Técnicas biométricas: análisis de las técnicas actuales y nuevas tendencias

En las tecnologías de la información, la biometría se refiere a la aplicación de técnicas matemáticas y estadísticas sobre los rasgos conductuales o físicos de un ser vivo para su autenticación, es decir, verificar su identidad. Existen muchas aplicaciones que requieren que la autenticación del usuario o la verificación de su identidad sea precisa, siendo la biometría la disciplina que se ocupa de la identificación automática o la verificación de la identidad de individuos basada en sus características fisiológicas y/o de comportamiento, resulta necesario comprender los indicadores biométricos completamente para poder implementar un sistema biométrico exitoso.Eje: Computación Gráfica, Imágenes y Visualización.Red de Universidades con Carreras en Informátic

Poisoning Attacks on Learning-Based Keystroke Authentication and a Residue Feature Based Defense

Behavioral biometrics, such as keystroke dynamics, are characterized by relatively large variation in the input samples as compared to physiological biometrics such as fingerprints and iris. Recent advances in machine learning have resulted in behaviorbased pattern learning methods that obviate the effects of variation by mapping the variable behavior patterns to a unique identity with high accuracy. However, it has also exposed the learning systems to attacks that use updating mechanisms in learning by injecting imposter samples to deliberately drift the data to impostors’ patterns. Using the principles of adversarial drift, we develop a class of poisoning attacks, named Frog-Boiling attacks. The update samples are crafted with slow changes and random perturbations so that they can bypass the classifiers detection. Taking the case of keystroke dynamics which includes motoric and neurological learning, we demonstrate the success of our attack mechanism. We also present a detection mechanism for the frog-boiling attack that uses correlation between successive training samples to detect spurious input patterns. To measure the effect of adversarial drift in frog-boiling attack and the effectiveness of the proposed defense mechanism, we use traditional error rates such as FAR, FRR, and EER and the metric in terms of shifts in biometric menagerie

Framework for evaluation of multimodal biometric systems

Primena biometrijskih tehnologija danas u ljudskom društvu postaje sve češća, gotovo da možemo konstatovati da je ona deo naše svakodnevnice. Prilikom implementacije biometrijske autentikacije, svaki sistem ima svoje zahteve i ograničenja, u zavisnosti od konkretnog scenarija u kojem se sistem koristi. Za odabir odgovarajućeg biometrijskog modaliteta, kao i algoritama za rad sa biometrijskim modalitetom, neophodno je sprovesti odgovarajuću evaluaciju performansi rada biometrijskog sistema. Ipak, ovu evaluaciju nije uvek lako sprovesti, kako za unimodalne, tako i za multimodalne biometrijske sisteme. Čak i kada su dostupne javne baze biometrijskih podataka za evaluaciju algoritama određenog biometrijskog modaliteta, potrebno je prilagoditi rad sistema protokolu testiranja koji konkretna baza definiše. U slučaju multimodalnog pristupa, evaluacija se dodatno komplikuje usled upotrebe različitih algoritama za fuziju informacija. Kako u dostupnoj relevantnoj literaturi nije pronađen detaljan prikaz modela evaluacije multimodalnih biometrijskih sistema, a radi prevazilaženja ovih teškoća, u okviru ovog doktorata definisan je objedinjeni model evaluacije multimodalnih biometrijskih sistema. Za definisanje ovog modela primenjena je MDA (Model Driven Architecture) paradigma. U okviru objedinjenog modela dat je metamodel evaluacije multimodalnih biometrijskih sistema, koji predstavlja svojevrsnu ontologiju pojmova značajnih za ovu oblast. Primenom ovog metamodela, moguće je kreirati modele evaluacije različitih biometrijskih sistema. Na osnovu modela evaluacije multimodalnih biometrijskih sistema kreiran je prototip okvira za evaluaciju multimodalnih biometrijskih sistema. Pomoću predloženog okvira moguća je evaluacija performansi multimodalnog biometrijskog sistema u različitim slučajevima korišćenja. Eksperimentalni rezultati evaluacije nad konkretnom bazom i algoritmima pokazuju da primena okvira skraćuje za četiri puta vreme potrebno za evaluaciju. Razvijena je i nova metoda za analitičko određivanje praga osetljivosti u skladu sa postavljenim parametrima željenog ponašanja sistema. Na kraju, na primeru alata koji je koristio neke od funkcionalnosti okvira, prikazano je kako primena okvira može učiniti efikasnijim proces obrazovanja inženjera u oblasti biometrije.Application of biometric technologies in our contemporary human society is getting more frequent, so we can almost state that biometric technologies are part of our everyday life. When implementing biometric authentication, each system has specific requirements and constraints, which depend on the actual scenario in which the system is being used. In order to choose the adequate biometric modality, and also a fitting algorithm for the chosen modality, it is necessary to perform an evaluation of the biometric system performance. However, this evaluation is not always easy to conduct. This fact is true for both the unimodal and multimodal biometric systems. Even when open biometrics databases are available for evaluation, it is necessary to adapt system to work with testing protocol of the chosen open database. Moreover, if the biometric system uses multiple biometric modalities, evaluation gets even more complicated because of different available fusion algorithms. In order to overcome these difficulties, as there is not a detailed model of multimodal biometric systems available in relevant literature, this thesis presents a unified multimodal biometric systems evaluation model. Presented model is based on MDA (Model Driven Architecture) paradigm. A part of the unified multimodal biometric systems evaluation model is the metamodel of multimodal biometric system evaluation, which represents an ontology of terms used in this domain. Based on unified multimodal biometric systems evaluation model, a prototype framework for multimodal biometrics systems evaluation has been created. By using proposed framework it is possible to evaluate performance of multimodal biometric system in different use cases. Experimental evaluation results based on used database and algorithms show that the use of framework shortens time necessary for evaluation to a quarter of previously required time. Also, a new analytical method for biometric system threshold optimization, based on the predefined desired system behavior was developed. As final, a learning tool based on some of the framework functionalities is used to show how the use of framework can make the process of educating engineers in the field of biometrics more efficient

