Being able to measure the actual information content of biometrics is very important but also a challenging problem. Main difficulty here is not only related to the selected feature representation of the biometric data, but also related to the matching algorithm employed in biometric systems. In this paper, we propose a new measure for measuring biometric information using relative entropy between intra-user and inter-user distance distributions. As an example, we evaluated the proposed measure on a face image dataset.

We present an information-theoretically secure biometric storage system using graph-based error correcting codes in a Slepian-Wolf coding framework. Our architecture is motivated by the noisy nature of personal biometrics and the requirement to provide security without storing the true biometric at the device. The principal difficulty is that real biometric signals, such as fingerprints, do not obey the i.i.d. or ergodic statistics that are required for the underlying typicality properties in the Slepian-Wolf coding framework. To meet this challenge, we propose to transform the biometric data into binary feature vectors that are i.i.d. Bernoulli(0.5), independent across different users, and related within the same user through a BSC-p channel with small p< 0.5. Since this is a standard channel model for LDPC codes, the feature vectors are now suitable for LDPC syndrome coding. The syndromes serve as secure biometrics for access control. Experiments on a fingerprint database demonstrate that the system is information-theoretically secure, and achieves very low false accept rates and low false reject rates.

Since biometric data cannot be easily replaced or revoked, it is important that biometric templates used in biometric applications should be constructed and stored in a secure way, such that attackers would not be able to forge biometric data easily even when the templates are compromised. This is a challenging goal since biometric data are "noisy" by nature, and the matching algorithms are often complex, which make it difficult to apply traditional cryptographic techniques, especially when multiple modalities are considered. In this paper, we consider a "fusion " of a minutiae-based fingerprint authentication scheme and an SVD-based face authentication scheme, and show that by employing a recently proposed cryptographic primitive called "secure sketch ", and a known geometric transformation on minutiae, we can make it easier to combine different modalities, and at the same time make it computationally infeasible to forge an "original" combination of fingerprint and face image that passes the authentication. We evaluate the effectiveness of our scheme using real fingerprints and face images from publicly available sources.

Powerful digital media editing tools make producing good quality forgeries very easy for almost anyone. Therefore, proving the authenticity and integrity of digital media becomes increasingly important. In this work, we propose a simple method to detect image tampering operations that involve sharpness/blurriness adjustment. Our approach is based on the assumption that if a digital image undergoes a copy-paste type of forgery, average sharpness/blurriness value of the forged region is expected to be different as compared to the non-tampered parts of the image. The method of estimating sharpness/blurriness value of an image is based on the regularity properties of wavelet transform coefficients which involves measuring the decay of wavelet transform coefficients across scales. Our preliminary results show that the estimated sharpness/blurriness scores can be used to identify tampered areas of the image.

In a novel method for identifying the source camera of a digital image is proposed. The method is based on first extracting imaging sensor's pattern noise from many images and later verifying its presence in a given image through a correlative procedure. In this paper, we investigate the performance of this method in a more realistic setting and provide results concerning its detection performance. To improve the applicability of the method as a forensic tool, we propose an enhancement over it by also verifying that class properties of the image in question are in agreement with those of the camera. For this purpose, we identify and compare characteristics due to demosaicing operation. Our results show that the enhanced method offers a significant improvement in the performance.

Secure storage of biometric templates has become an increasingly important issue in biometric authentication systems. We study how secure sketch, a recently proposed error-tolerant cryptographic primitive, can be applied to protect the templates. We identify several practical issues that are not addressed in the existing theoretical framework, and show the subtleties in evaluating the security of practical systems. We propose a general framework to design and analyze a secure sketch for biometric templates, and give a concrete construction for face biometrics as an example. We show that theoretical bounds have their limitations in practical schemes, and the exact security of the system often needs more careful investigations. We further discuss how to use secure sketch in the design of multifactor authentication systems that allow easy revocation of user credentials.