Identification of an individual from discriminating features of the friction ridge surface is one of the oldest and most commonly used biometric techniques. Methods for identification span from tedious, although highly accurate, manual examination to much faster Automated Fingerprint Identification Systems (AFIS). While automatic fingerprint recognition has grown in popularity due to the speed and accuracy of matching minutia features of good quality plain-to-rolled prints, the performance is less than impressive when matching partial fingerprints. For some applications, including forensic analysis where partial prints come in the form of latent prints, it is not always possible to obtain high-quality image samples. Latent prints, which are lifted from a surface, are typically of low quality and low fingerprint surface area. As a result, the overlapping region in which to find corresponding features in the genuine matching ten-print is reduced; this in turn reduces the identification performance. Image quality also can vary substantially during image capture in applications with a high throughput of subjects having limited training, such as in border control. The rushed image capture leads to an overall acceptable sample being obtained where local image region quality may be low. We propose an improvement to the reliability of features detected in exemplar prints in order to reduce the likelihood of an unreliable overlapping region corresponding with a genuine partial print. A novel approach is proposed for detecting minutiae in low quality image regions. The approach has demonstrated an increase in match performance for a set of fingerprints from a well-known database. While the method is effective at improving match performance for all of the fingerprint images in the database, a more significant improvement is observed for a subset of low quality images. In addition, a novel method for fingerprint analysis using a sequence of fingerprint images is proposed. The approach uses the sequence of images to extract and track minutiae for temporal analysis during a single impression, reducing the variation in image quality during image capture. Instead of choosing a single acceptable image from the sequence based on a global measure, we examine the change in quality on a local level and stitch blocks from multiple images based on the optimal local quality measures. / Ph. D.

Securing information during its storage and transmission is an important and widely addressed issue. Generally, cryptographic techniques are used for information security. Cryptography requires long keys which need to be kept secret in order to protect the information. The drawback of cryptography is that these keys are not strongly linked to the user identity. In order to strengthen the link between the user's identity and his cryptographic keys, biometrics is combined with cryptography. In this thesis, we present various methods to combine biometrics with cryptography. With this combination, we also address the privacy issue of biometric systems: revocability, template diversity, and privacy protection are added to the biometric verification systems. Finally, we also present a protocol for generating and sharing biometrics based crypto-biometric session keys. These systems are evaluated on publicly available iris and face databases

The dissertation investigates the promises and challenges for application of cardiac signals in biometrics and affective computing, and noninvasive measurement of cardiac signals. We have mainly discussed two major cardiac signals: electrocardiogram (ECG), and photoplethysmogram (PPG). ECG and PPG signals hold strong potential for biometric authentications and identifications. We have shown that by mapping each cardiac beat from time domain to an angular domain using a limit cycle, intra-class variability can be significantly minimized. This is in contrary to conventional time domain analysis. Our experiments with both ECG and PPG signal shows that the proposed method eliminates the effect of instantaneous heart rate on the shape morphology and improves authentication accuracy. For noninvasive measurement of PPG beats, we have developed a systematic algorithm to extract pulse rate from face video in diverse situations using video magnification. We have extracted signals from skin patches and then used frequency domain correlation to filter out non-cardiac signals. We have developed a novel entropy based method to automatically select skin patches from face. We report beat-to-beat accuracy of remote PPG (rPPG) in comparison to conventional average heart rate. The beat-to-beat accuracy is required for applications related to heart rate variability (HRV) and affective computing. The algorithm has been tested on two datasets, one with static illumination condition and the other with unrestricted ambient illumination condition. Automatic skin detection is an intermediate step for rPPG. Existing methods always depend on color information to detect human skin. We have developed a novel standalone skin detection method to show that it is not necessary to have color cues for skin detection. We have used LBP lacunarity based micro-textures features and a region growing algorithm to find skin pixels in an image. Our experiment shows that the proposed method is applicable universally to any image including near infra-red images. This finding helps to extend the domain of many application including rPPG. To the best of our knowledge, this is first such method that is independent of color cues. / Ph. D.

