The main goal of this thesis is to introduce the meaning of term identification and term biometrics as a key field for fingerprint recognition. Thesis also introduces principals and types of automatic processing of fingerprint images and automatic fingerprints identification algorithms. An existing and successful methods are being described in the thesis and pre-processing of fingerprint images is being realized. Automatic fingerprint identification algorithm based on distance of minutiae from the core, core type and orientation field of the fingerprint is proposed. The proposed algorithm was tested on a database of fingerprint images and was statistically analysed.

Deepfake technológia je v poslednej dobe na vzostupe. Vzniká mnoho techník a nástrojov pre tvorbu deepfake médií a začínajú sa používať ako pre nezákonné tak aj pre prospešné činnosti. Nezákonné použitie vedie k výskumu techník pre detekciu deepfake médií a ich neustálemu zlepšovaniu, takisto ako k potrebe vzdelávať širokú verejnosť o nástrahách, ktoré táto technológia prináša. Jedna z málo preskúmaných oblastí škodlivého použitia je používanie deepfake pre oklamanie systémov hlasovej autentifikácie. Názory spoločnosti na vykonateľnosť takýchto útokov sa líšia, no existuje len málo vedeckých dôkazov. Cieľom tejto práce je preskúmať aktuálnu pripravenosť systémov hlasovej biometrie čeliť deepfake nahrávkam. Vykonané experimenty ukazujú, že systémy hlasovej biometrie sú zraniteľné pomocou deepfake nahrávok. Napriek tomu, že skoro všetky verejne dostupné nástroje a modely sú určené pre syntézu anglického jazyka, v tejto práci ukazujem, že syntéza hlasu v akomkoľvek jazyku nie je veľmi náročná. Nakoniec navrhujem riešenie pre zníženie rizika ktoré deepfake nahrávky predstavujú pre systémy hlasovej biometrie, a to používať overenie hlasu závislé na texte, nakoľko som ukázal, že je odolnejšie proti deepfake nahrávkam.

Reliable authorization and authentication is now becoming necessary for many everyday activities such as boarding an aircraft, doing financial transactions etc. This work deals with the possibility of proposing an appropriate method of acquisition, processing and evaluation of data from the tablet itself, focusing on the possibility of obtaining data from the graphics tablet used in conjunction with a personal computer, for the purpose of verifying identity. It contains an overview of biometrics, as independent developing science over the last decades of the 20th century to the present, a summary of the development of a graphics tablet, the current situation, a brief overview of the most popular technologies used in their construction and distribution. Furthermore, it focuses on the design and implementation of appropriate procedures to obtain data provided by the Trust tablet TB - 7300, using available software development kit for the Microsoft Tablet PC, and a comparison of WinForms and WPF model (.NET Framework), with the declaration of suitability for the use of the second one. Last but not least, according to the response from the available set of users, this work focuses on the design of appropriate types of input data, test patterns, method and application for collecting and processing data from the graphic tablet, as well as their use for the verification of the identity of the individual. Ultimately, it is possible to discuss the accuracy of the method on a set of users, its suitability for use and shortcomings. Based on the analysis of the issue, the proposed method can be declared as under-optimal - it is safe, but inaccurate with low stability and repeatability. It is also important to accent that this is just the initial proposal, the use of applications in everyday life is for current phase impossible and the transition from laboratory conditions would require further development and improvement of the process.

This master's thesis deals with fingerprint verification. The theoretical part consist of biometry identification systems and evaluating their reliability and robustness. After that we focus on fingerprints properties needed to identification. We mention several types of fingerprint sensors, which are generaly in public use. In practical part of thesis we deal with enhancement of fingeprint image and methods of identifications. At last we created software for fingeprint identification in programming environment Matlab.

