Pseudo Identities Based on Fingerprint Characteristics

This paper presents the integrated project TURBINE which is funded under the EU 7th research framework programme. This research is a multi-disciplinary effort on privacy enhancing technology, combining innovative developments in cryptography and fingerprint recognition. The objective of this project is to provide a breakthrough in electronic authentication for various applications in the physical world and on the Internet. On the one hand it will provide secure identity verification thanks to fingerprint recognition. On the other hand it will reliably protect the biometric data through advanced cryptography technology. In concrete terms, it will provide the assurance that (i) the data used for the authentication, generated from the fingerprint, cannot be used to restore the original fingerprint sample, (ii) the individual will be able to create different "pseudo-identities" for different applications with the same fingerprint, whilst ensuring that these different identities (and hence the related personal data) cannot be linked to each other, and (iii) the individual is enabled to revoke an biometric identifier (pseudo-identity) for a given application in case it should not be used anymore

Analysis of Biometric Authentication Protocols in the Blackbox Model

In this paper we analyze different biometric authentication protocols considering an internal adversary. Our contribution takes place at two levels. On the one hand, we introduce a new comprehensive framework that encompasses the various schemes we want to look at. On the other hand, we exhibit actual attacks on recent schemes such as those introduced at ACISP 2007, ACISP 2008, and SPIE 2010, and some others. We follow a blackbox approach in which we consider components that perform operations on the biometric data they contain and where only the input/output behavior of these components is analyzed.Comment: 10 pages, 1 figures, submitted to IEEE Transactions on Information Forensics and Securit

Template Protection For 3D Face Recognition

The human face is one of the most important biometric modalities for automatic authentication. Three-dimensional face recognition exploits facial surface information. In comparison to illumination based 2D face recognition, it has good robustness and high fake resistance, so that it can be used in high security areas. Nevertheless, as in other common biometric systems, potential risks of identity theft, cross matching and exposure of privacy information threaten the security of the authentication system as well as the user\\u27s privacy. As a crucial supplementary of biometrics, the template protection technique can prevent security leakages and protect privacy. In this chapter, we show security leakages in common biometric systems and give a detailed introduction on template protection techniques. Then the latest results of template protection techniques in 3D face recognition systems are presented. The recognition performances as well as the security gains are analyzed

Binary Biometrics: An Analytic Framework to Estimate the Performance Curves Under Gaussian Assumption

In recent years, the protection of biometric data has gained increased interest from the scientific community. Methods such as the fuzzy commitment scheme, helper-data system, fuzzy extractors, fuzzy vault, and cancelable biometrics have been proposed for protecting biometric data. Most of these methods use cryptographic primitives or error-correcting codes (ECCs) and use a binary representation of the real-valued biometric data. Hence, the difference between two biometric samples is given by the Hamming distance (HD) or bit errors between the binary vectors obtained from the enrollment and verification phases, respectively. If the HD is smaller (larger) than the decision threshold, then the subject is accepted (rejected) as genuine. Because of the use of ECCs, this decision threshold is limited to the maximum error-correcting capacity of the code, consequently limiting the false rejection rate (FRR) and false acceptance rate tradeoff. A method to improve the FRR consists of using multiple biometric samples in either the enrollment or verification phase. The noise is suppressed, hence reducing the number of bit errors and decreasing the HD. In practice, the number of samples is empirically chosen without fully considering its fundamental impact. In this paper, we present a Gaussian analytical framework for estimating the performance of a binary biometric system given the number of samples being used in the enrollment and the verification phase. The error-detection tradeoff curve that combines the false acceptance and false rejection rates is estimated to assess the system performance. The analytic expressions are validated using the Face Recognition Grand Challenge v2 and Fingerprint Verification Competition 2000 biometric databases

Interaction evaluation of a mobile voice authentication system

Biometric recognition is nowadays widely used in smartphones, making the users' authentication easier and more transparent than PIN codes or patterns. Starting from this idea, the EU project PIDaaS aims to create a secure authentication system through mobile devices based on voice and face recognition as two of the most reliable and user-accepted modalities. This work introduces the project and the first PIDaaS usability evaluation carried out by means of the well-known HBSI model In this experiment, participants interact with a mobile device using the PIDaaS system under laboratory conditions: video recorded and assisted by an operator. Our findings suggest variability among sessions in terms of usability and feed the next PIDaaS HCI design

Towards a more secure border control with 3D face recognition

Biometric data have been integrated in all ICAO compliant passports, since the ICAO members started to implement the ePassport standard. The additional use of three-dimensional models promises significant performance enhancements for border control points. By combining the geometry- and texture-channel information of the face, 3D face recognition systems show an improved robustness while processing variations in poses and problematic lighting conditions when taking the photo. This even holds in a hybrid scenario, when a 3D face scan is compared to a 2D reference image. To assess the potential of three-dimensional face recognition, the 3D Face project was initiated. This paper outlines the approach and research results of this project: The objective was not only to increase the recognition rate but also to develop a new, fake resistant capture device. In addition, methods for protection of the biometric template were researched and the second generation of the international standard ISO/IEC 19794-5:2011 was inspired by the project results

Unrecognizable Yet Identifiable: Image Distortion with Preserved Embeddings

In the realm of security applications, biometric authentication systems play a crucial role, yet one often encounters challenges concerning privacy and security while developing one. One of the most fundamental challenges lies in avoiding storing biometrics directly in the storage but still achieving decently high accuracy. Addressing this issue, we contribute to both artificial intelligence and engineering fields. We introduce an innovative image distortion technique that effectively renders facial images unrecognizable to the eye while maintaining their identifiability by neural network models. From the theoretical perspective, we explore how reliable state-of-the-art biometrics recognition neural networks are by checking the maximal degree of image distortion, which leaves the predicted identity unchanged. On the other hand, applying this technique demonstrates a practical solution to the engineering challenge of balancing security, precision, and performance in biometric authentication systems. Through experimenting on the widely used datasets, we assess the effectiveness of our method in preserving AI feature representation and distorting relative to conventional metrics. We also compare our method with previously used approaches