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A presente dissertação aborda o processo de identificação por biometria das estruturas oculares, analisando suas bases biológicas e tecnológicas e sua aplicabilidade e confiabilidade para utilização jurídica. Está dividida em três partes. Na primeira, são analisados aspectos do conceito de identidade em suas diversas acepções e do processo de identificação médico legal por meio da utilização de diferentes métodos. Na segunda, passa-se a estudar a biometria da íris e da retina, abordando suas bases biológicas e tecnológicas. Na terceira e última parte, estuda-se a aplicabilidade e confiabilidade da biometria ocular para finalidades jurídicas, como método de perícia da identidade. / The purpose of this work is to study the identification process by ocular biometrics, from its biological and technological basis to its forensic and legal system applications. It is divided into three sections. The first section discusses the concept of identity and the identification methods used by forensic professionals. The second section discusses the ocular biometrics methods using iris and retinal traits, emphasizing their biological as well as their technological basis. The third and last section discusses the reliability and applicability of these biometrics modalities as identification methods in legal and forensic issues.

A presente dissertação aborda o processo de identificação por biometria das estruturas oculares, analisando suas bases biológicas e tecnológicas e sua aplicabilidade e confiabilidade para utilização jurídica. Está dividida em três partes. Na primeira, são analisados aspectos do conceito de identidade em suas diversas acepções e do processo de identificação médico legal por meio da utilização de diferentes métodos. Na segunda, passa-se a estudar a biometria da íris e da retina, abordando suas bases biológicas e tecnológicas. Na terceira e última parte, estuda-se a aplicabilidade e confiabilidade da biometria ocular para finalidades jurídicas, como método de perícia da identidade. / The purpose of this work is to study the identification process by ocular biometrics, from its biological and technological basis to its forensic and legal system applications. It is divided into three sections. The first section discusses the concept of identity and the identification methods used by forensic professionals. The second section discusses the ocular biometrics methods using iris and retinal traits, emphasizing their biological as well as their technological basis. The third and last section discusses the reliability and applicability of these biometrics modalities as identification methods in legal and forensic issues.

Biometrics is constantly evolving technology which has been widely used in many official and commercial identification applications. In fact in recent years biometric-based authentication techniques received more attention due to increased concerns in security. Most biometric systems that are currently in use typically employ a single biometric trait. Such systems are called unibiometric systems. Despite considerable advances in recent years, there are still challenges in authentication based on a single biometric trait, such as noisy data, restricted degree of freedom, intra-class variability, non-universality, spoof attack and unacceptable error rates. Some of the challenges can be handled by designing a multimodal biometric system. Multimodal biometric systems are those which utilize or are capable of utilizing, more than one physiological or behavioural characteristic for enrolment, verification, or identification. In this thesis, we propose a novel fusion approach at a hybrid level between iris and online signature traits. Online signature and iris authentication techniques have been employed in a range of biometric applications. Besides improving the accuracy, the fusion of both of the biometrics has several advantages such as increasing population coverage, deterring spoofing activities and reducing enrolment failure. In this doctoral dissertation, we make a first attempt to combine online signature and iris biometrics. We principally explore the fusion of iris and online signature biometrics and their potential application as biometric identifiers. To address this issue, investigations is carried out into the relative performance of several statistical data fusion techniques for integrating the information in both unimodal and multimodal biometrics. We compare the results of the multimodal approach with the results of the individual online signature and iris authentication approaches. This dissertation describes research into the feature and decision fusion levels in multimodal biometrics.

The modern mobile device has become an everyday tool for users and business. Technological advancements in the device itself and the networks that connect them have enabled a range of services and data access which have introduced a subsequent increased security risk. Given the latter, the security requirements need to be re-evaluated and authentication is a key countermeasure in this regard. However, it has traditionally been poorly served and would benefit from research to better understand how authentication can be provided to establish sufficient trust. This thesis investigates the security requirements of mobile devices through literature as well as acquiring the user’s perspectives. Given the findings it proposes biometric authentication as a means to establish a more trustworthy approach to user authentication and considers the applicability and topology considerations. Given the different risk and requirements, an authentication framework that offers transparent and continuous is developed. A thorough end-user evaluation of the model demonstrates many positive aspects of transparent authentication. The technical evaluation however, does raise a number of operational challenges that are difficult to achieve in a practical deployment. The research continues to model and simulate the operation of the framework in an controlled environment seeking to identify and correlate the key attributes of the system. Based upon these results and a number of novel adaptations are proposed to overcome the operational challenges and improve upon the impostor detection rate. The new approach to the framework simplifies the approach significantly and improves upon the security of the system, whilst maintaining an acceptable level of usability.

