Jeroen Breebaart

Preventing the Decodability Attack Based Cross-Matching in a Fuzzy Commitment Scheme

Template protection techniques are used within biometric systems in order to safeguard the privacy of the systems subjects. This protection also includes unlinkability, i.e., preventing cross-matching between two or more reference templates from the same subject across different applications. In the literature, the template protection techniques based on fuzzy commitment, also known as the code-offset construction, have recently been investigated. Recent work presented the decodability attack vulnerability facilitating cross-matching based on the protected templates and its theoretical analysis. First, we extend the theoretical analysis and include the comparison between the system and cross-matching performance. We validate the presented analysis using real biometric data from the MCYT fingerprint database. Second, we show that applying a random bit-permutation process secures the fuzzy commitment scheme from cross-matching based on the decodability attack.

Multi-algorithm fusion with template protection

The popularity of biometrics and its widespread use introduces privacy risks. To mitigate these risks, solutions such as the helper-data system, fuzzy vault, fuzzy extractors, and cancelable biometrics were introduced, also known as the field of template protection. In parallel to these developments, fusion of multiple sources of biometric information have shown to improve the verification performance of the biometric system. In this work we analyze fusion of the protected template from two 3D recognition algorithms (multi-algorithm fusion) at feature-, score-, and decision-level. We show that fusion can be applied at the known fusion-levels with the template protection technique known as the Helper-Data System. We also illustrate the required changes of the Helper-Data System and its corresponding limitations. Furthermore, our experimental results, based on 3D face range images of the FRGC v2 dataset, show that indeed fusion improves the verification performance.

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.

Biometric template protection : The need for open standards ()

The objective of this paper is to outline the potential threats to security and privacy that are associated with biometric-enabled applications, to summarize the resulting requirements to ensure secure and private handling of personal data, and to explain why standardization in this area is required. The currently ongoing standardization efforts in ISO/IEC in the area of biometric template protection are described.

A Backward-Compatible Multichannel Audio Codec

We propose in this paper a backward-compatible multichannel audio codec. This codec represents a multichannel audio input signal by a down mix and parametric data. In order to enable backward compatibility, it is necessary to have the possibility of exerting control over the down-mixing procedure. At the same time, in order to achieve a high coding efficiency, both signal and perceptual redundancies should be exploited. In this paper, we describe a codec that unifies the above-mentioned conditions: backward compatibility and exploitation of both signal and perceptual redundancies. The codec combines a high audio quality and a low parameter bit rate. Moreover, its design is flexible, examples of which are the scalability of the audio quality to (in principle) transparency and the possibility to preserve the correlation structure of the original input signals by using synthetic signals. A stereo backward compatible version of the proposed codec is used as a component of the recently standardized MPEG Surround multichannel audio codec.

Features for Audio Classification

Four audio feature sets are evaluated in their ability to differentiate five audio classes: popular music, classical music, speech, background noise and crowd noise. The feature sets include low-level signal properties, mel-frequency spectral coefficients, and two new sets based on perceptual models of hearing. The temporal behavior of the features is analyzed and parameterized and these parameters are included as additional features. Using a standard Gaussian framework for classification, results show that the temporal behavior of features is important for automatic audio classification. In addition, classification is better, on average, if based on features from models of auditory perception rather than on standard features.

Phantom Materialization: A Novel Method to Enhance Stereo Audio Reproduction on Headphones

Loudspeaker reproduction systems are subject to a compromise between spatial realism and cost. By simulating loudspeaker reproduction on headphones, the resulting spatial realism is limited accordingly, despite the virtually unlimited spatial imaging capabilities of binaural audio rendering technology. More particularly, phantom imaging as often used for stereo audio material intended for loudspeaker reproduction is subject to various restrictions in terms of loudspeaker positioning in simulated space. As a consequence, phantom imaging should preferably be avoided when simulating virtual loudspeakers over headphones, especially if head tracking is incorporated or if a wide sound stage is desired. A novel method is described to extract phantom sound sources from stereo audio content and convert these to sound sources in a virtual listening environment.

A quantitative analysis of indistinguishability for a continuous domain biometric cryptosystem

Biometric information is regarded as highly sensitive information and therefore encryption techniques for biometric information are needed to address security and privacy requirements of biometric information. Most security analyses for these encryption techniques focus on the scenario of one user enrolled in a single biometric system. In practice, biometric systems are deployed at different places and the scenario of one user enrolled in many biometric systems is closer to reality. In this scenario, cross-matching (tracking users enrolled in multiple databases) becomes an important privacy threat. To prevent such cross-matching, various methods to create renewable and indistinguishable biometric references have been published. In this paper, we investigate the indistinguishability or the protection against cross-matching of a continuous-domain biometric cryptosystem, the QIM. In particular our contributions are as follows. Firstly, we present a technique, which allows an adversary to decide whether two protected biometric reference data come from the same person or not. Secondly, we quantify the probability of success of an adversary who plays the indistinguishability game and thirdly, we compare the probability of success of an adversary to the authentication performance of the biometric system for the MCYT fingerprint database. The results indicate that although biometric cryptosystems represent a step in the direction of privacy enhancement, we are not there yet.

Analytical template protection performance and maximum key size given a Gaussian-modeled biometric source

Template protection techniques are used within biometric systems in order to protect the stored biometric template against privacy and security threats. A great portion of template protection techniques are based on extracting a key from or binding a key to a biometric sample. The achieved protection depends on the size of the key and its closeness to being random. In the literature it can be observed that there is a large variation on the reported key lengths at similar classification performance of the same template protection system, even when based on the same biometric modality and database. In this work we determine the analytical relationship between the system performance and the theoretical maximum key size given a biometric source modeled by parallel Gaussian channels. We consider the case where the source capacity is evenly distributed across all channels and the channels are independent. We also determine the effect of the parameters such as the source capacity, the number of enrolment and verification samples, and the operating point selection on the maximum key size. We show that a trade-off exists between the privacy protection of the biometric system and its convenience for its users.

Multichannel coding of applause signals

We develop a parametric multichannel audio codec dedicated to coding signals consisting of a dense series of transient-type events. These signals of which applause is a typical example are known to be problematic for such audio codecs. The codec design is based on preservation of both timbre and transient-type event density. It combines a very low complexity and a low parameter bit rate (0.2 kbps). In a formal listening test, we compared the proposed codec to the recently standardised MPEG Surround multichannel codec, with an associated parameter bit rate of 9 kbps. We found the new codec to have a significantly higher audio quality than the MPEG Surround codec for the two multichannel applause signals under test. Though this seems promising, the technique presented is not fully mature, for example, because issues related to integration of the proposed codec in the MPEG Surround codec were not addressed.