La sécurité est un enjeu majeur de notre société numérique. En règle générale, les techniques cryptographiques sont utilisées pour sécuriser l'information avec des clés cryptographiques. Un inconvénient majeur de ces systèmes est le faible lien entre les clés et l’utilisateur. Avec la biométrie on a une preuve plus forte de la présence physique d’un individu, mais ces systèmes possèdent aussi leurs inconvénients, tels que la non-révocabilité ainsi que le potentiel de compromettre notre vie privée. Un axe de recherche multidisciplinaire se profile depuis 1998, la crypto-biométrie. Dans cette thèse des solutions innovantes sont proposées pour améliorer la sécurité tout en protégeant notre vie privée. Plusieurs systèmes crypto-biométriques sont proposés, tels que la biométrie révocable, des systèmes de régénérations de clés crypto-biométriques, ainsi qu’une proposition pratique d’un protocole d'authentification. Ces systèmes sont évaluées sur des bases de données publiques d'images de visage et d'iris / Securing information during its storage and transmission is an important and widely addressed issue. Generally, cryptographic techniques are used for information security. Cryptography requires long keys which need to be kept secret in order to protect the information. The drawback of cryptography is that these keys are not strongly linked to the user identity. In order to strengthen the link between the user's identity and his cryptographic keys, biometrics is combined with cryptography. In this thesis, we present various methods to combine biometrics with cryptography. With this combination, we also address the privacy issue of biometric systems: revocability, template diversity, and privacy protection are added to the biometric verification systems. Finally, we also present a protocol for generating and sharing biometrics based crypto-biometric session keys. These systems are evaluated on publicly available iris and face databases

