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Jean-Pierre Hubaux

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Publications associées (202)

GA4GH: International policies and standards for data sharing across genomic research and healthcare

Jean-Pierre Hubaux, Junjun Zhang, Jamal Nasir

The Global Alliance for Genomics and Health (GA4GH) aims to accelerate biomedical advances by enabling the responsible sharing of clinical and genomic data through both harmonized data aggregation and federated approaches. The decreasing cost of genomic se ...

Elsevier2021

System and method for privacy-preserving distributed training of machine learning models on distributed datasets

Jean-Pierre Hubaux, Jean-Philippe Léonard Bossuat, David Jules Froelicher, Joao André Gomes de Sá e Sousa, Juan Ramón Troncoso-Pastoriza, Sinem Sav, Apostolos Pyrgelis

A computer-implemented method and a distributed computer system (100) for privacy- preserving distributed training of a global model on distributed datasets (DS1 to DSn). The system has a plurality of data providers (DP1 to DPn) being communicatively coupl ...

2021

SoK: Privacy-Preserving Collaborative Tree-based Model Learning

Jean-Pierre Hubaux, Sylvain Chatel, Juan Ramón Troncoso-Pastoriza, Apostolos Pyrgelis

2021

Privacy and Integrity Preserving Computations with CRISP

Jean-Pierre Hubaux, Sylvain Chatel, Juan Ramón Troncoso-Pastoriza, Apostolos Pyrgelis

In the digital era, users share their personal data with service providers to obtain some utility, e.g., access to high-quality services. Yet, the induced information flows raise privacy and integrity concerns. Consequently, cautious users may want to prot ...

USENIX ASSOC2021

SCOR: A secure international informatics infrastructure to investigate COVID-19

Jean-Pierre Hubaux, Juan Ramón Troncoso-Pastoriza

Global pandemics call for large and diverse healthcare data to study various risk factors, treatment options, and disease progression patterns. Despite the enormous efforts of many large data consortium initiatives, scientific community still lacks a secur ...

OXFORD UNIV PRESS2020

MedCo(2): Privacy-Preserving Cohort Exploration and Analysis

Jean-Pierre Hubaux, Mickaël Misbach, David Jules Froelicher, Jean Louis Raisaro, Juan Ramón Troncoso-Pastoriza

Medical studies are usually time consuming, cumbersome and extremely costly to perform, and for exploratory research, their results are also difficult to predict a priori. This is particularly the case for rare diseases, for which finding enough patients i ...

IOS PRESS2020

PriFi: Low-Latency Anonymity for Organizational Networks

Jean-Pierre Hubaux, Ludovic Barman, Ennan Zhai, Italo Ivan Dacosta Petrocelli, Bryan Alexander Ford, Mahdi Zamani, Apostolos Pyrgelis

Organizational networks are vulnerable to traffic-analysis attacks that enable adversaries to infer sensitive information from the network traffic – even if encryption is used. Typical anonymous communication networks are tailored to the Internet and are p ...

2020

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

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

HideMyApp: Hiding the Presence of Sensitive Apps on Android

Jean-Pierre Hubaux, Kévin Clément Huguenin, Thi Van Anh Pham, Italo Ivan Dacosta Petrocelli, John Stephan, Eleonora Losiouk

Millions of users rely on mobile health (mHealth) apps to manage their wellness and medical conditions. Although the popularity of such apps continues to grow, several privacy and security challenges can hinder their potential. In particular, the simple fa ...

Proceedings of the 28th USENIX Security Symposium2019

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

The (Co)-Location Sharing Game

Jean-Pierre Hubaux, Mathias Jacques Jean-Marc Humbert, Kévin Clément Huguenin, Alexandra-Mihaela Olteanu

Most popular location-based social networks, such as Facebook and Foursquare, let their (mobile) users post location and co-location (involving other users) information. Such posts bring social benefits to the users who post them but also to their friends ...

2019

HideMyApp : Hiding the Presence of Sensitive Apps on Android

Jean-Pierre Hubaux, Kévin Clément Huguenin, Thi Van Anh Pham, Italo Ivan Dacosta Petrocelli, John Stephan, Eleonora Losiouk

2019

Reducing Metadata Leakage from Encrypted Files and Communication with PURBs

Jean-Pierre Hubaux, Ludovic Barman, Kirill Nikitin, Matthew Joshua Underwood, Bryan Alexander Ford, Wouter Lueks

Most encrypted data formats leak metadata via their plaintext headers, such as format version, encryption schemes used, number of recipients who can decrypt the data, and even the recipients’ identities. This leakage can pose security and privacy risks to ...

Sciendo2019

HideMyApp : Hiding the Presence of Sensitive Apps on Android

Jean-Pierre Hubaux, Kévin Clément Huguenin, Italo Ivan Dacosta Petrocelli, John Stephan, Eleonora Losiouk

USENIX ASSOC2019

A Predictive Model for User Motivation and Utility Implications of Privacy-Protection Mechanisms in Location Check-Ins

Jean-Pierre Hubaux, Igor Bilogrevic, Reza Shokri, Kévin Clément Huguenin, Joana Catarina Soares Machado, Stefan Mihaila, Italo Ivan Dacosta Petrocelli

Location check-ins contain both geographical and semantic information about the visited venues. Semantic information is usually represented by means of tags (e.g., “restaurant”). Such data can reveal some personal information about users beyond what they a ...

2018

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