme and the Fuzzy Vault.
- KonferenzbeitragPrivacy Enhancing Technology for a 3D-Face Recognition System(BIOSIG 2007: biometrics and electronic signatures, 2007) Zhou, Xuebing; Kevenaar, Tom; Kelkboom, Emile; Busch, Christoph; Veen, Michiel van der; Nouak, Alexander2D Face images are traditionally used in civil governmental applications. An extension from 2D to 3D images will lead to several advantages when setting up automated authentication systems. However, privacy concerns of storing face images on smart cards or in databases will inhibit the acceptance of such systems. In this paper we concentrate on privacy enhancing technologies for biometric information where we focus on 3D face images. The feature vectors are obtained using a histogram-based approach and the privacy protected templates are generated based on fuzzy extractors. It is shown that the private face recognition system has an acceptable verification per- formance. Finally, it is described how the proposed system can be used in the setting of an ePassport.
- KonferenzbeitragA reference framework for the privacy assessment of keyless biometric template protection systems(BIOSIG 2010: Biometrics and Electronic Signatures. Proceedings of the Special Interest Group on Biometrics and Electronic Signatures, 2010) Kevenaar, Tom; Korte, Ulrike; Merkle, Johannes; Niesing, Matthias; Ihmor, Heinrich; Busch, Christoph; Zhou, XuebingOver the past decades, a number of methods have been reported in the scientific literature to protect the privacy of biometric information stored in biometric systems. Keyless Biometric Template Protection (KBTP) methods aim to protect biometric information without the use of long-term secrets by deploying one-way functions. These KBTP methods are currently developed to an extent that commercial products have become available. When assessing and comparing different KBTP methods it is important to have a common and generic approach. Therefore, in this paper we present a reference framework that can be used in assessing and comparing the privacy properties of KBTP systems.