Preda Mihailescu

Security Considerations in Minutiae-Based Fuzzy Vaults

The fuzzy vault scheme is a cryptographic primitive that can be used to protect human fingerprint templates where stored. Analyses for most implementations account for brute-force security only. There are, however, other risks that have to be consider, such as false-accept attacks, record multiplicity attacks, and information leakage from auxiliary data, such as alignment parameters. In fact, the existing work lacks analyses of these weaknesses and are even susceptible to a variety of them. In view of these vulnerabilities, we redesign a minutiae-based fuzzy vault implementation preventing an adversary from running attacks via record multiplicity. Furthermore, we propose a mechanism for robust absolute fingerprint prealignment. In combination, we obtain a fingerprint-based fuzzy vault that resists known record multiplicity attacks and that does not leak information about the protected fingerprints from auxiliary alignment data. By experiments, we evaluate the performance of our security-improved implementation that, even though it has slight usability merits as compared with other minutiae-based implementations, provides improved security. However, despite heavy efforts spent in improving security, our implementation is, like all other implementations based on a single finger, subjected to a fundamental security limitation related to the false acceptance rate, i.e., false-accept attack. Consequently, this paper supports the notion that a single finger is not sufficient to provide acceptable security. Instead, implementations for multiple finger or even multiple modalities should be deployed the security of which may be improved by the technical contributions of this paper.

Improved Fingerprint Image Segmentation and Reconstruction of Low Quality Areas

One of the main reason for false recognition is noise added to fingerprint images during the acquisition step. Hence, the improvement of the enhancement step affects general accuracy of automatic recognition systems. In one of our previous publications we introduced hierarchically linked extended features -- the new set of features which not only includes additional fingerprint features individually but also contains the information about their relationships such as line adjacency information at minutiae points or links between neighbouring fingerprint lines. In this work we present the application of the extended features to preprocessing and enhancement. We use structural information for improving the segmentation step, as well as connecting disrupted fingerprint lines and recovering missing minutiae. Experiments show a decrease in the error rate in matching.

Computing the eigenvalue in the schoof-elkies-atkin algorithm using abelian lifts

The Schoof-Elkies-Atkin algorithm is the best known method for counting the number of points of an elliptic curve defined over a finite field of large characteristic. We use Abelian properties of division polynomials to design a fast theoretical and practical algorithm for nding the eigenvalue.

Fast convolutions meet Montgomery

Arithmetic in large ring and field extensions is an important problem of symbolic computation, and it consists essentially of the combination of one multiplication and one division in the underlying ring. Methods are known for replacing one division by two short multiplications in the underlying ring, which can be performed essentially by using convolutions. However, while using school-book multiplication, modular multiplication may be grouped into 2M(R) operations (where M(R) denotes the number of operations of one multiplication in the underlying ring), the short multiplication problem is an important obstruction to convolution. It raises the costs in that case to 3M(R). In this paper we give a method for understanding and bypassing this problem, thus reducing the costs of ring arithmetic to roughly 2M(R) when also using fast convolutions. The algorithms have been implemented with results which fit well the theoretical prediction and which shall be presented in a separate paper.

Robust orientation field estimation in fingerprint images with broken ridge lines

A good and reliable orientation field (OF) estimation is of great importance in fingerprint image processing. This paper presents an OF estimation approach that is based on traced ridge and furrow lines. The method considers pieces of flow information from a larger region and provides robustness against disturbances caused, e.g. by temporary scars, creases, contamination, wetness or dryness of the finger. The performance of the method is evaluated in simulation runs with artificial ridge interruptions and compared to the gradients based method and a multiscale directional operator.

Hierarchically linked extended features in fingerprints

Requirements for identifying and defining additional fingerprint features beyond minutiae, even not limited to level 3 details, has already been addressed by the community . However, new feature proposals are based on refinements of existing features (e.g. a finer level of classification), or on the introduction of new single features (e.g. 3-D level features such as the ridge height) . The new set of features proposed in this work does not only include additional fingerprint features individually but it also contains the information about their relationships such as line adjacency information at minutiae points or links between neighboring fingerprint lines. The dual information, that is the interference between ridges and valleys, is included as well. For the first confirmation of the quality of extracted features in application for the matching, the goodness of the extracted minutiae has been tested. The experiments have shown a decreased error rate when applying the minutiae to a standard minutiae-based matcher.