CO-CREATING REQUIREMENTS FOR THE EMERGING ELECTRONIC IDENTITY MANAGEMENT PLATFORM

Digital transformation of public sector entails prominence to electronic identity (e-ID) management platforms. The new, user-centric systems for e-ID management can be enhanced with Artificial intelligence (AI) and distributed ledger technology (DLT). However, such technological complexity can make these systems counter-intuitive for an ordinary user. Existing research identifies that the socio-technical arrangements for e-ID platforms are often ignored. In this study, we investigate what kind of requirements users have for an e-ID management platform in public sector. We employed principles of cocreation methodology to design and run a series of workshops in five European municipalities. Despite technological propositions of an e-ID platform, accessibility, usability, and security attributes were the most debated issues among the prospective users. The results from the co-creative requirements elicitation suggest for broadening the discussions around e-ID management platforms to encompass social and socio-technical aspects in the design and development of these systems

An overview of touchless 2D fingerprint recognition

Touchless fingerprint recognition represents a rapidly growing field of research which has been studied for more than a decade. Through a touchless acquisition process, many issues of touch-based systems are circumvented, e.g., the presence of latent fingerprints or distortions caused by pressing fingers on a sensor surface. However, touchless fingerprint recognition systems reveal new challenges. In particular, a reliable detection and focusing of a presented finger as well as an appropriate preprocessing of the acquired finger image represent the most crucial tasks. Also, further issues, e.g., interoperability between touchless and touch-based fingerprints or presentation attack detection, are currently investigated by different research groups. Many works have been proposed so far to put touchless fingerprint recognition into practice. Published approaches range from self identification scenarios with commodity devices, e.g., smartphones, to high performance on-the-move deployments paving the way for new fingerprint recognition application scenarios.This work summarizes the state-of-the-art in the field of touchless 2D fingerprint recognition at each stage of the recognition process. Additionally, technical considerations and trade-offs of the presented methods are discussed along with open issues and challenges. An overview of available research resources completes the work

TrustPass Blockchain based Trusted Digital Identity Platform towards Digital Transformation

According to the United States Census Bureau, by June 2019 world population on earth was 7.5 billion, which exceeds the world population of 7.2 billion as of 2015. Each of these citizens needs to prove their identity in order to fulfill their day-to-day routine. In this current digital revolution whole world is transforming to digitalization. Therefore, proving someones identity in the digital space is a must, because being able to track a person digitally can result in elimination of the identity theft and most incidents related to online harassments, while focusing on data privacy and security of citizens, we have proposed Trust Pass: Cyber Security Intelligence based trusted digital identity platform capable of registering and verifying service providers based on document validation neural network model (95.4% accuracy) and allowing citizens to authenticate themselves to service providers with three factor biometrics authentication with liveness detection neural network model (99.8% accuracy)

