Auflistung nach Autor:in "Kolberg, Jascha"
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- KonferenzbeitragEfficiency 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, ChristophSince 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.
- KonferenzbeitragFingerprint Presentation Attack Detection using Laser Speckle Contrast Imaging(BIOSIG 2018 - Proceedings of the 17th International Conference of the Biometrics Special Interest Group, 2018) Keilbach, Pascal; Kolberg, Jascha; Gomez-Barrero, Marta; Busch, Christoph; Langweg, HannoWith the increased deployment of biometric authentication systems, some security concerns have also arisen. In particular, presentation attacks directed to the capture device pose a severe threat. In order to prevent them, liveness features such as the blood flow can be utilised to develop presentation attack detection (PAD) mechanisms. In this context, laser speckle contrast imaging (LSCI) is a technology widely used in biomedical applications in order to visualise blood flow. We therefore propose a fingerprint PAD method based on textural information extracted from preprocessed LSCI images. Subsequently, a support vector machine is used for classification. In the experiments conducted on a database comprising 32 different artefacts, the results show that the proposed approach classifies correctly all bona fides. However, the LSCI technology experiences difficulties with thin and transparent overlay attacks.
- KonferenzbeitragMulti-algorithm Benchmark for Fingerprint Presentation Attack Detection with Laser Speckle Contrast Imaging(BIOSIG 2019 - Proceedings of the 18th International Conference of the Biometrics Special Interest Group, 2019) Kolberg, Jascha; Gomez-Barrero, Marta; Busch, ChristophThe increased usage of biometric authentication systems has raised concerns regarding the security of components in a biometric system. As a consequence, preventing security issues related to presentation attacks targeting the biometric capture device are of utmost importance. To develop presentation attack detection (PAD) mechanisms, features confirming the liveness of the biometric characteristic such as the blood flow within the finger are needed. Utilising laser speckle contrast imaging (LSCI) to observe blood movement below the surface, we present an evaluation of different machine learning classifiers for fingerprint PAD. The experiments over a database comprising 35 different presentation attack instrument (PAI) species show that the detection performance varies depending on the utilised feature extraction method. A majority voting of selected classifiers and features achieves an APCER of 9% for a convenient BPCER of 0.05%.
- AbstractPost-Quantum Secure Two-Party Computation for Iris Biometric Template Protection(crypto day matters 33, 2021) Bauspieß, Pia; Kolberg, Jascha; Demmler, Daniel; Krämer, Juliane; Busch, Christoph
- KonferenzbeitragSicherheit und Datenschutz für Biometrische Systeme(D22, 2022) Kolberg, JaschaBiometrische Authetisierungsverfahren werden heutzutage für benutzerfreundliche Entsperrungen von mobilen Endgeräten sowie für sicherheitskritische Identifizierungsverfahren bei der Grenzkontrolle eingesetzt. Allerdings steigt auch die Anzahl der Angriffe auf biometrische Systeme mit deren Verbreitung. Daher erfordert die Bereitstellung biometrischer Systeme weiterreichende Maßnahmen um den Datenschutz gewährleisten und Missbrauch verhindern zu können. In diesem Zusammenhang werden in dieser Dissertation kryptographische Lösungen untersucht, um biometrische Daten sicher zu speichern und zudem im verschlüsselten Raum zu vergleichen. Um dabei langfristigen Schutz zu garantieren, werden ausschließlich Verfahren genutzt, die selbst zukünftigen Quantencomputern standhalten. Neben den Datenschutzbedenken wird die Sicherheit biometrischer Systeme durch Präsentationsangriffe während der Aufnahme gefährdet. Daher sind Verfahren zur Präsentationsangriff Detektierung (PAD) erforderlich um zwischen bona fiden Aufnahmen und Angriffen unterscheiden zu können. Zu diesem Zweck werden in dieser Dissertation verschiedene PAD Methoden für Fingerabdrucksysteme entwickelt und evaluiert.
- KonferenzbeitragTowards Fingerprint Presentation Attack Detection Based on Convolutional Neural Networks and Short Wave Infrared Imaging(BIOSIG 2018 - Proceedings of the 17th International Conference of the Biometrics Special Interest Group, 2018) Tolosana, Ruben; Gomez-Barrero, Marta; Kolberg, Jascha; Morales, Aythami; Busch, Christoph; Ortega-Garcia, JavierBiometric recognition offers many advantages over traditional authentication methods, but they are also vulnerable to, for instance, presentation attacks. These refer to the presentation of artifacts, such as facial pictures or gummy fingers, to the biometric capture device, with the aim of impersonating another person or to avoid being recognised. As such, they challenge the security of biometric systems and must be prevented. In this paper, we present a new fingerprint presentation attack detection method based on convolutional neural networks and multi-spectral images extracted from the finger in the short wave infrared spectrum. The experimental evaluation, carried out on an initial small database but comprising different materials for the fabrication of the artifacts and including unknown attacks for testing, shows promising results: all samples were correctly classified.