A Decentralised Digital Identity Architecture

Current architectures to validate, certify, and manage identity are based on centralised, top-down approaches that rely on trusted authorities and third-party operators. We approach the problem of digital identity starting from a human rights perspective, with a primary focus on identity systems in the developed world. We assert that individual persons must be allowed to manage their personal information in a multitude of different ways in different contexts and that to do so, each individual must be able to create multiple unrelated identities. Therefore, we first define a set of fundamental constraints that digital identity systems must satisfy to preserve and promote privacy as required for individual autonomy. With these constraints in mind, we then propose a decentralised, standards-based approach, using a combination of distributed ledger technology and thoughtful regulation, to facilitate many-to-many relationships among providers of key services. Our proposal for digital identity differs from others in its approach to trust in that we do not seek to bind credentials to each other or to a mutually trusted authority to achieve strong non-transferability. Because the system does not implicitly encourage its users to maintain a single aggregated identity that can potentially be constrained or reconstructed against their interests, individuals and organisations are free to embrace the system and share in its benefits.Comment: 30 pages, 10 figures, 3 table

An architecture for secure data management in medical research and aided diagnosis

Programa Oficial de Doutoramento en Tecnoloxías da Información e as Comunicacións. 5032V01[Resumo] O Regulamento Xeral de Proteccion de Datos (GDPR) implantouse o 25 de maio de 2018 e considerase o desenvolvemento mais importante na regulacion da privacidade de datos dos ultimos 20 anos. As multas fortes definense por violar esas regras e non e algo que os centros sanitarios poidan permitirse ignorar. O obxectivo principal desta tese e estudar e proponer unha capa segura/integracion para os curadores de datos sanitarios, onde: a conectividade entre sistemas illados (localizacions), a unificacion de rexistros nunha vision centrada no paciente e a comparticion de datos coa aprobacion do consentimento sexan as pedras angulares de a arquitectura controlar a sua identidade, os perfis de privacidade e as subvencions de acceso. Ten como obxectivo minimizar o medo a responsabilidade legal ao compartir os rexistros medicos mediante o uso da anonimizacion e facendo que os pacientes sexan responsables de protexer os seus propios rexistros medicos, pero preservando a calidade do tratamento do paciente. A nosa hipotese principal e: os conceptos Distributed Ledger e Self-Sovereign Identity son unha simbiose natural para resolver os retos do GDPR no contexto da saude? Requirense solucions para que os medicos e investigadores poidan manter os seus fluxos de traballo de colaboracion sen comprometer as regulacions. A arquitectura proposta logra eses obxectivos nun ambiente descentralizado adoptando perfis de privacidade de datos illados.[Resumen] El Reglamento General de Proteccion de Datos (GDPR) se implemento el 25 de mayo de 2018 y se considera el desarrollo mas importante en la regulacion de privacidad de datos en los ultimos 20 anos. Las fuertes multas estan definidas por violar esas reglas y no es algo que los centros de salud puedan darse el lujo de ignorar. El objetivo principal de esta tesis es estudiar y proponer una capa segura/de integración para curadores de datos de atencion medica, donde: la conectividad entre sistemas aislados (ubicaciones), la unificacion de registros en una vista centrada en el paciente y el intercambio de datos con la aprobacion del consentimiento son los pilares de la arquitectura propuesta. Esta propuesta otorga al titular de los datos un rol central, que le permite controlar su identidad, perfiles de privacidad y permisos de acceso. Su objetivo es minimizar el temor a la responsabilidad legal al compartir registros medicos utilizando el anonimato y haciendo que los pacientes sean responsables de proteger sus propios registros medicos, preservando al mismo tiempo la calidad del tratamiento del paciente. Nuestra hipotesis principal es: .son los conceptos de libro mayor distribuido e identidad autosuficiente una simbiosis natural para resolver los desafios del RGPD en el contexto de la atencion medica? Se requieren soluciones para que los medicos y los investigadores puedan mantener sus flujos de trabajo de colaboracion sin comprometer las regulaciones. La arquitectura propuesta logra esos objetivos en un entorno descentralizado mediante la adopcion de perfiles de privacidad de datos aislados.[Abstract] The General Data Protection Regulation (GDPR) was implemented on 25 May 2018 and is considered the most important development in data privacy regulation in the last 20 years. Heavy fines are defined for violating those rules and is not something that healthcare centers can afford to ignore. The main goal of this thesis is to study and propose a secure/integration layer for healthcare data curators, where: connectivity between isolated systems (locations), unification of records in a patientcentric view and data sharing with consent approval are the cornerstones of the proposed architecture. This proposal empowers the data subject with a central role, which allows to control their identity, privacy profiles and access grants. It aims to minimize the fear of legal liability when sharing medical records by using anonymisation and making patients responsible for securing their own medical records, yet preserving the patient’s quality of treatment. Our main hypothesis is: are the Distributed Ledger and Self-Sovereign Identity concepts a natural symbiosis to solve the GDPR challenges in the context of healthcare? Solutions are required so that clinicians and researchers can maintain their collaboration workflows without compromising regulations. The proposed architecture accomplishes those objectives in a decentralized environment by adopting isolated data privacy profiles

