Concept

Personal data

Related publications (89)

SafetyPin: Encrypted Backups with Human-Memorable Secrets

We present the design and implementation of SafetyPin, a system for encrypted mobile-device backups. Like existing cloud-based mobile-backup systems, including those of Apple and Google, SafetyPin requires users to remember only a short PIN and defends aga ...

USENIX Association2020

SafetyPin: Encrypted Backups with Human-Memorable Secrets

Henry Nathaniel Corrigan-Gibbs

USENIX ASSOC2020

Private and Secure Distributed Learning

Georgios Damaskinos

The ever-growing number of edge devices (e.g., smartphones) and the exploding volume of sensitive data they produce, call for distributed machine learning techniques that are privacy-preserving. Given the increasing computing capabilities of modern edge de ...

EPFL2020

EpilepsyGAN: Synthetic Epileptic Brain Activities with Privacy Preservation

David Atienza Alonso, Amir Aminifar, Alireza Amirshahi, Damián Pascual Ortiz

Epilepsy is a chronic neurological disorder affecting more than 65 million people worldwide and manifested by recurrent unprovoked seizures. The unpredictability of seizures not only degrades the quality of life of the patients, but it can also be life-thr ...

2020

Drynx: Decentralized, Secure, Verifiable System for Statistical Queries and Machine Learning on Distributed Datasets

Jean-Pierre Hubaux, Juan Ramón Troncoso-Pastoriza, David Jules Froelicher, Joao André Gomes de Sá e Sousa

Data sharing has become of primary importance in many domains such as big-data analytics, economics and medical research, but remains difficult to achieve when the data are sensitive. In fact, sharing personal information requires individuals' unconditiona ...

2020

Introduction to the Swiss Data Custodian

Marc-Edouard Baptiste Grégoire Schultheiss, Olivier Verscheure

Trust in the use of sensitive data is not nearly widespread. Even though there is no shortage in tools and methods to address the digitisation of our society and industries, the acquisition and access to non-open data represent the greatest challenge. In t ...

2019

MedCo: Enabling Secure and Privacy-Preserving Exploration of Distributed Clinical and Genomic Data

Jean-Pierre Hubaux, Bryan Alexander Ford, Juan Ramón Troncoso-Pastoriza, Jean Louis Raisaro, Joao André Gomes de Sá e Sousa, Mickaël Misbach, Olivier Michielin

The increasing number of health-data breaches is creating a complicated environment for medical-data sharing and, consequently, for medical progress. Therefore, the development of new solutions that can reassure clinical sites by enabling privacy-preservin ...

2019

Self-Recognition in Data Visualization: How Individuals See Themselves in Visual Representations

Dario Rodighiero, Loup Cellard

This article explores how readers recognize their personal identities represented through data visualizations. The recognition is investigated starting from three definitions captured by the philosopher Paul Ricoeur: the identification with the visualizati ...

2019

Consensual and Privacy-Preserving Sharing of Multi-Subject and Interdependent Data

Jean-Pierre Hubaux, Kévin Clément Huguenin, Italo Ivan Dacosta Petrocelli, Alexandra-Mihaela Olteanu

Individuals share increasing amounts of personal data online. This data often involves–or at least has privacy implications for–data subjects other than the individual who shares it (e.g., photos, genomic data) and the data is shared without their consent. ...

2018

Building a common and privacy-preserving front end for open-source clinical research platforms

Mickaël Misbach

Being able to exploit large and heterogeneous medical data is crucial for realizing the promise of precision medicine to its full potential. Yet, currently, due to the presence of multiple and fragmented systems at different clinical sites, it is often dif ...

2018

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