Usability in biometric recognition systems

Mención Internacional en el título de doctorBiometric recognition, which is a technology already mature, grows nowadays in several contexts, including forensics, access controls, home automation systems, internet, etc. Now that technology is moving to mobile scenarios, biometric recognition is being also integrated in smartphones, tablets and other mobile devices as a convenient solution for guaranteeing security, complementing other methods such as PIN or passwords. Nevertheless, the use of biometric recognition is not as spread as desired and it is still unknown for a wide percentage of the population. It has been demonstrated [1] that some of the possible reasons for the slow penetration of biometrics could be related to usability concerns. This could lead to various drawbacks like worst error rates due to systems misuses and it could end with users rejecting the technology and preferring other approaches. This Thesis is intended to cover this topic including a study of the current state of the art, several experiments analysing the most relevant usability factors and modifications to a usability evaluation methodology. The chosen methodology is the H-B interaction, carried out by Fernandez-Saavedra [2], based on the ISO/IEC 19795 [3], the HBSI [4], the ISO 9241-210 [5] and on Common Criteria [6]. Furthermore, this work is focused on dealing with accessibility concerns in biometric recognition systems. This topic, usually included into the usability field, has been addressed here separately, though the study of the accessibility has followed the same steps as the usability study: reviewing the state of the art, pointing and analysing the main influential factors and making improvements to the state of the art. The recently published standard EN 301 549 – “Accessibility requirements suitable for public procurement of ICT products and services in Europe” [7] has been also analysed. These two topics have been overcome through the well-known user-centric-design approach. In this way, first the influential factors have been detected. Then, they have been isolated (when possible) and measured. The results obtained have been then interpreted to suggest new updates to the H-B interaction. This 3-steps approach has been applied cyclically and the factors and methodology updated after each iteration. Due to technology and usability trends, during this work, all the systems/applications developed in the experiments have been thought to be mobile directly or indirectly. The biometric modalities used during the experiments performed in this Thesis are those pointed as suitable for biometric recognition in mobile devices: handwritten recognition signature, face and fingerprint recognition. Also, the scenarios and the applications used are in line with the main uses of biometrics in mobile environments, such as sign documents, locking/unlocking devices, or make payments. The outcomes of this Thesis are intended to guide future developers in the way of designing and testing proper usable and accessible biometrics. Finally, the results of this Thesis are being suggested as a new International Standard within ISO/IEC/JTC1/SC37 – Biometric Recognition, as standardization is the proper way of guaranteeing usability and accessibility in future biometric systems. The contributions of this Thesis include: • Improvements to the H-B interaction methodology, including several usability evaluations. • Improvements on the accessibility of the ICT (Information and Communications Technology) products by means of the integration of biometric recognition systems • Adaptation and application of the EN 301 549 to biometric recognition systems.El reconocimiento biométrico, que es una tecnología ya madura, crece hoy en día en varios contextos, incluyendo la medicina forense, controles de acceso, sistemas de automatización del hogar, internet, etc. Ahora que la tecnología se está moviendo a los escenarios móviles, el reconocimiento biométrico está siendo también integrado en los teléfonos inteligentes, tabletas y otros dispositivos móviles como una solución conveniente para garantizar la seguridad, como complemento de otros métodos de seguridad como el PIN o las contraseñas. Sin embargo, el uso del reconocimiento biométrico es todavía desconocido para un amplio porcentaje de la población. Se ha demostrado [1] que algunas de las posibles razones de la lenta penetración de la biometría podrían estar relacionadas con problemas de usabilidad. Esto podría dar lugar a diversos inconvenientes, ofreciendo un rendimiento por debajo de lo esperado debido al mal uso de los sistemas y podría terminar con los usuarios rechazando la tecnología y prefiriendo otros enfoques. Esta tesis doctoral trata este tema incluyendo un estudio del estado actual de la técnica, varios experimentos que analizan los factores de usabilidad más relevantes y modificaciones a una metodología de evaluación de la usabilidad, la "H-B interaction" [2] basada en la ISO / IEC 19795 [3], el HBSI [4], la ISO 9241 [5] y Common Criteria [6]. Además, este trabajo se centra también en los problemas de accesibilidad de los sistemas de reconocimiento biométrico. Este tema, que por lo general se incluye en el campo de la usabilidad, se ha tratado aquí por separado, aunque el estudio de la accesibilidad ha seguido los mismos pasos que el estudio de usabilidad: revisión del estado del arte, análisis de los principales factores influyentes y propuesta de cambios en la metodología H-B interaction. Han sido también analizados los requisitos de accesibilidad para las Tecnologías de la Información y la Comunicación (TIC) en Europa, bajo la norma EN 301 549 [7]. Estos dos temas han sido estudiados a través de un enfoque centrado en el usuario (User Centric Design - UCD). De esta manera, se han detectado los factores influyentes. A continuación, dichos factores han sido aislados (cuando ha sido posible) y medidos. Los resultados obtenidos han sido interpretados para sugerir nuevos cambios a la metodología H-B interaction. Este enfoque de 3 pasos se ha aplicado de forma cíclica a los factores y a la metodología después de cada iteración. Debido a las tendencias tecnológicas y de usabilidad, durante este trabajo, todos los sistemas / aplicaciones desarrolladas en los experimentos se han pensado para ser móviles, directa o indirectamente. Las modalidades utilizadas durante los experimentos realizados en esta tesis doctoral son las que se señalaron como adecuados para el reconocimiento biométrico en dispositivos móviles: la firma manuscrita, la cara y el reconocimiento de huellas dactilares. Además, los escenarios y las aplicaciones utilizadas están en línea con los principales usos de la biometría en entornos móviles, como la firma de documentos, el bloqueo / desbloqueo de dispositivos, o hacer pagos. Los resultados de esta tesis tienen como objetivo orientar a los futuros desarrolladores en el diseño y evaluación de la usabilidad y la accesibilidad en los sistemas de reconocimiento biométrico. Por último, los resultados de esta tesis doctoral se sugerirán como un nuevo estándar de ISO / IEC / JTC1 / SC37 - Biometric Recognition, ya que la normalización es la manera adecuada de garantizar la usabilidad y la accesibilidad en los futuros sistemas biométricos. Las contribuciones de esta tesis incluyen: • Mejora de la metodología de evaluación H-B interaction, incluyendo varias evaluaciones de usabilidad. • Mejora de la accesibilidad de los sistemas de información / electrónicos mediante la integración de sistemas biométricos y varias evaluaciones. • Adaptación y aplicación de la norma de accesibilidad EN 301 549 al campo de los sistemas biométricos.Programa Oficial de Doctorado en Ingeniería Eléctrica, Electrónica y AutomáticaPresidente: Patrizio Campisi.- Secretario: Enrique Cabellos Pardo.- Vocal: Marcos Faundez Zanu

