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Juan Ramón Troncoso-Pastoriza

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Publications associées (33)

Lattigo: A multiparty homomorphic encryption library in Go

Jean-Pierre Hubaux, Jean-Philippe Léonard Bossuat, Christian Vincent Mouchet, Juan Ramón Troncoso-Pastoriza

We present and demo of Lattigo, a multiparty homomorphic encryption library in Go. After a brief introduction of the origin and history of the library, we dive into the most relevant technical aspects that differentiate Lattigo from other existing librarie ...

2020

Data protection and ethics requirements for multisite research with health data: a comparative examination of legislative governance frameworks and the role of data protection technologies

Jean-Pierre Hubaux, Jacques Fellay, Jean Louis Raisaro, Juan Ramón Troncoso-Pastoriza

Personalised medicine can improve both public and individual health by providing targeted preventative and therapeutic healthcare. However, patient health data must be shared between institutions and across jurisdictions for the benefits of personalised me ...

OXFORD UNIV PRESS2020

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

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

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

SPHN/PHRT - MedCo in Action: Empowering the Swiss Molecular Tumor Board with Privacy-Preserving and Real-Time Patient Discovery

Jean-Pierre Hubaux, Mickaël Misbach, Jacques Fellay, Joao André Gomes de Sá e Sousa, Juan Ramón Troncoso-Pastoriza

MedCo is the first operational system that makes sensitive medical-data available for research in a simple, privacy-conscious and secure way. It enables a consortium of clinical sites to collectively protect their data and to securely share them with inves ...

IOS PRESS2020

Privacy-preserving semi-parallel logistic regression training with fully homomorphic encryption

Juan Ramón Troncoso-Pastoriza

Background Privacy-preserving computations on genomic data, and more generally on medical data, is a critical path technology for innovative, life-saving research to positively and equally impact the global population. It enables medical research algorithm ...

2020

GenoShare: Supporting Privacy-Informed Decisions for Sharing Individual-Level Genetic Data

Jean-Pierre Hubaux, Juan Ramón Troncoso-Pastoriza, Carmela González Troncoso

One major obstacle to developing precision medicine to its full potential is the privacy concerns related to genomic-data sharing. Even though the academic community has proposed many solutions to protect genomic privacy, these so far have not been adopted ...

IOS PRESS2020

MedChain: Accountable and Auditable Data Sharing in Distributed Medical Scenarios

Jean-Pierre Hubaux, Linus Gasser, Jean Louis Raisaro, Bryan Alexander Ford, Juan Ramón Troncoso-Pastoriza

The current trend towards personalized medicine creates an urgent need to share data among different hospitals and health institutions, which endangers the privacy of the data subjects if not done with the appropriate precautions. Conversely, the frequency ...

2019

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

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

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

Revisiting Multivariate Lattices for Encrypted Signal Processing

Juan Ramón Troncoso-Pastoriza

Multimedia contents are inherently sensitive signals that must be protected when processed in untrusted environments. The field of Secure Signal Processing addresses this challenge by developing methods which enable operating with sensitive signals in a pr ...

ASSOC COMPUTING MACHINERY2019

Camera Attribution Forensic Analyzer in the Encrypted Domain

Juan Ramón Troncoso-Pastoriza

Digital media forensics must deal with constantly increasing volumes of data. In order to efficiently scale up, outsourcing computation becomes an appealing solution. However, due to the highly sensitive nature of forensic data, its privacy must be protect ...

IEEE2018

On Enforcing the Digital Immunity of a Large Humanitarian Organization

Jean-Pierre Hubaux, Bryan Alexander Ford, Philipp Svetolik Jovanovic, Juan Ramón Troncoso-Pastoriza

Humanitarian action, the process of aiding individuals in situations of crises, poses unique information-security challenges due to natural or manmade disasters, the adverse environments in which it takes place, and the scale and multidisciplinary nature o ...

2018

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

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

Being able to share large amounts of sensitive clinical and genomic data across several institutions is crucial for precision medicine to scale up. Unfor- tunately, existing solutions only partially address this challenge and are still unable to provide th ...

2017

ORide: A Privacy-Preserving yet Accountable Ride-Hailing Service

Jean-Pierre Hubaux, Kévin Clément Huguenin, Thi Van Anh Pham, Italo Ivan Dacosta Petrocelli, Guillaume Francois Maurice Endignoux, Juan Ramón Troncoso-Pastoriza

In recent years, ride-hailing services (RHSs) have become increasingly popular, serving millions of users per day. Such systems, however, raise significant privacy concerns, because service providers are able to track the precise mobility patterns of all r ...

2017

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