<div>In recent years, developers have used the proliferation of biometric sensors in smart devices, along with recent advances in deep learning, to implement an array of biometrics-based recognition systems. Though these systems demonstrate remarkable performance and have seen wide acceptance, they present unique and pressing security and privacy concerns. One proposed method which addresses these concerns is the elegant, fusion-based Biometric-Capsule (BC) scheme. The BC scheme is provably secure, privacy-preserving, cancellable and interoperable in its secure feature fusion design. </div><div><br></div><div>In this work, we demonstrate that the BC scheme is uniquely fit to secure state-of-the-art facial verification, authentication and identification systems. We compare the performance of unsecured, underlying biometrics systems to the performance of the BC-embedded systems in order to directly demonstrate the minimal effects of the privacy-preserving BC scheme on underlying system performance. Notably, we demonstrate that, when seamlessly embedded into a state-of-the-art FaceNet and ArcFace verification systems which achieve accuracies of 97.18% and 99.75% on the benchmark LFW dataset, the BC-embedded systems are able to achieve accuracies of 95.13% and 99.13% respectively. Furthermore, we also demonstrate that the BC scheme outperforms or performs as well as several other proposed secure biometric methods.</div>

The emergence of the Internet of Things (IoT) brought about the widespread of Body Sensor Networks (BSN) that continuously monitor patients using a collection of tiny-powered and lightweight bio-sensors offering convenience to both physicians and patients in the modern health care environment. Unfortunately, the deployment of bio-sensors in public hacker-prone settings means that they are vulnerable to various security threats exposing the security and privacy of patient information. This thesis presents an authentication scheme for each of two applications of medical sensor networks. The first is an ECC based authentication scheme suitable for a hospital-like setting whereby the patient is hooked up to sensors connected to a medical device such as an ECG monitor while the doctor needs real-time access to continuous sensor readings. The second protocol is a Chebyshev chaotic map-based authentication scheme suitable for deployment on wearable sensors allowing readings from the lightweight sensors connected to patients to be sent and stored on a trusted server while the patient is on the move. We formally and informally proved the security of both schemes. We also simulated both of them on AVISPA to prove their resistance to active and passive attacks. Moreover, we analyzed their performance to show their competitiveness against similar schemes and their suitability for deployment in each of the intended scenarios.