Made available in DSpace on 2015-03-03T15:48:40Z (GMT). No. of bitstreams: 1 FernandoP_TESE.pdf: 2701691 bytes, checksum: 2a3af30ede2c717ab23b1c7dc03a128a (MD5) Previous issue date: 2013-05-24 / This work discusses the application of techniques of ensembles in multimodal recognition systems development in revocable biometrics. Biometric systems are the future identification techniques and user access control and a proof of this is the constant increases of such systems in current society. However, there is still much advancement to be developed, mainly with regard to the accuracy, security and processing time of such systems. In the search for developing more efficient techniques, the multimodal systems and the use of revocable biometrics are promising, and can model many of the problems involved in traditional biometric recognition. A multimodal system is characterized by combining different techniques of biometric security and overcome many limitations, how: failures in the extraction or processing the dataset. Among the various possibilities to develop a multimodal system, the use of ensembles is a subject quite promising, motivated by performance and flexibility that they are demonstrating over the years, in its many applications. Givin emphasis in relation to safety, one of the biggest problems found is that the biometrics is permanently related with the user and the fact of cannot be changed if compromised. However, this problem has been solved by techniques known as revocable biometrics, which consists of applying a transformation on the biometric data in order to protect the unique characteristics, making its cancellation and replacement. In order to contribute to this important subject, this work compares the performance of individual classifiers methods, as well as the set of classifiers, in the context of the original data and the biometric space transformed by different functions. Another factor to be highlighted is the use of Genetic Algorithms (GA) in different parts of the systems, seeking to further maximize their eficiency. One of the motivations of this development is to evaluate the gain that maximized ensembles systems by different GA can bring to the data in the transformed space. Another relevant factor is to generate revocable systems even more eficient by combining two or more functions of transformations, demonstrating that is possible to extract information of a similar standard through applying different transformation functions. With all this, it is clear the importance of revocable biometrics, ensembles and GA in the development of more eficient biometric systems, something that is increasingly important in the present day / O presente trabalho aborda a aplica??o de t?cnicas de comit?s de classificadores no desenvolvimento de sistemas de reconhecimento multimodais em biometrias revog?veis. Sistemas biom?tricos s?o o futuro das t?cnicas de identifica??o e controle de acesso de usu?rios, prova disso, s?o os aumentos constantes de tais sistemas na sociedade atual. Por?m, ainda existem muitos avan?os a serem desenvolvidos, principalmente no que se refere ? acur?cia, seguran?a e tempo de processamento de tais sistemas. Na busca por desenvolver t?cnicas mais eficientes, os sistemas multimodais e a utiliza??o de biometrias revog?veis mostram-se promissores, podendo contornar muitos dos problemas envolvidos no reconhecimento biom?trico tradicional. Um sistema multimodal ? caracterizado por combinar diferentes t?cnicas de seguran?a biom?trica e com isso, superar muitas limita- ??es, como: falhas de extra??o ou processamento dos dados. Dentre as v?rias possibilidades de se desenvolver um sistema multimodal, a utiliza??o de comit?s de classificadores ? um assunto bastante promissor, motivado pelo desempenho e flexibilidade que os mesmos v?m demonstrando ao longo dos anos, em suas in?meras aplica??es. Dando ?nfase em rela- ??o ? seguran?a, um dos maiores problemas encontrados se deve as biometrias estarem relacionadas permanentemente com o usu?rio e o fato de n?o poderem ser alteradas caso comprometidas. No entanto, esse problema vem sendo solucionado por t?cnicas conhecidas como biometrias revog?veis, as quais consistem em aplicar uma transforma??o sobre os dados biom?tricos de forma a proteger as caracter?sticas originais, possibilitando seu cancelamento e substitui??o. Com o objetivo de contribuir com esse importante tema, esse trabalho compara o desempenho de m?todos de classifica??es individuais, bem como conjunto de classificadores, no contexto dos dados originais e no espa?o biom?trico transformado por diferentes fun??es. Outro fator a se destacar, ? o uso de Algoritmos Gen?ticos (AGs) em diferentes partes dos sistemas, buscando maximizar ainda mais a efici?ncia dos mesmos. Uma das motiva??es desse desenvolvimento ? avaliar o ganho que os sistemas de comit?s maximizados por diferentes AGs podem trazer aos dados no espa?o transformado. Tamb?m busca-se gerar sistemas revog?veis ainda mais eficientes, atrav?s da combina??o de duas ou mais fun??es de transforma??o revog?veis, demonstrando que ? poss?vel extrair informa??es complementares de um mesmo padr?o atrav?s de tais procedimentos. Com tudo isso, fica claro a import?ncia das biometrias revog?veis, comit?s de classificadores e AGs, no desenvolvimento de sistemas biom?tricos mais eficientes, algo que se mostra cada vez mais importante nos dias atuais

M. Tech. (Department of Information and Communication Technology, Faculty of Applied and Computer Sciences), Vaal University of Technology. / Mobile devices are rapidly becoming a key computing platform, transforming how people access business and personal information. Accessing business and personal data using mobile devices requires authentication that is secure. The world is rapidly becoming connected and all users of mobile devices need to be clear regarding individual data security. As a result, biometrics for mobile devices has come into existence. Biometric technology can be applied on mobile devices to improve the trustworthiness of wireless services. Furthermore, it is of great importance and necessary to start paying attention to and investing in mobile biometric technologies, as they are quickly turning into tools of choice for productivity. In the literature review, it shows that few studies measured the acceptance of biometric authentication technology on mobile devices. This study seeks to find out the perceptions as to the acceptance of biometric authentication technology on mobile devices. TAM2 was used as the foundation for generating the hypothesis and developing the conceptual framework for this study. This quantitative study used a survey-based questionnaire to collect data from 305 participants. The simple random sampling technique was used to select participants for this study. The response rate was 98% of the expected population, which was a total of 302 valid responses. A descriptive analysis was deployed to provide a description of respondents’ demographic characteristics. SPSS was used to compute the multiple regressions in order to evaluate the research hypotheses. The findings of this study revealed that perceived humanness, perceived interactivity, perceived social presence, perceived ease of use and subjective social norm, and perceived usefulness and trust are important determinants of customers’ intention to accept and use mobile biometric devices. It was found that reliability is a good predictor of trust. On the other hand privacy, identity theft and combining data are also important determinants of trust. This work can be used to strengthen biometric authentication technology in-cooperation with mobile devices for simplicity of use. Since most mobile devices are used for personal and business information, further research on the acceptance of biometric authentication technology on mobile devices is needed.

