With the advance of the modern information society, the importance of reliable identity authentication has increased dramatically. Using biometrics as a means for verifying the identity of a person increases both the security and the convenience of the systems. By using yourself to verify your identity such risks as lost keys and misplaced passwords are removed and by virtue of this, convenience is also increased. The most mature and well-developed biometric technique is fingerprint recognition. Fingerprints are unique for each individual and they do not change over time, which is very desirable in this application. There are multitudes of approaches to fingerprint recognition, most of which work by identifying so called minutiae and match fingerprints based on these. In this diploma work, two alternative methods for locating distinct features in fingerprint images have been evaluated. The Template Correlation Method is based on the correlation between the image and templates created to approximate the homogenous ridge/valley areas in the fingerprint. The high-dimension of the feature vectors from correlation is reduced through principal component analysis. By visualising the dimension reduced data by ordinary plotting and observing the result classification is performed by locating anomalies in feature space, where distinct features are located away from the non-distinct. The Circular Sampling Method works by sampling in concentric circles around selected points in the image and evaluating the frequency content of the resulting functions. Each images used here contains 30400 pixels which leads to sampling in many points that are of no interest. By selecting the sampling points this number can be reduced. Two approaches to sampling points selection has been evaluated. The first restricts sampling to occur only along valley bottoms of the image, whereas the second uses orientation histograms to select regions where there is no single dominant direction as sampling positions. For each sampling position an intensity function is achieved by circular sampling and a frequency spectrum of this function is achieved through the Fast Fourier Transform. Applying criteria to the relationships of the frequency components classifies each sampling location as either distinct or non-distinct. Using a cyclic approach to evaluate the methods and their potential makes selection at various stages possible. Only the Circular Sampling Method survived the first cycle, and therefore all tests from that point on are performed on thismethod alone. Two main errors arise from the tests, where the most prominent being the number of spurious points located by the method. The second, which is equally serious but not as common, is when the method misclassifies visually distinct features as non-distinct. Regardless of the problems, these tests indicate that the method holds potential but that it needs to be subject to further testing and optimisation. These tests should focus on the three main properties of the method: noise sensitivity, radial dependency and translation sensitivity.

In the age of a networking revolution, when the Internet has changed not only the way we see computing, but also the whole society, we constantly face new challenges in the area of user verification. It is often the case that the login-id password pair does not provide a sufficient level of security. Other, more sophisticated techniques are used: one-time passwords, smart cards or biometric identity verification. The biometric approach is considered to be one of the most secure ways of authentication. On the other hand, many biometric methods require additional hardware in order to sample the corresponding biometric feature, which increases the costs and the complexity of implementation. There is however one biometric technique which does not demand any additional hardware – user identification based on keyboard statistics. This thesis is focused on this way of authentication. The keyboard statistics approach is based on the user’s unique typing rhythm. Not only what the user types, but also how she/he types is important. This report describes the statistical analysis of typing samples which were collected from 20 volunteers, as well as the implementation and testing of the identity verification system, which uses the characteristics examined in the experimental stage.

Computer security is becoming an increasingly important topic in today’s society, withever increasing connectivity between devices and services. Stolen passwords have thepotential to cause severe damage to companies and individuals alike, leading to therequirement that the security system must be able to detect and prevent fraudulentlogin. Keystroke biometrics is the study of the typing behavior in order to identifythe typist, using features extracted during typing. The features traditionally used inkeystroke biometrics are linear combinations of the timestamps of the keystrokes.This work focuses on feature learning methods and is based on the Carnegie Mellonkeystroke data set. The aim is to investigate if other feature extraction methods canenable improved classification of users. Two methods are employed to extract latentfeatures in the data: Pre-training of an artificial neural network classifier and an autoencoder. Several tests are devised to test the impact of pre-training and compare theresults of a similar network without pre-training. The effect of feature extraction withan autoencoder on a classifier trained on the autoencoder features in combination withthe conventional features is investigated.Using pre-training, I find that the classification accuracy does not improve when using an adaptive learning rate optimizer. However, when a stochastic gradient descentoptimizer is used the accuracy improves by about 8%. Used in conjunction with theconventional features, the features extracted with an autoencoder improve the accuracyof the classifier with about 2%. However, a classifier based on the autoencoder featuresalone is not better than a classifier based on conventional features.