L’objectif de ces travaux de recherche est d’étudier les méthodes d’évaluation de laqualité des images biométriques multimodales sur des échantillons acquis de manièrenon contrainte. De nombreuses s études ont noté l’importance de la qualité del’échantillon pour un système de reconnaissance ou un algorithme de comparaison,puisque la performance du système biométrique est intrinsèquement dépendant dela qualité des images de l’échantillon. Dès lors, la nécessité d’évaluer la qualitédes échantillons biométriques pour plusieurs modalités (empreintes digitales, iris,visage, etc.) est devenue primordiale notamment avec l’apparition de systèmesbiométriques multimodaux de haute précision.Après une introduction présentant un historique de la biométrie et des préceptesliés à la qualité des échantillons biométriques, nous présentons le concept d’évaluationde la qualité des échantillons pour plusieurs modalités. Les normes de qualitéISO / CEI récemment établies pour les empreintes digitales, l’iris et le visage sontprésentées. De plus, des approches d’évaluation de la qualité des échantillons conçuesspécifiquement pour les empreintes digitales avec et sans contact, pour l’iris(dont une image est capturée en proche infrarouge et dans le domaine visible),ainsi que le visage sont étudiées. Finalement, des techniques d’évaluation des performancesdes mesures de qualité des échantillons biométriques sont égalementétudiées.Sur la base des conclusions formulées suite à l’étude des solutions algorithmiques portant sur l’évaluation de la qualité des échantillons biométriques, nous proposonsun cadre commun pour l’évaluation de la qualité d’image biométrique pourplusieurs modalité. Après avoir étudié les attributs de qualité basés sur l’image parmodalité biométrique, nous examinons quelle intersection existe pour l’ensembledes modalités. Ensuite, nous sélectionnons et redéfinissons les attributs de qualitébasés sur l’image qui sont les plus importants afin de définir un cadre commun.Afin de relier ces attributs de qualité aux vrais échantillons biométriques,nous développons une nouvelle base de données de qualité d’image biométriquemulti-modalité qui contient des images échantillons de haute qualité et des imagesdégradées pour l’empreinte digitale acquise sans contact, l’iris (dont l’acquisitionest réalisée dans le spectre visible) et le visage. Les types de dégradation appliquéssont liés aux attributs de qualité qui sont communs aux diverses modalitéset qui sont basés sur l’image. Un autre aspect important du cadre commun proposéest la qualité de l’image et ses applications en biométrie. Nous avons d’abordintroduit et classifié les métriques de qualité d’image existantes, puis effectué unbref aperçu des métriques de qualité d’image sans référence, qui peuvent être appliquéespour l’évaluation de la qualité des échantillons biométriques. De plus, nousétudions comment les mesures de qualité d’image sans référence ont été utiliséespour l’évaluation de la qualité des empreintes digitales, de l’iris et des modalitésbiométriques du visage.Des expériences pour l’évaluation de la performance des métriques de qualitéd’image sans référence sur les images de visage et de l’iris sont effectuées. Lesrésultats expérimentaux indiquent qu’il existe plusieurs métriques qui peuventévaluer la qualité des échantillons biométriques de l’iris et du visage avec un fortcoefficient de correlation. La méthode obtenant les meilleurs résultats en termede performance est ré-entrainée sur des images d’empreintes digitales, ce qui permetd’augmenter significativement les performances du système de reconnaissancebiométrique.À travers le travail réalisé dans cette thèse, nous avons démontré l’applicabilitédes métriques de qualité d’image sans référence pour l’évaluation d’échantillonsbiométriques multi-modalité non contraints. / The aim of this research is to investigate multi-modality biometric image qualityassessment methods for unconstrained samples. Studies of biometrics noted thesignificance of sample quality for a recognition system or a comparison algorithmbecause the performance of the biometric system depends mainly on the qualityof the sample images. The need to assess the quality of multi-modality biometricsamples is increased with the requirement of a high accuracy multi-modalitybiometric systems.Following an introduction and background in biometrics and biometric samplequality, we introduce the concept of biometric sample quality assessment for multiplemodalities. Recently established ISO/IEC quality standards for fingerprint,iris, and face are presented. In addition, sample quality assessment approacheswhich are designed specific for contact-based and contactless fingerprint, nearinfrared-based iris and visible wavelength iris, as well as face are surveyed. Followingthe survey, approaches for the performance evaluation of biometric samplequality assessment methods are also investigated.Based on the knowledge gathered from the biometric sample quality assessmentchallenges, we propose a common framework for the assessment of multi-modalitybiometric image quality. We review the previous classification of image-basedquality attributes for a single biometric modality and investigate what are the commonimage-based attributes for multi-modality. Then we select and re-define themost important image-based quality attributes for the common framework. In order to link these quality attributes to the real biometric samples, we develop anew multi-modality biometric image quality database which has both high qualitysample images and degraded images for contactless fingerprint, visible wavelengthiris, and face modalities. The degradation types are based on the selected commonimage-based quality attributes. Another important aspect in the proposed commonframework is the image quality metrics and their applications in biometrics. Wefirst introduce and classify the existing image quality metrics and then conducteda brief survey of no-reference image quality metrics, which can be applied to biometricsample quality assessment. Plus, we investigate how no-reference imagequality metrics have been used for the quality assessment for fingerprint, iris, andface biometric modalities.The experiments for the performance evaluation of no-reference image qualitymetrics for visible wavelength face and iris modalities are conducted. The experimentalresults indicate that there are several no-reference image quality metricsthat can assess the quality of both iris and face biometric samples. Lastly, we optimizethe best metric by re-training it. The re-trained image quality metric canprovide better recognition performance than the original. Through the work carriedout in this thesis we have shown the applicability of no-reference image qualitymetrics for the assessment of unconstrained multi-modality biometric samples.

The digital world tolerates a high volume of information and interactions. Considering the usage of electronic services by authorities, User Authentication (UA) is crucial. Numerous authentication methods are proposed in the literature; yet, identifying users based on their actual identities with the capability of global usage and respecting privacy is under research. By adopting Blockchain technology in the software industry, the record management systems have satisfied properties such as transparency, accountability, anonymity, and attack resiliency. Moreover, Smartphones are powerful devices capable of hosting a Subscriber Identification Module (SIM) Card that secures the execution of processes involving use of sensitive information. A combination of these technologies is the foundation of a strong UA in cyberspace. In this thesis, we propose the design and prototype of Blockchain-based Global Authentication System (BBGAS) that offers a secure, privacy-preserving, and transparent authentication system based on users' biometrics via Smartphones appropriate for service provider applications.