The term biometrics is used to describe the process of analyzing biological and behavioral traits that are unique to an individual in order to confirm or determine his or her identity. Many biometric modalities are currently being researched and implemented including, fingerprints, hand and facial geometry, iris recognition, vein structure recognition, gait, voice recognition, etc... This project explores the possibility of using corneal topography measurements as a trait for biometric identification. Two new corneal topographers were developed for this study. The first was designed to function as an operator-free device that will allow a user to approach the device and have his or her corneal topography measured. Human subject topography data were collected with this device and compared to measurements made with the commercially available Keratron Piccolo topographer (Optikon, Rome, Italy). A third topographer that departs from the standard Placido disk technology allows for arbitrary pattern illumination through the use of LCD monitors. This topographer was built and tested to be used in future research studies. Topography data was collected from 59 subjects and modeled using Zernike polynomials, which provide for a simple method of compressing topography data and comparing one topographical measurement with a database for biometric identification. The data were analyzed to determine the biometric error rates associated with corneal topography measurements. Reasonably accurate results, between three to eight percent simultaneous false match and false non-match rates, were achieved.

Liveness detection in automatic fingerprint identification systems (AFIS) is an issue which still prevents its use in many unsupervised security applications. In the last decade, various hardware and software solutions for the detection of liveness from fingerprints have been proposed by academic research groups. However, the proposed methods have not yet been practically implemented with existing AFIS. A large amount of research is needed before commercial AFIS can be implemented. In this research, novel active pore based liveness detection methods were proposed for AFIS. These novel methods are based on the detection of active pores on fingertip ridges, and the measurement of ionic activity in the sweat fluid that appears at the openings of active pores. The literature is critically reviewed in terms of liveness detection issues. Existing fingerprint technology, and hardware and software solutions proposed for liveness detection are also examined. A comparative study has been completed on the commercially and specifically collected fingerprint databases, and it was concluded that images in these datasets do not contained any visible evidence of liveness. They were used to test various algorithms developed for liveness detection; however, to implement proper liveness detection in fingerprint systems a new database with fine details of fingertips is needed. Therefore a new high resolution Brunel Fingerprint Biometric Database (B-FBDB) was captured and collected for this novel liveness detection research. The first proposed novel liveness detection method is a High Pass Correlation Filtering Algorithm (HCFA). This image processing algorithm has been developed in Matlab and tested on B-FBDB dataset images. The results of the HCFA algorithm have proved the idea behind the research, as they successfully demonstrated the clear possibility of liveness detection by active pore detection from high resolution images. The second novel liveness detection method is based on the experimental evidence. This method explains liveness detection by measuring the ionic activities above the sample of ionic sweat fluid. A Micro Needle Electrode (MNE) based setup was used in this experiment to measure the ionic activities. In results, 5.9 pC to 6.5 pC charges were detected with ten NME positions (50μm to 360 μm) above the surface of ionic sweat fluid. These measurements are also a proof of liveness from active fingertip pores, and this technique can be used in the future to implement liveness detection solutions. The interaction of NME and ionic fluid was modelled in COMSOL multiphysics, and the effect of electric field variations on NME was recorded at 5μm -360μm positions above the ionic fluid.

La biométrie se réfère à la reconnaissance automatique des individus. Elle est basée sur leurs caractéristiques physiologiques et/ou comportementales. Le contrôle postural, bien que soit une caractéristique comportementale de l'Homme, n'a pas été bien développée dans le domaine de la biométrie. Le travail mené dans cette thèse repose sur l'analyse des signaux stabilométriques et l'application à la biométrie. Dans un premier volet, une étude de l'information posturale, en particulier le signal stabilométrique, est effectuée à travers des méthodes d'analyses classiques à savoir et l'analyse spatio-temporelle, spectrale et stochastique et à travers aussi deux méthodes de décomposition : la décomposition appelée analyse en composantes principales (ACP) et la décomposition en ondelettes. La méthode ACP, basée sur le modèle additif, permet de décomposer le signal en trois composantes: un signal de tendance, un signal d'excursion et un signal de tremblements. La méthode de décomposition en ondelettes permet de décomposer le signal en trois niveaux de signaux de détail et trois niveaux de signaux d'approximation. Suite à l'étude de la stabilité posturale, l'analyse spectrale et l'analyse de la phase des différentes composantes issues de la ACP et de la décomposition en ondelettes, la comparaison de ces deux méthodes conclut que la méthode ACP est plus appropriée que la décomposition en ondelettes pour analyser le stabilogramme. A partir des méthodes de décomposition et des méthodes d'analyses classiques, des paramètres sont extraits afin d'étudier l'effet de différents facteurs sur la stabilité posturale et sur le déplacement du centre de masse. Ces facteurs sont la vision, la direction, la proprioception, l'âge, le genre, la taille et le poids. Un deuxième volet de ce travail est consacré à l'application biométrique, à partir des paramètres extraits et suite à une analyse statistique ANOVA, ceux qui sont les plus discriminatifs sont utilisés pour identifier des sujets et les classer selon leur âge, genre, poids et taille. Cette application biométrique est effectuée par trois méthodes de classification à savoir, K-ppv, ADL et SVM. Les applications biométriques aboutissent à des taux de reconnaissance respectables dépassant 80%. De ce fait, il est à déduire que l'analyse du contrôle postural est prometteuse dans le domaine de la biométrie / Biometrics refers to automatic recognition of individuals. It is based on their physiological and / or behavioral. The postural control, despite that is a human behavioral characteristic, has not been well developed in the field of biometrics. The work performed in this thesis is based on the stabilometric signals analysis ant biometric application. Firstly, a study of the postural information especially the stabilometric signal is carried out through traditional analysis namely temporal, frequency and stochastic analysis and two decomposition methods named principle components analysis (ACP) decomposition and wavelet decomposition. The ACP method, based on the additive model, allows decomposing the signal into three components: a trend signal, a rambling signal and a trembling signal. The wavelet decomposition method allows decomposing the signal into three levels of detail signals and three signal levels of approximation. Through the study of postural stability, spectral analysis and phase analysis of the different components from the ACP and the wavelet decomposition, the comparison of these two methods concludes that the ACP method is more appropriate than the wavelet decomposition to analyze the stabilogram. From the decomposition methods and classical methods of analysis, several parameters are extracted to study the effect of different factors on postural stability and the center of mass displacement. These factors are named vision, direction, proprioception, age, gender, height and weight. A second aspect of this work is devoted to the application of biometrics, from the extracted parameters and through ANOVA statistic analysis, those that are most discriminative are used to identify subjects and classify them according to age, gender, weight and size. This biometric application is performed by three classification methods namely, K-NN, LDA and SVM. Biometric applications result in respectable recognition rate exceeding 80%. Therefore, it is inferred that the analysis of postural control is promising in the field of biometrics