The use of mobile devices has extended to all areas of human life and has changed the way people work and socialize. Mobile devices are susceptible to getting lost, stolen, or compromised. Several approaches have been adopted to protect the information stored on these devices. One of these approaches is user authentication. The two most popular methods of user authentication are knowledge based and token based methods but they present different kinds of problems. Biometric authentication methods have emerged in recent years as a way to deal with these problems. They use an individual’s unique characteristics for identification and have proven to be somewhat effective in authenticating users. Biometric authentication methods also present several problems. For example, they aren’t 100% effective in identifying users, some of them are not well perceived by users, others require too much computational effort, and others require special equipment or special postures by the user. Ultimately their implementation can result in unauthorized use of the devices or the user being annoyed by the implementation. New ways of interacting with mobile devices have emerged in recent years. This makes it necessary for authentication methods to adapt to these changes and take advantage of them. For example, the use of touchscreens has become prevalent in mobile devices, which means that biometric authentication methods need to adapt to it. One important aspect to consider when adopting these new methods is their acceptance of these methods by users. The Technology Acceptance Model (TAM) states that system use is a response that can be predicted by user motivation. This work presents an authentication method that can constantly verify the user’s identity which can help prevent unauthorized use of a device or access to sensitive information. The goal was to authenticate people while they used their fingers to interact with their touchscreen mobile devices doing ordinary tasks like vertical and horizontal scrolling. The approach used six biometric traits to do the authentication. The combination of those traits allowed for authentication at the beginning and at the end of a finger stroke. Support Vector Machines were employed and the best results obtained show Equal Error Rate values around 35%. Those results demonstrate the potential of the approach to verify a person’s identity. Additionally, this works tested the acceptance of the approach among participants, which can influence its eventual adoption. An acceptance level of 80% was obtained which compares favorably against other behavioral biometric approaches.

Encephalogram (EEG) devices are one of the active research areas in human-computer interaction (HCI). They provide a unique brain-machine interface (BMI) for interacting with a growing number of applications. EEG devices interface with computational systems, including traditional desktop computers and more recently mobile devices. These computational systems can be targeted by malicious users. There is clearly an opportunity to leverage EEG capabilities for increasing the efficiency of access control mechanisms, which are the first line of defense in any computational system. Access control mechanisms rely on a number of authenticators, including “what you know”, “what you have”, and “what you are”. The “what you are” authenticator, formally known as a biometrics authenticator, is increasingly gaining acceptance. It uses an individual’s unique features such as fingerprints and facial images to properly authenticate users. An emerging approach in physiological biometrics is cognitive biometrics, which measures brain’s response to stimuli. These stimuli can be measured by a number of devices, including EEG systems. This work shows an approach to authenticate users interacting with their computational devices through the use of EEG devices. The results demonstrate the feasibility of using a unique hard-to-forge trait as an absolute biometrics authenticator by exploiting the signals generated by different areas of the brain when exposed to visual stimuli. The outcome of this research highlights the importance of the prefrontal cortex and temporal lobes to capture unique responses to images that trigger emotional responses. Additionally, the utilization of logarithmic band power processing combined with LDA as the machine learning algorithm provides higher accuracy when compared against common spatial patterns or windowed means processing in combination with GMM and SVM machine learning algorithms. These results continue to validate the value of logarithmic band power processing and LDA when applied to oscillatory processes.