La Reconnaissance automatique des personnes est devenue un sujet de plus en plus important avec l'augmentation constante des besoins en sécurité. De nombreux systèmes biométriques existent. Ils utilisent différentes caractéristiques humaines. Parmi tous les traits biométriques, la reconnaissance faciale inclut des aspects positifs en termes d'accessibilité et de fiabilité. Dans cette thèse, deux défis en reconnaissance faciales sont étudiés. Le premier est le leurrage. Le leurrage en reconnaissance faciale est présenté. Des contre-mesures permettant d'améliorer les systèmes actuels sont proposés. A cet effet, les attaques basées sur des photographies 2D ou des masques 3D sont analysées. Le second défi exploré dans cette thèse est lié aux variations dues à des altérations du visage (i.e. chirurgie plastique), maquillage et accessoires pour le visage (e.g. occultations par la présence de lunettes). L'impact de ces variations en reconnaissance de visage est étudiée séparément. Ensuite, des techniques robustes contre les variations de camouflage sont proposées. / Human recognition has become an important topic as the need and investments for security applications grow continuously. Numerous biometric systems exist which utilize various human characteristics. Among all biometrics traits, face recognition is advantageous in terms of accessibility and reliability. In the thesis, two challenges in face recognition are analyzed. The first one is face spoofing. Spoofing in face recognition is explained together with the countermeasure techniques that are proposed for the protection of face recognition systems against spoofing attacks. For this purpose, both 2D photograph and 3D mask attacks are analyzed. The second challenge explored in the thesis is disguise variations, which are due to facial alterations, facial makeup and facial accessories (occlusions). The impact of these disguise variations on face recognition is explored, separately. Then, techniques which are robust against disguise variations are proposed.

La reconnaissance biométrique a été utilisée longtemps dans des espaces confinés, généralement à l'intérieur, où les opérations de sécurité exigeaient des systèmes de haute précision, par exemple dans les postes de police, les banques, les entreprises, les aéroports. Les activités de terrain, au contraire, exigent plus de flexibilité et portabilité conduisant au développement de dispositifs pour l'acquisition des traits biométriques et des algorithmes pour la reconnaissance biométrique dans des conditions moins contraintes. L'application de la reconnaissance biométrique "portable" est limitée dans des domaines spécifiques, par exemple pour le contrôle de l'immigration, et exige des dispositifs dédiés. Pour étendre l'utilisation de la biométrie sur les appareils personnels, des tentatives ont été faites par l’intégration des scanners d'empreintes digitales dans les ordinateurs portables ou les smartphones. Mais la reconnaissance biométrique sur les appareils personnels a été utilisée seulement pour un nombre limité de tâches, comme le déverrouillage d'écrans à l'aide des empreintes digitales au lieu de mots de passe. Les activités décrites dans cette thèse se sont portées sur le développement de solutions pour la reconnaissance de l'iris sur les appareils mobiles: - Acquisition: collection de la base de données MICHE, contenant des images d'iris capturée par des appareils mobiles; - Segmentation: développement d'un algorithme de segmentation innovante; - Extraction de caractéristiques: la reconnaissance de l'iris a été combinée avec le visage et la reconnaissance du smartphone.Enfin, la reconnaissance du regard a été étudiée afin de vérifier sa possible fusion avec l'iris / Biometric recognition for a long time has been used in confined spaces, usually indoor, where security-critical operations required high accuracy recognition systems, e.g. in police stations, banks, companies, airports. Field activities, on the contrary, required more portability and flexibility leading to the development of devices for less constrained biometric traits acquisition and consequently of robust algorithms for biometric recognition in less constrained conditions. However, the application of "portable" biometric recognition, was still limited in specific fields e.g. for immigration control, and still required dedicated devices. A further step would be to spread the use of biometric recognition on personal devices, as personal computers, tablets and smartphones. Some attempts in this direction were made embedding fingerprint scanners in laptops or smartphones. So far biometric recognition on personal devices has been employed just for a limited set of tasks, as to unlock the screen using fingerprints instead of passwords. The research activities described in this thesis were focused on studying and developing solutions for iris recognition on mobile devices. This topic has been analyzed in all its main phases: - Acquisition: collection of the MICHE database, containing pictures of irises acquired by mobile devices; - Segmentation: development of an innovative iris segmentation algorithm; - Feature extraction and matching: iris recognition has been combined with the face and with sensor (smartphone) recognition. Finally, the use of gaze analysis for human recognition has been investigated in order to verify its possible fusion with iris.