Jason Jeffers

Minutiae-Based Structures for A Fuzzy Vault

One vital application of biometrics is to supplement or replace passwords to provide secure authentication. Cryptographic schemes using passwords require exactly the same password at enrolment and verification to authenticate successfully. The inherent variation in samples of the same biometric makes it difficult to replace passwords directly with biometrics in a cryptographic scheme. The fuzzy vault is an innovative cryptographic construct that uses error correction techniques to compensate for biometric variation. Our research is directed to methods of realizing the fuzzy vault for the fingerprint biometric using minutia points described in a translation and rotation invariant manner. We investigate three different minutia representation methods, which are translation and rotation invariant. We study their robustness and determine their suitability to be incorporated in a fuzzy vault construct. We finally show that one of our three chosen structures shows promise for incorporation into a fuzzy vault scheme.

Fingerprint Alignment for A Minutiae-Based Fuzzy Vault

The fuzzy vault is an innovative cryptographic construct that uses error correction techniques to compensate for natural biometric variation. For fingerprints, the fuzzy vault can be used to compensate for the insertion and deletion of minutiae between samples, within the cryptographic framework. However, fingerprint biometrics also suffer from the problem that samples at enrolment and verification cannot be captured and recorded within a universally agreed frame of reference. There is currently no efficient fingerprint pre-alignment technique that also protects the template. In this paper we propose a pre-alignment algorithm that incorporates quantifiable template protection and explore the suitability of three minutiae-based structures for the algorithm. We find that one of the structures is strongly suitable with respect to the goals of our pre-alignment algorithm and its impact on the false non-match rate of an overall system is quantified. Our research also clarifies the key characteristics required from minutiae-based structures for high performance.

Fingerprints as Spatial Graphs: Nodes and Edges

Point-pattern matching of minutiae is the most common method used in fingerprint biometrics, but it is generally insufficient by itself. It has particular limitations in matching partial prints or in secure (biocryptographic) matching. Here, we add structure with a new spatial graph represention of a fingerprint, with minutiae as nodes. Using a sample of fingerprint graphs extracted from the FVC2002 database, we show that matching fingerprints using only the edges of the graphs performs almost as well as using only the nodes. Combinations of edges and nodes have superior performance to either individual score.

Fractional biometrics: safeguarding privacy in biometric applications

This paper presents a biometric system solution that “masks” a fraction of a person’s biometric image before submission, to reduce the possibility of forgery and collusion. A prototype system was constructed for the fingerprint biometric and tested in three security scenarios. It is shown that implementing the fractional biometric system does not significantly affect accuracy. We provide theoretical security analysis on the guessing entropy of a Fractional Template and the security against collusion. We demonstrate that by masking above 50% of the biometric features, we achieve a sufficient mix of security, robustness and accuracy to warrant further study. When 75% of the features are masked, we found that the theoretical guessing entropy is 42 bits, and we found that, on average, 5 authenticators had to collude before the system would be compromised.

Estimating individuality in feature point based retina templates

The lack of large public retina image databases means it is difficult to judge the relative merits of the retina biometric itself, of different scoring functions, or of potential biocryptographic constructs. We derive conservative theoretical genuine and imposter score distributions for feature point based retina templates by normal kernel density estimation. We base them on 147 images from the VARIA database and use 7 scoring functions. This allows us to infer EERs in the range 0.3%-1.3% and, for FNMRs of less than 10%, entropy estimates between 65 bits and 200 bits.

Entropy of the Retina Template

We compare two vessel extraction methods for creation of a retina template, using a database of 20 images of normal retinas. Each vessel in a well defined region is represented by a three dimensional feature, from which a retina template is built. Based on the sample distributions, we propose a preliminary theoretical model to predict the entropy of a retina template. We analyse by experimental and theoretical means the entropy present, and infer that entropy from our retina template compares sufficiently favourably with that of a minutia-based fingerprint template to warrant further study.

Entropy of Feature Point-Based Retina Templates

This paper studies the amount of distinctive information contained in a privacy protecting and compact template of a retinal image created from the locations of crossings and bifurcations in the choroidal vasculature, otherwise called feature points. Using a training set of 20 different retina, we build a template generator that simulates one million imposter comparisons and computes the number of imposter retina comparisons that successfully matched at various thresholds. The template entropy thus computed was used to validate a theoretical model of imposter comparisons. The simulator and the model both estimate that 20 bits of entropy can be achieved by the feature point-based template. Our results reveal the distinctiveness of feature point-based retinal templates, hence establishing their potential as a biometric identifier for high security and memory intensive applications.

Protection of minutiae‐based templates using biocryptographic constructs in the set difference metric

Fingerprint biometric authentication has particular advantages in a highly mobile environment.We investigate design issues involved in building authentication systems using minutia-based fingerprint templates, where the template is protected during comparison as well as storage. Two popular bio-cryptographic schemes based on the set difference metric, the Fuzzy Vault and PinSketch, are analysed with regard to theoretical bounds on the template sizes and decision thresholds. We define six different minutiae-based templates and for each, qantisation parameters are determined that yield the best matching performance at a threshold where the probability of false match is zero. We then determine which, if any, of the representations satisfy the theoretical bounds proposed for each bio-cryptographic construct. We implement a PinSketchbased authentication system that uses a combination of a commonality and a set difference measure to securely compare two fingerprint templates, with negligible deterioration in accuracy. Our results indicate that to securely correct the degree of intrasample error observed in minutiae-based templates, efficient commonality-based error tolerant cryptographic constructs will be more suited than set difference based constructs. Copyright

Influence Neighbourhoods in CiteSeer: A Case Study

We are interested in using purely network-based techniques to assist in matching instances across databases that can be represented as complex networks. In particular we are interested in the individuality of the influence neighbourhood of a node (the sub graph induced by its in-neighbours) in a directed network. We derive a paper citation network from the archived Cite Seer database and use this network as a case study of influence neighbourhoods. We show that papers can reliably be distinguished by their influence neighbourhoods.