E-learning has grown to such an extent that paper-based testing is being replaced by computer-based testing otherwise known as e-exams. Because these e-exams can be delivered outside of the traditional proctored environment, additional authentication measures must be employed in order to offer similar authentication assurance as found in proctored, paper-based testing. This dissertation addressed the need for valid authentication in e-learning systems, in e-examinations in particular, and especially in professional certification e-examinations. Furthermore, this dissertation proposed a more robust method for learner authentication during e-examination taking. Finally, this dissertation extended e-learning research by comparing e-examination scores and durations of three separate groups of exam takers using different authentication methods: Online Using Username/Password (OLUP), In-Testing Center (ITC), and Online with Multibiometrics (OLMB) to better understand the role as well as the possible effect of continuous and dynamic multibiometric authentication on professional certification e-examination scores and durations. The sample used in this study was based on participants who were all professional members of a technology professional certification organization. The methodology used to collect data was a posttest only, multiple, non-equivalent groups quasi-experiment, where age, gender, and Information Technology Proficiency (ITP) were also recorded. The analyses performed in this study included pre-analysis data screening, reliability analyses for each instrument used, and the main analysis to address each hypothesis. Group affiliation, i.e. type of authentication methods, was found to have no significant effect on differences among exam scores and durations. While there was a clear path of increased mean e-examination score as authentication method was relaxed, it was evident from the analysis that these were not significant differences. Age was found to have a significant effect on exam scores where younger participants were found to have higher exam scores and lower exam durations than older participants. Gender was not found to have a significant effect on exam scores nor durations. ITP was found to have a significant effect on exam scores and durations where greater scores with the ITP instrument indicated greater exam scores and lower exam durations. This study's results can help organizations better understand the role, possible effect, and potential application of continuous and dynamic multibiometric authentication as a justifiable approach when compared with the more common authentication approach of User Identifier (UID) and password, both in professional certification e-examinations as well as in an online environment.

This thesis is about the relationship between human bodies and instrumental technologies that can be use to measure them. It adopts the position that instruments are technological structures that evoke and manifest particular phenomena of embodied life. However, through their history of association and use in the sciences and scientific medicine, instruments tend to be attached to a particular ontology, that of mechanical objectivity. Embarking from research into the artistic uses of physiological sensor technology in creative practices such as performance and installation art, this thesis asks whether it is possible to use instruments in a way that departs from their association with scientific objectivity. Drawing on philosophers who have developed an understanding of the relationship of instrumental technologies and human bodies as co-constructive, it explores how this model of con-construction might be understood to offer an alternative ontology for understanding the use of instruments in practices outside of science and scientific medicine. The project is therefore suggestive of degrees of freedom and flexibility that are open to exploitation by creative practices in the realm of instrumentation as an alternative to orthodox rationalisations of the value of scientific equipment as authentic, revealing and objective. The major contribution of the thesis is that transfers and synthesises arguments and evidence from the history and philosophy of sciences that serve to demonstrate how the instrumental measurement of human bodies can be considered to be a form of creative practice. It assembles a position based on the work of thinkers from a number of disciplines, particularly philosophy of science, technology, and the medical humanities. These offer examples of ontological frameworks within which the difference between the realm of the instrumental, material, biological, and the objective, and the phenomenal, meaningful and subjective, might be collapsed. Doing this, the thesis sheds light on how physical devices might enter into the interplay of making, mattering and objectifying the immaterial, a realm that it might be considered the role of artists to manifest. Drawing on contemporary, and secondary, accounts of the development of empirical testing in the medical sciences, the thesis agues for the recovery of a romantic account of human physiology, in which the imagination and meaning are active and embodied. It therefore offers to link the bodily and the instrumental through an extended-materialist account in which the physiological, rather than the psychological, is central. Developing a response to constructionist models of the body and instrumentation, the thesis concludes that a model of the poetic may be adopted as a method for understanding the opportunities and imperatives inherent in the avoidance of deterministic approaches to biosignalling technologies. In doing this, the thesis contributes particularly to the creative arts and technology research practices concerned with the use of body sensor technologies in humanistic applications. It complements the existing works by artists in this area that make use of instruments by assembling a number of theoretical readings and interpretations of how instruments work – among them the thermometer, lie detector, and automatograph – which illustrate the argument that that is possible to operate from a theoretical position within which instruments are both material, performative and symbolic.