Inferring the Meaning of Non-personal, Anonymized, and Anonymous Data

On the awareness of the dynamism pertaining to data and its processing, this paper investigates the problem of having two mutually exclusive definitions of personal and non-personal data in the legal framework in force. The taxonomic analysis of key terms and their context of application highlights the risk to crystalize the whole system upon which the digital single market is built, suffocating its future development. With this premise, the paper discusses the extent of the two main data processing tools provided by the GDPR, questioning the ex-ante categorization of data and its outcome, supporting stakeholders in overcoming this issue

Statistical properties and privacy guarantees of an original distance-based fully synthetic data generation method

Introduction: The amount of data generated by original research is growing exponentially. Publicly releasing them is recommended to comply with the Open Science principles. However, data collected from human participants cannot be released as-is without raising privacy concerns. Fully synthetic data represent a promising answer to this challenge. This approach is explored by the French Centre de Recherche en {\'E}pid{\'e}miologie et Sant{\'e} des Populations in the form of a synthetic data generation framework based on Classification and Regression Trees and an original distance-based filtering. The goal of this work was to develop a refined version of this framework and to assess its risk-utility profile with empirical and formal tools, including novel ones developed for the purpose of this evaluation.Materials and Methods: Our synthesis framework consists of four successive steps, each of which is designed to prevent specific risks of disclosure. We assessed its performance by applying two or more of these steps to a rich epidemiological dataset. Privacy and utility metrics were computed for each of the resulting synthetic datasets, which were further assessed using machine learning approaches.Results: Computed metrics showed a satisfactory level of protection against attribute disclosure attacks for each synthetic dataset, especially when the full framework was used. Membership disclosure attacks were formally prevented without significantly altering the data. Machine learning approaches showed a low risk of success for simulated singling out and linkability attacks. Distributional and inferential similarity with the original data were high with all datasets.Discussion: This work showed the technical feasibility of generating publicly releasable synthetic data using a multi-step framework. Formal and empirical tools specifically developed for this demonstration are a valuable contribution to this field. Further research should focus on the extension and validation of these tools, in an effort to specify the intrinsic qualities of alternative data synthesis methods.Conclusion: By successfully assessing the quality of data produced using a novel multi-step synthetic data generation framework, we showed the technical and conceptual soundness of the Open-CESP initiative, which seems ripe for full-scale implementation

Estudi de la privacitat en dades de mobilitat : cas d'ús Swap Mobility Location

En un món on l'ús de la tecnologia és gairebé imprescindible, els usuaris es veuen forçats a cedir dades de caràcter personal a tercers per a poder fer-ne ús. Aquestes es publiquen a bases de dades públiques, generant així la necessitat de protegir la intimitat dels usuaris davant possibles atacs, mantenint, a l'hora, la integritat de les dades que seran aprofitades en estudis posteriors. Així mateix, l'objectiu principal d'aquest projecte és realitzar un estudi de l'actual estat de l'art en els mètodes de preservació de la privacitat en la publicació de les dades, fent èmfasi en les dades de les localitzacions dels usuaris, i implementar un dels mètodes estudiats posant solució al problema plantejat i estudiant els resultats.En un mundo donde el uso de la tecnología es casi imprescindible, los usuarios se ven forzados a ceder datos de carácter personal a terceros para poder hacer uso. Estos se publican en bases de datos públicas, generando así la necesidad de proteger la intimidad de los usuarios ante posibles ataques, manteniendo, a la vez, la integridad de los datos que serán aprovechados en estudios posteriores. Asimismo, el objetivo principal de este proyecto es realizar un estudio del actual estado del arte en los métodos de preservación de la privacidad en la publicación de los datos, haciendo énfasis en los datos de las localizaciones de los usuarios, e implementar uno de los métodos estudiados poniendo solución al problema planteado, estudiando los resultados.In a world where the use of technology has become almost essential, users has been forced to relinquish / cede personal data to others so that they can make use of it. This data is published in public database, generating the necessity of protecting the intimity of the users in front of posstible attacks, mantaining, at the same time, the integrity of the data that will be resourceful in later studies. In this way, the main objective of this project is to carry out a study of the current state of Art in the preservation methods of the preservation of the privacy in the publication of data, emphasising in the data of users location and implementing one of the studied methods, drawing a solution to the considered problem and studying the results

CITIES: Energetic Efficiency, Sustainability; Infrastructures, Energy and the Environment; Mobility and IoT; Governance and Citizenship

This book collects important contributions on smart cities. This book was created in collaboration with the ICSC-CITIES2020, held in San José (Costa Rica) in 2020. This book collects articles on: energetic efficiency and sustainability; infrastructures, energy and the environment; mobility and IoT; governance and citizenship

Political Science and Digitalization – Global Perspectives

Digitalization is not only a new research subject for political science, but a transformative force for the discipline in terms of teaching and learning as well as research methods and publishing. This volume provides the first account of the influence of digitalization on the discipline of political science including contributions from 20 different countries. It presents a regional stocktaking of the challenges and opportunities of digitalization in most world regions

Political Science and Digitalization – Global Perspectives

Digitalization is not only a new research subject for political science, but a transformative force for the discipline in terms of teaching and learning as well as research methods and publishing. This volume provides the first account of the influence of digitalization on the discipline of political science including contributions from 20 different countries. It presents a regional stocktaking of the challenges and opportunities of digitalization in most world regions

Political Science and Digitalization – Global Perspectives

Digitalization is not only a new research subject for political science, but a transformative force for the discipline in terms of teaching and learning as well as research methods and publishing. This volume provides the first account of the influence of digitalization on the discipline of political science including contributions from 20 different countries. It presents a regional stocktaking of the challenges and opportunities of digitalization in most world regions