A First Look Into Users’ Perceptions of Facial Recognition in the Physical World

Facial recognition (FR) technology is being adopted in both private and public spheres for a wide range of reasons, from ensuring physical safety to providing personalized shopping experiences. It is not clear yet, though, how users perceive this emerging technology in terms of usefulness, risks, and comfort. We begin to address these questions in this paper. In particular, we conducted a vignette-based study with 314 participants on Amazon Mechanical Turk to investigate their perceptions of facial recognition in the physical world, based on thirty-five scenarios across eight different contexts of FR use. We found that users do not have a binary answer towards FR adoption. Rather, their perceptions are grounded in the specific contexts in which FR will be applied. The participants considered a broad range of factors, including control over facial data, the utility of FR, the trustworthiness of organizations using FR, and the location and surroundings of FR use to place the corresponding privacy risks in context. They weighed the privacy risks with the usability, security, and economic gain of FR use as they reported their perceptions. Participants also noted the reasons and rationals behind their perceptions of facial recognition, which let us conduct an in-depth analysis of their perceived benefits, concerns, and comfort with using this technology in various scenarios. Through this first systematic look into users’ perceptions of facial recognition in the physical world, we shed light on the tension between FR adoption and users’ concerns. Taken together, our findings have broad implications that advance the Privacy and Security community’s understanding of FR through the lens of users, where we presented guidelines for future research in these directions

A Performance Assessment Framework for Mobile Biometrics

This project aims to develop and explore a robust framework for assessing biometric systems on mobile platforms, where data is often collected in non-constrained, potentially challenging environments. The framework enables the performance assessment given a particular platform, biometric modality, usage environment, user base and required security level. The ubiquity of mobile devices such as smartphones and tablets has increased access to Internet-based services across various scenarios and environments. Citizens use mobile platforms for an ever-expanding set of services and interactions, often transferring personal information, and conducting financial transactions. Accurate identity authentication for physical access to the device and service is, therefore, critical to ensure the security of the individual, information, and transaction. Biometrics provides an established alternative to conventional authentication methods. Mobile devices offer considerable opportunities to utilise biometric data from an enhanced range of sensors alongside temporal information on the use of the device itself. For example, cameras and dedicated fingerprint devices can capture front-line physiological biometric samples (already used for device log-on applications and payment authorisation schemes such as Apple Pay) alongside voice capture using conventional microphones. Understanding the performance of these biometric modalities is critical to assessing suitability for deployment. Providing a robust performance and security assessment given a set of deployment variables is critical to ensure appropriate security and accuracy. Conventional biometrics testing is typically performed in controlled, constrained environments that fail to encapsulate mobile systems' daily (and developing) use. This thesis aims to develop an understanding of biometric performance on mobile devices. The impact of different mobile platforms, and the range of environmental conditions in use, on biometrics' accuracy, usability, security, and utility is poorly understood. This project will also examine the application and performance of mobile biometrics when in motion