A Framework for Preserving Privacy and Cybersecurity in Brain-Computer Interfacing Applications

Brain-Computer Interfaces (BCIs) comprise a rapidly evolving field of technology with the potential of far-reaching impact in domains ranging from medical over industrial to artistic, gaming, and military. Today, these emerging BCI applications are typically still at early technology readiness levels, but because BCIs create novel, technical communication channels for the human brain, they have raised privacy and security concerns. To mitigate such risks, a large body of countermeasures has been proposed in the literature, but a general framework is lacking which would describe how privacy and security of BCI applications can be protected by design, i.e., already as an integral part of the early BCI design process, in a systematic manner, and allowing suitable depth of analysis for different contexts such as commercial BCI product development vs. academic research and lab prototypes. Here we propose the adoption of recent systems-engineering methodologies for privacy threat modeling, risk assessment, and privacy engineering to the BCI field. These methodologies address privacy and security concerns in a more systematic and holistic way than previous approaches, and provide reusable patterns on how to move from principles to actions. We apply these methodologies to BCI and data flows and derive a generic, extensible, and actionable framework for brain-privacy-preserving cybersecurity in BCI applications. This framework is designed for flexible application to the wide range of current and future BCI applications. We also propose a range of novel privacy-by-design features for BCIs, with an emphasis on features promoting BCI transparency as a prerequisite for informational self-determination of BCI users, as well as design features for ensuring BCI user autonomy. We anticipate that our framework will contribute to the development of privacy-respecting, trustworthy BCI technologies

Selected Computing Research Papers Volume 7 June 2018

Contents Critical Evaluation of Arabic Sentimental Analysis and Their Accuracy on Microblogs (Maha Al-Sakran) Evaluating Current Research on Psychometric Factors Affecting Teachers in ICT Integration (Daniel Otieno Aoko) A Critical Analysis of Current Measures for Preventing Use of Fraudulent Resources in Cloud Computing (Grant Bulman) An Analytical Assessment of Modern Human Robot Interaction Systems (Dominic Button) Critical Evaluation of Current Power Management Methods Used in Mobile Devices (One Lekula) A Critical Evaluation of Current Face Recognition Systems Research Aimed at Improving Accuracy for Class Attendance (Gladys B. Mogotsi) Usability of E-commerce Website Based on Perceived Homepage Visual Aesthetics (Mercy Ochiel) An Overview Investigation of Reducing the Impact of DDOS Attacks on Cloud Computing within Organisations (Jabed Rahman) Critical Analysis of Online Verification Techniques in Internet Banking Transactions (Fredrick Tshane

Biometric walk recognizer. Research and results on wearable sensor-based gait recognition

Gait is a biometric trait that can allow user authentication, though being classified as a "soft" one due to a certain lack in permanence, and to sensibility to specific conditions. The earliest research relies on computer vision-based approaches, especially applied in video surveillance. More recently, the spread of wearable sensors, especially those embedded in mobile devices, which are able to capture the dynamics of the walking pattern through simpler 1D signals, has spurred a different research line. This capture modality can avoid some problems related to computer vision-based techniques, but suffers from specific limitations. Related research is still in a less advanced phase with respect to other biometric traits. However, the promising results achieved so far, the increasing accuracy of sensors, the ubiquitous presence of mobile devices, and the low cost of related techniques, make this biometrics attractive and suggest to continue the investigations in this field. The first Chapters of this thesis deal with an introduction to biometrics, and more specifically to gait trait. A comprehensive review of technologies, approaches and strategies exploited by gait recognition proposals in the state-of-the-art is also provided. After such introduction, the contributions of this work are presented in details. Summarizing, it improves preceding result achieved during my Master Degree in Computer Science course of Biometrics and extended in my following Master Degree Thesis. The research deals with different strategies, including preprocessing and recognition techniques, applied to the gait biometrics, in order to allow both an automatic recognition and an improvement of the system accuracy