This work demonstrates the viability of the ballistocardiogram (BCG) signal derived from a head-worn device as a biometric modality for authentication. The BCG signal is the measure of an individual's body acceleration as a result of the heart's ejection of blood. It is a characterization of an individual's cardiac cycle and can be derived non-invasively from the measurement of subtle movements of a person's extremities. Through the use of accelerometer and gyroscope sensors on a Smart Eyewear (SEW) device, derived BCG signals are used to train a convolutional neural network (CNN) as an authentication model, which is personalized for each wearer. This system is evaluated using data from 12 subjects, showing that this approach has an equal error rate of 3.5% immediately after training, and only marginally degrades to 13% after about 2 months, in the worst case. We also explore the use of our authentication approach for individuals with severe motor disabilities, and observe that the results fall only slightly short of those of the larger population, with immediate EER values at 11.2% before rising to 21.6%, again in the worst case.. Overall, we demonstrate that this model presents a longitudinally-viable authentication solution for passive biometric authentication.

Orientador: Luiza Aparecida Trinca / Banca: José Silvio Govone / Banca: Silvio Sandoval Zocchi / Resumo: Os ensaios na area de farmacologia cl nica envolvem coletas sangu neas e medidas da informação (concentração de um fármaco) em horários pré estabelecidos. A prática atual, na maioria das vezes, estabelece os tempos de coleta arbitrariamente, o que pode resultar em dados pouco informativos para ajustar um modelo. Uma metodologia para resolver este tipo de problema e a construcão de delineamentos otimos. Em geral, os modelos envolvem equações não lineares. Sendo que um modelo popular e o modelo monocompartimental (de primeira ordem de absorção e eliminação) que possui três parâmetros. O problema principal de delineamento para modelos não lineares e que a matriz de variâncias e covariâncias dos estimadores dos parâmetros depende dos valores destes, dificultando o planejamento. Outra dificuldade é que várias coletas são realizadas num mesmo sujeito e portanto as respostas são correlacionadas. Assim, a matriz de variâncias e covariâncias depende também das correlações que podem ser incorporadas considerando-se um modelo não linear com efeitos aleatórios. Esse trabalho visa o estudo da teoria de delineamentos... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: Trials in clinical pharmacology involves colleting blood samples and measuring the concentration of a drug at pre-especi ed moments. Current practice, usually xes the point times arbitrarily, which can result in uninformative data to t the aimed model. A methodology for solving such problems is the construction of optimum designs. In general, the models involve nonlinear equations. A popular model is the one-compartment model ( rst-order absorption and elimination). This model has three parameters. The main problem of design for nonlinear models is that the matrix of variances and covariances of the estimators of the parameters depends on the values of these, making the planning more di cult. Another di culty is that several samples are performed in the same subject and therefore the responses are correlated. The matrix of variances and covariances also depends on the correlations. The correlations can be incorporated by considering a nonlinear model with random e ects. This work aims to study the theory of optimal designs and the construction of algorithm to optimize designs under the nonlinear model with xed e ects and random e ects. The methodology can produce local optimum designs at some prior value of the parameters or try to reach global optimum through the incorporation of probability distributions of the parameters which are taken into account when calculating the value of the criterion used such designs are called Bayesians. Based on the results of an experiment from the literature D and Aw local and Bayesian optimum designs were obtained. To compare designs their e ciencies were calculated / Mestre