Abstract In the last decades, face recognition systems have evolved a lot in terms of performance. As a result, this technology is now considered as mature and is applied in many real world applications from border control to financial transactions and computer security. Yet, many studies show that these systems suffer from vulnerabilities to spoofing attacks, a weakness that may limit their usage in many cases. A face spoofing attack or presentation attack occurs when someone tries to masquerade as someone else by presenting a fake face in front of the face recognition camera. To protect the recognition systems against attacks of this kind, many face anti-spoofing methods have been proposed. These methods have shown good performances on the existing face anti-spoofing databases. However, their performances degrade drastically under real world variations (e.g., illumination and camera device variations). In this thesis, we concentrate on improving the generalization capabilities of the face anti-spoofing methods with a particular focus on the texture based techniques. In contrast to most existing texture based methods aiming at extracting texture features from gray-scale images, we propose a joint color-texture analysis. First, the face images are converted into different color spaces. Then, the feature histograms computed over each image band are concatenated and used for discriminating between real and fake face images. Our experiments conducted on three color spaces: RGB, HSV and YCbCr show that extracting the texture information from separated luminance chrominance color spaces (HSV and YCbCr) yields to better performances compared to gray-scale and RGB image representations. Moreover, to deal with the problem of illumination and image-resolution variations, we propose to extract this texture information from different scale images. In addition to representing the face images in different scales, the multi-scale filtering methods also act as pre-processing against factors such as noise and illumination. Although our obtained results are better than the state of the art, they are still far from the requirements of real world applications. Thus, to help in the development of robust face anti-spoofing methods, we collected a new challenging face anti-spoofing database using six camera devices in three different illumination and environmental conditions. Furthermore, we have organized a competition on the collected database where fourteen face anti-spoofing methods have been assessed and compared. / Tiivistelmä Kasvontunnistusjärjestelmien suorituskyky on parantunut huomattavasti viime vuosina. Tästä syystä tätä teknologiaa pidetään nykyisin riittävän kypsänä ja käytetään jo useissa käytännön sovelluksissa kuten rajatarkastuksissa, rahansiirroissa ja tietoturvasovelluksissa. Monissa tutkimuksissa on kuitenkin havaittu, että nämä järjestelmät ovat myös haavoittuvia huijausyrityksille, joissa joku yrittää esiintyä jonakin toisena henkilönä esittämällä kameralle jäljennöksen kohdehenkilön kasvoista. Tämä haavoittuvuus rajoittaa kasvontunnistuksen laajempaa käyttöä monissa sovelluksissa. Tunnistusjärjestelmien turvaamiseksi on kehitetty lukuisia menetelmiä tällaisten hyökkäysten torjumiseksi. Nämä menetelmät ovat toimineet hyvin tätä tarkoitusta varten kehitetyillä kasvotietokannoilla, mutta niiden suorituskyky huononee dramaattisesti todellisissa käytännön olosuhteissa, esim. valaistuksen ja käytetyn kuvantamistekniikan variaatioista johtuen. Tässä työssä yritämme parantaa kasvontunnistuksen huijauksen estomenetelmien yleistämiskykyä keskittyen erityisesti tekstuuripohjaisiin menetelmiin. Toisin kuin useimmat olemassa olevat tekstuuripohjaiset menetelmät, joissa tekstuuripiirteitä irrotetaan harmaasävykuvista, ehdotamme väritekstuurianalyysiin pohjautuvaa ratkaisua. Ensin kasvokuvat muutetaan erilaisiin väriavaruuksiin. Sen jälkeen kuvan jokaiselta kanavalta erikseen lasketut piirrehistogrammit yhdistetään ja käytetään erottamaan aidot ja väärät kasvokuvat toisistaan. Kolmeen eri väriavaruuteen, RGB, HSV ja YCbCr, perustuvat testimme osoittavat, että tekstuuri-informaation irrottaminen HSV- ja YCbCr-väriavaruuksien erillisistä luminanssi- ja krominanssikuvista parantaa suorituskykyä kuvien harmaasävy- ja RGB-esitystapoihin verrattuna. Valaistuksen ja kuvaresoluution variaation takia ehdotamme myös tämän tekstuuri-informaation irrottamista eri tavoin skaalatuista kuvista. Sen lisäksi, että itse kasvot esitetään eri skaaloissa, useaan skaalaan perustuvat suodatusmenetelmät toimivat myös esikäsittelynä sellaisia suorituskykyä heikentäviä tekijöitä vastaan kuten kohina ja valaistus. Vaikka tässä tutkimuksessa saavutetut tulokset ovat parempia kuin uusinta tekniikkaa edustavat tulokset, ne ovat kuitenkin vielä riittämättömiä reaalimaailman sovelluksissa tarvittavaan suorituskykyyn. Sen takia edistääksemme uusien robustien kasvontunnistuksen huijaamisen ilmaisumenetelmien kehittämistä kokosimme uuden, haasteellisen huijauksenestotietokannan käyttäen kuutta kameraa kolmessa erilaisessa valaistus- ja ympäristöolosuhteessa. Järjestimme keräämällämme tietokannalla myös kansainvälisen kilpailun, jossa arvioitiin ja verrattiin neljäätoista kasvontunnistuksen huijaamisen ilmaisumenetelmää.

