Interview: Meet the UtiP-DAM team!
The Correlation Systems team is a highly skilled and multidisciplinary group, comprising project managers, data scientists, sensor developers, and backend and frontend developers. Together, they leverage years of collaboration and experience in problem-solving, research, and development to tackle complex challenges. Currently, the team is focused on the UtiP-DAM project, which addresses the critical issue of […]
Interview: Meet DID-IMP team!
DID-IMP uses blockchain technology to eliminate the need for traditional hierarchical structures like Certificate Authorities (CA) and Registration Authorities (RA). Instead, it replaces these with a feeless blockchain smart contract, which also serves as a Certificate Store for issuing and managing revocable certificates. This streamlined architecture is ideal for IoT Secure Automatic Data Sharing (SADS), […]
Interview: Meet the DUME team!
The DUME team represents a dynamic collaboration between Logimade and ARDITI, combining expertise across multiple disciplines to ensure the success of the project. Under the leadership of Dr. Nuno Rodrigues, the team is strategically aligned with the project’s objectives, with key contributors specializing in systems optimization, decentralized architecture, backend development, and business strategy. Together, they […]
Interview: Meet the OIDC-PRINCE team!
The OIDC-PRINCE team is a dedicated group of security experts, consisting of senior researchers Bruno Sousa and Paulo Silva, alongside a PhD student, Ratul, and two master’s students. Their combined expertise spans security research and code implementation, making them well-equipped to tackle privacy challenges in today’s digital landscape. Together, they are working on the OIDC-PRINCE […]
Interview: Meet the MorphMetro team!
In this interview with the team behind MorphMetro, we explore their innovative approach to enhancing data security and privacy in the realm of measurement systems. MorphMetro is a collaborative effort between two SMEs—Random Red Ltd. and MindMint Ltd.—and a group of experts in metrology, machine learning, information security, and blockchain technology. With support from the […]
Interview: Meet the DOOF team!
DOOF is a project focusing on transforming personal data governance and establishing a robust data economy. It introduces a framework for privacy-enhancing technologies, ensuring GDPR compliance and empowering individuals to manage their data rights effectively. DOOF aims to enhance trust and transparency by offering user-friendly data management tools and GDPR-compliant data exchanges. Its adaptability and […]
SURE
SURE SURE offers a unified evaluation system for synthetic data, simultaneously measuring privacy and utility. This integrated approach contrasts with conventional methods, which evaluate these factors in isolation, and allows users to effectively balance them during data synthesis. This diagram serves as a visual representation of how each module contributes to the utility-privacy assessment process […]
ProvenAI
ProvenAI ProvenAI is at the forefront of reshaping AI collaboration and knowledge management with a visionary approach. Rooted in the belief that contributors deserve control and recognition for their intellectual contributions, the project introduces groundbreaking features focused on contribution, traceability, and data control. Central to ProvenAI’s mission is the development of modularized software components that […]
PECS
PECS People’s privacy control over the personal data that they generate and consume while they drive modern cars is extremely weak at present. There is historical as well as recent evidence that car brands harvest a variety of personal data from drivers and, arguably, full compliance of their processing with the European General Data Protection […]
OIDC-PRINCE
OIDC-PRINCE The OIDC PRINCE project aims to enhance the privacy support in user consents used in OpenID Connect authentication and authorization processes. Nowadays the consent to access the claims about end-user and authentication events (e.g., gender, birthdate, phone number), may have associated privacy issues. Users need to be informed regarding the potential risk of providing […]
