Empreinte digitale

Résumé

vignette| upright=0.9| Photo d'une empreinte digitale. vignette| upright=0.8| Dermatoglyphes d'un doigt : plis papillaires (crêtes et sillons). Une empreinte digitale ou dactylogramme est le dessin formé par un doigt sur un support suffisamment lisse pour qu'y restent marqués les dermatoglyphes. Les dermatoglyphes, également appelés « empreintes digitales » par abus de langage, sont des plis (des crêtes et des sillons) à la surface de la peau et particulièrement des doigts, qui forment des volutes et des tourbillons spécifiques à chaque doigt de chaque individu. La probabilité que deux personnes aient les mêmes empreintes digitales est infinitésimale : une chance sur . Les dermatoglyphes commencent à se former entre la et la semaine de vie du fœtus, par un plissement des couches cellulaires. Si l'expression des gènes joue un rôle, les circonvolutions des crêtes qui leur donnent leur dessin caractéristique dépendent de nombreux facteurs externes, notamment la vitesse de croissance

Source officielle

https://fr.wikipedia.org/wiki/Empreinte_digitale

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Biometrics & [and] Security

Claude Barral

Since the beginning of this brand new century, and especially since the 2001 Sept 11 events in the U.S, several biometric technologies are considered mature enough to be a new tool for security. Generally associated to a personal device for privacy protection, biometric references are stored in secured electronic devices such as smart cards, and systems are using cryptographic tools to communicate with the smart card and securely exchange biometric data. After a general introduction about biometrics, smart cards and cryptography, a second part will introduce our work with fake finger attacks on fingerprint sensors and tests done with different materials. The third part will present our approach for a lightweight fingerprint recognition algorithm for smart cards. The fourth part will detail security protocols used in different applications such as Personal Identity Verification cards. We will discuss our implementation such as the one we developed for the NIST to be used in PIV smart cards. Finally, a fifth part will address Cryptography-Biometrics interaction. We will highlight the antagonism between Cryptography – determinism, stable data – and Biometrics – statistical, error-prone –. Then we will present our application of challenge-response protocol to biometric data for easing the fingerprint recognition process.

EPFL2010

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Degradation in data quality is still a main source of errors in the modern biometric recognition systems. However, the data quality can be embedded in the recognition methods at global and local levels to build more accurate biometric systems. Local quality measures represent the quality of local parts within a biometric sample. They are either combined into a global quality measure or directly embedded into the recognition techniques. Minutiae-based comparison is the main and the most common technique used for fingerprint recognition and high-resolution palmprint recognition in various security and forensic applications. The focus of this thesis is mainly on direct incorporation of the local quality measures into the state-of-the-art minutiae-based recognition methods, particularly those based on Minutiae Cylinder-Code (MCC). Firstly, we introduce cylinder quality measures as a new type of local quality measures associated with the local minutiae descriptors. Then, we propose several methods for incorporating such local quality measures into the biometric systems, in order to improve their recognition performance. Among them is a novel and efficient quality-based consolidation method for embedding minutiae quality and cylinder quality measures in MCC based comparison methods. We also propose a supervised embedding method based on a binary classification model, which requires labeled minutiae for training. Finally, we apply a variant of the proposed consolidation method for the challenging case of latent fingerprint and palmprint identification with embedded subjective and objective minutiae quality.

EPFL2016

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Accelerating photofragmentation UV Spectroscopy–Mass spectrometry fingerprinting for quantification of isomeric peptides

Oleg Boyarkine, Erik Saparbayev, Elizaveta Solovyeva

Identification of isomeric biomolecules remains a challenging analytical problem. A recently developed spectroscopic method that combines UV photofragmentation and mass spectrometry for fingerprinting of cold ions (2D UV-MS), has already demonstrated its high performance in the library-based identification and quantification of different types of biomolecular isomers. The practical use of the method has been hindered by a slow rate of data acquisition, which makes the fingerprinting incompatible with high-throughput analysis and online liquid chromatography (LC) separation. Herein we demonstrate how the use of a few pre-selected wavelengths can accelerate the method by two orders of magnitude without a significant loss of accuracy. As a proof of principle, 2D UV-MS fingerprinting was coupled to online LC separation and tested for quantification of isomeric peptides containing either Asp or isoAsp residues. The relative concentrations of the peptides mixed in solution have been determined, on average, with better than 4% and 6% accuracy for resolving and non-resolving gradients of LC separation, respectively.

2021

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