Personalized Pain Study Platform Using Evidence-Based Continuous Learning Tool

With the increased accessibility to mobile technologies, research utilizing mobile technologies in medical and public health area has also increased. The efficiency and effectiveness of healthcare services are also improved by introduction of mobile technologies. Effective pain treatment requires regular and continuous pain assessment of the patients. Mobile Health or mHealth has been an active interdisciplinary research area for more than a decade to research pain assessment through different software research tools. Different mHealth support systems are developed to assess pain level of patient using different techniques. Close attention to participant’s self- reported pain along with data mining based pain level detection could help the healthcare industry and researchers to deliver effective health services in pain treatment. Pain expression recognition can be a good way for data mining based approach though pain expression recognition itself may utilize different approach based on the research study scope. Most of the pain research tools are study or disease specific. Some of the tools are pain specific (lumber pain, cancer pain etc) and some are patient group specific (neonatal, adult, woman etc). This results in recurrent but potentially avoidable costs such as time, money, and workforce to develop similar service or software research tools for each research study. Based on the pain study research characteristics, it is possible to design and implement a customizable and extensible generic pain research tool. In this thesis, we have proposed, designed, and implemented a customizable personalized pain study platform tool following a micro service architecture. It has most of the common software research modules that are needed for a pain research study. These include real-time data collection, research participant management, role based access control, research data anonymization etc. This software research tool is also used to investigate pain level detection accuracy using evidence-based continuous learning from facial expression which yielded about 71% classification accuracy. This tool is also HIPAA compliant and platform independent which makes it device independent, privacy-aware, and security-aware

Ocular motion classification for mobile device presentation attack detection

Title from PDF of title page viewed February 25, 2021Dissertation advisor: Reza DerakhshanVitaIncludes bibliographical references (page 105-129)Thesis (Ph.D.)--School of Computing and Engineering. University of Missouri--Kansas City, 2020As a practical pursuit of quantified uniqueness, biometrics explores the parameters that make us who we are and provides the tools we need to secure the integrity of that identity. In our culture of constant connectivity, an increasing reliance on biometrically secured mobile devices is transforming them into a target for bad actors. While no system will ever prevent all forms of intrusion, even state of the art biometric methods remain vulnerable to spoof attacks. As these attacks become more sophisticated, ocular motion based presentation attack detection (PAD) methods provide a potential deterrent. This dissertation presents the methods and evaluation of a novel optokinetic nystagmus (OKN) based PAD system for mobile device applications which leverages phase-locked temporal features of a unique reflexive behavioral response. Background is provided for historical and literary context of eye motion and ocular tracking to provide context to the objectives and accomplishments of this work. An evaluation of the improved methods for sample processing and sequential stability is provided with highlights for the presented improvements to the stability of convolutional facial landmark localization, and automated spatiotemporal feature extraction and classification models. Insights gleaned from this work are provided to elucidate some of the major challenges of mobile ocular motion feature extraction, as well as additional future considerations for the refinement and application of OKN motion signatures as a novel mobile device based PAD method.Introduction -- Retrospective, Contextual and Contemporary analysis -- Experimental Design -- Methods and Results -- Discussion -- Conclusion

The role of technology in improving the Customer Experience in the banking sector: a systematic mapping study

Information Technology (IT) has revolutionized the way we manage our money. The adoption of innovative technologies in banking scenarios allows to access old and new financial services but in a faster and more secure, comfortable, rewarding and engaging way. The number, the performances and the seamless integration of these innovations is a driver for banks to retain their customers and avoid costly change of hearts. The literature is rich in works reporting on the use of technology with direct or indirect impact on the experience of banking customers. Some mapping studies about the adoption of technologies in the field exist, but they are specific to particular technologies (e.g., only Artificial Intelligence), or vice versa too generic (e.g., reviewing the adoption of technologies to support any kind of banking process). So a specific research effort on the crossed domain of technology and Customer Experience (CX) is missing. This paper aims to overcome the following gaps: the lack of a comprehensive map of the research made in the field in the past decade; a discussion on the current research trends of top publications and journals is missing; the next research challenges are yet to be identified. To face these limitations, we designed and submitted 7 different queries to pull papers out of 4 popular scientific databases. From an initial set of 6,756 results, we identified a set of 89 primary studies that we thoroughly analyzed. A selection of the top 20% works allowed us to seek the most performant technologies as well as other promising ones that have not been experimented yet in the field. Main results prove that the combined study of technology and CX in the banking sector is not approached systematically and thus the development of a new specific research line is needed