Characterization of Biometric Template Aging in a Multiyear, Multivendor Longitudinal Fingerprint Matching Study

Biometric features are known to change over time, presenting a challenge for their use in identity management systems. Viewed as an instrumentation and measurement problem, these changes represent a potential source of measurement or calibration error that needs to be addressed at the system level in order to guarantee performance over the lifetime of the system. In this paper, we develop a novel metric, biometric permanence, to characterize the stability of biometric features. First, we define permanence in terms of the change in a false nonmatch rate (FNMR) over a repeated sequence of enrollment and verification events for a given population. However, since changes in the FNMR are expected to be small, any variability in the biometric capture over time will camouflage the changes of interest. To address this issue, we propose a robust methodology that can isolate the visit-to-visit variability and substantially improve the estimation. We develop and characterize a heuristic statistical model for a biometric capture system, and apply it to a large data set of fingerprint biometrics collected over a period of seven years on a variety of commercially available capture devices. We discuss how this methodology can be used to isolate the effect of biometric template aging and to develop system-level strategies for dealing with it

XXI Workshop de Investigadores en Ciencias de la Computación - WICC 2019: libro de actas

Trabajos presentados en el XXI Workshop de Investigadores en Ciencias de la Computación (WICC), celebrado en la provincia de San Juan los días 25 y 26 de abril 2019, organizado por la Red de Universidades con Carreras en Informática (RedUNCI) y la Facultad de Ciencias Exactas, Físicas y Naturales de la Universidad Nacional de San Juan.Red de Universidades con Carreras en Informátic

XXI Workshop de Investigadores en Ciencias de la Computación - WICC 2019: libro de actas

Trabajos presentados en el XXI Workshop de Investigadores en Ciencias de la Computación (WICC), celebrado en la provincia de San Juan los días 25 y 26 de abril 2019, organizado por la Red de Universidades con Carreras en Informática (RedUNCI) y la Facultad de Ciencias Exactas, Físicas y Naturales de la Universidad Nacional de San Juan.Red de Universidades con Carreras en Informátic