Concerns over Information Technology security, including theft, fraud and abuse have forced organizations to take a cautious approach to Electronic Commerce. This research study suggests that organizations can keep secure their resources by implementing an effective and accurate identification system, which will enable them to provide a better service to their customers and to prevent individuals from misrepresenting themselves to the organization. Various means of identification are available, but the key focus should be to establish accurate identity. The research study addresses biometric identification methods as a means of improving the security of on-line transactions. The specific focus is an investigation of user perceptions with regard to biometric identification methods. The research study, through a theoretical understanding of the concepts found within the research problem statement, compiles a Technology Adoption Model for understanding why individuals accept or reject Information Technology innovations, which has proved to be one of the most challenging issues in Information Technology research. The exploratory field study section of the research study makes use of interpretive research as a basis to identify various themes related to user perceptions of biometrics. The themes identified are discussed during a focus group session with research participants. The main focus of the exploratory field study section is on user perceptions related to biometric identification methods and to enhance the Technology Adoption Model compiled by gathering user perceptions regarding the Internet, Electronic Business, biometrics and user adoption via a questionnaire to provide a possible solution for the research study problem statement. From the exploratory field study, it was concluded that user perceptions will play a role with regard to identification through biometrics within Electronic Business and that the social factors trust, security, and privacy considerations will also have to be taken into account. / Dissertation (MCom Informatics)--University of Pretoria, 2005. / Informatics / unrestricted

This dissertation develops an innovative approach towards less-constrained iris biometrics. Two major contributions are made in this research endeavor: (1) Designed an award-winning segmentation algorithm in the less-constrained environment where image acquisition is made of subjects on the move and taken under visible lighting conditions, and (2) Developed a pioneering iris biometrics method coupling segmentation and recognition of the iris based on video of moving persons under different acquisitions scenarios. The first part of the dissertation introduces a robust and fast segmentation approach using still images contained in the UBIRIS (version 2) noisy iris database. The results show accuracy estimated at 98% when using 500 randomly selected images from the UBIRIS.v2 partial database, and estimated at 97% in a Noisy Iris Challenge Evaluation (NICE.I) in an international competition that involved 97 participants worldwide involving 35 countries, ranking this research group in sixth position. This accuracy is achieved with a processing speed nearing real time. The second part of this dissertation presents an innovative segmentation and recognition approach using video-based iris images. Following the segmentation stage which delineats the iris region through a novel segmentation strategy, some pioneering experiments on the recognition stage of the less-constrained video iris biometrics have been accomplished. In the video-based and less-constrained iris recognition, the test or subject iris videos/images and the enrolled iris images are acquired with different acquisition systems. In the matching step, the verification/identification result was accomplished by comparing the similarity distance of encoded signature from test images with each of the signature dataset from the enrolled iris images. With the improvements gained, the results proved to be highly accurate under the unconstrained environment which is more challenging. This has led to a false acceptance rate (FAR) of 0% and a false rejection rate (FRR) of 17.64% for 85 tested users with 305 test images from the video, which shows great promise and high practical implications for iris biometrics research and system design.

Equipamentos médicos equipados com interface de rede, classificados como sensores, transmitem informações sensíveis sobre a rede, constituindo uma rede de sensores. Essa rede pode ser utilizada para o acompanhamento remoto de pacientes a domicílio, com a finalidade de propiciar comodidade ao paciente. As informações provenientes desses sensores são vulneráveis, necessitando assim de fortes mecanismos de segurança. Devido às vulnerabilidades, métodos mais eficazes de autenticação vêm sendo desenvolvidos. Porém, as soluções de autenticação existentes obrigam a interação direta dos usuários com o sistema, não respeitando suas individualidades. Dessa forma, esta dissertação propõe uma solução de autenticação forte a qual retira a necessidade de interação do usuário com o sistema, baseando-se nos fatores de biometria e localização. O autenticador desenvolvido, foi testado através de estudos de casos distintos para mostrar sua eficiência e viabilidade para utilização em um ambiente real. / Medical devices equipped with network interfaces, classified as sensors, transmit sensitive information through the network and form a sensor network. This network can be used to monitor patients at home remotely. The information from these sensors is vulnerable and requires strong security mechanisms. Because of vulnerabilities, more effective authentication methods have been developed. However, the current authentication solutions require direct interaction of the user with the system, which does not respect their individuality. Thus, this dissertation proposes a strong authentication solution in which the interaction of the user with the system is removed based on biometrics and location factors. The developed authenticator was tested through different case studies to show its efficiency and feasibility before application in a real environment.

No presente trabalho são abordados estudos sobre elementos do projeto conceitual de um sistema de controle de acessos de pessoas a áreas industriais, voltado para o propósito de oferecer contribuição para o segmento particular daqueles tipos que exigem a utilização de automatização para atender a respectiva viabilização operacional relativa às atividades pertinentes ao controle de acessos em questão. Os testes práticos realizados com protótipos apresentaram resultados satisfatórios, validando os princípios de funcionamento dos elementos envolvidos, haja vista que foram verificadas as realizações das operações previstas pelo sistema que possui as características de: identificação por radiofrequência fundamentada em tecnologia voltada para aplicações de identificação à curta distância com leitor fixo e transponder read-only, identificação por biometria da impressão digital fundamentada em tecnologia de captura de imagem com utilização de leitura óptica; utilização de equipamentos para controle físico do acesso de pessoas, cujas previsões de instalação permitam atender fluxos nos sentidos unidirecional e bidirecional com relação a área controlada; aplicação de recursos disponíveis por Web Services para atendimento das necessidades afins exigidas para o desenvolvimento do sistema; segurança no transporte de dados fundamentada na utilização do protocolo SSL; estações de trabalho e servidores constituídos por computadores pessoais com arquitetura Intel ou compatível; utilização de elementos de integração de sistemas direcionados para a abrangência de sistemas computacionais empresariais empregados em indústrias. O objetivo proposto foi atingido, sendo que os testes práticos validaram os princípios de funcionamento dos elementos abordados, oferecendo contribuição para o mencionado segmento de sistemas de controle de acessos de pessoas. / The present work discusses studies about conceptual design elements to personal access control system to industrial areas. It aims at offering a contribution to enhance people control to areas with the use of automation resources. Practical template tests undertaken presented satisfactory results, thus validating their working principles and technological achievements of the operations previews of the system characteristics: radiofrequency identification based on the technology of short distance identification with fixed reader and `read-only transponder; biometric identification based on image capture using optical reading; equipment for controlling personal physical access , whose installation would permit unidirectional and bidirectional flows to the controlled area; use of resources available by Web Services to meet the needs to system development; data transport safety based on SSL protocol; work station and servers of the Intel type personal computers, or compatible; systems integration with corporate computer systems. The proposed goal has been achieved, and the practical tests confirmed the operational principles of the elements in question, offering contributions to the automated control systems of personal access in industrial areas.

Traditional authentication methods like Personal Identification Number (PIN) are getting obsolete and insecure for electronic-payments while mobile-payments are becoming more and more popular. Biometrics such as fingerprint and face recognition authentication methods seem to be a solution to this security issue as they are becoming a regular and integrated part of an average smartphone end-users purchase. However, for mobile-payments to be authenticated by biometrics, end-users acceptability of both technologies must be high. In this research, fingerprint and face recognition authentication methods are being tested with end-users and their current acceptability level is being determined based on interviews which are conducted upon finishing each testing scenario. The interview is using 39 questions which are determining previous usage of the technologies, their likeability, positives, negatives, and feelings about various features biometrics provide such as ease-of-use, stress-free method of payment, security, and many others. Additionally, one more authentication method is tested, namely two factor authentication consisting of one biometric method (fingerprint) and one traditional method (PIN) of authentication. The main goal for testing this method is to find out whether implementing (as currently it is not available) such technology into mobile-payments would be beneficial and how it scored in user-acceptance next to fingerprint and face recognition authentication methods. Once the user-acceptance level is determined the main reasons for it are presented. Last but not least, suggestions for improvements in this domain are presented so that biometrics are even more accepted by end-users who are performing mobile-payments on their smartphones.

Tato disertační práce se zabývá biometrickým a medicínským zařízením pro simultánní snímání duhovky a sítnice oka v jednom kroku. V případě biometrického zaměření je práce rozšířena o vzájemnou fúzi těchto dvou biometrik do jedné šablony, kdy multimodální systém vykazuje mnohem lepší parametry než systém unimodální, a to především ve větší unikátnosti, univerzálnosti a velmi obtížně proveditelnému útoku (až téměř nemožnému) na senzor. V případě medicínského využití práce dále rozvíjí detekci a klasifikaci nemocí pro základ expertního systému pro oftalmologické účely, který bude umožňovat pomoc lékaři při stanovení diagnózy nálezu v obrazu sítnice (či duhovky) oka.