Publications associées à Data re-identification

Differentially private multi-agent constraint optimization

Boi Faltings, Aleksei Triastcyn, Sankarshan Damle, Sujit Prakash Gujar

Distributed constraint optimization (DCOP) is a framework in which multiple agents with private constraints (or preferences) cooperate to achieve a common goal optimally. DCOPs are applicable in several multi-agent coordination/allocation problems, such as ...

Springer2024

PRO-Face C: Privacy-Preserving Recognition of Obfuscated Face via Feature Compensation

Touradj Ebrahimi, Lin Yuan, Xiao Pu, Yao Zhang, Hongbo Li

The advancement of face recognition technology has delivered substantial societal advantages. However, it has also raised global privacy concerns due to the ubiquitous collection and potential misuse of individuals' facial data. This presents a notable par ...

Ieee-Inst Electrical Electronics Engineers Inc2024

Differentially Private Multi-Agent Constraint Optimization

Boi Faltings, Sujit Prakash Gujar, Sankarshan Damle, Aleksei Triastcyn

Several optimization scenarios involve multiple agents that desire to protect the privacy of their preferences. There are distributed algorithms for constraint optimization that provide improved privacy protection through secure multiparty computation. How ...

ACM2022

Utility/privacy trade-off as regularized optimal transport

Etienne Patrice Boursier

Strategic information is valuable either by remaining private (for instance if it is sensitive) or, on the other hand, by being used publicly to increase some utility. These two objectives are antagonistic and leaking this information by taking full advant ...

SPRINGER HEIDELBERG2022

TEE-based decentralized recommender systems: The raw data sharing redemption

Anne-Marie Kermarrec, Rafael Pereira Pires, Akash Balasaheb Dhasade, Nevena Dresevic

Recommenders are central in many applications today. The most effective recommendation schemes, such as those based on collaborative filtering (CF), exploit similarities between user profiles to make recommendations, but potentially expose private data. Fe ...

2022

Generating Higher-Fidelity Synthetic Datasets with Privacy Guarantees

Boi Faltings, Aleksei Triastcyn

We consider the problem of enhancing user privacy in common data analysis and machine learning development tasks, such as data annotation and inspection, by substituting the real data with samples from a generative adversarial network. We propose employing ...

MDPI2022

Open-Set Person Re-Identification through Error Resilient Recurring Gallery Building

Touradj Ebrahimi, Evgeniy Upenik

In person re-identification, individuals must be correctly identified in images that come from different cameras or are captured at different points in time. In the open-set case, the above needs be achieved for people who have not been previously recognis ...

IEEE2021

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

Privacy - Preserving Data Exchange and Aggregation in Healthcare

Alevtina Dubovitskaya

Medical data are often scattered among multiple clinics, hospitals, insurance companies, pharmacies, and research institutions that store and process personal healthcare information. The use of information and communication technologies for health (eHealth ...

EPFL2018

Privacy-Enhancing Technologies for Medical and Genomic Data: From Theory to Practice

Jean Louis Raisaro

The impressive technological advances in genomic analysis and the significant drop in the cost of genome sequencing are paving the way to a variety of revolutionary applications in modern healthcare. In particular, the increasing understanding of the human ...

EPFL2018

Addressing Beacon Re-Identification Attacks: Quantification and Mitigation of Privacy Risks

Jean-Pierre Hubaux, Jean Louis Raisaro, Florian Tramèr, Shuang Wang, Carlos Bustamante

The Global Alliance for Genomics and Health (GA4GH) created the Beacon Project as a means of testing the willingness of data holders to share genetic data in the simplest technical context query for the presence of a specified nucleotide at a given positio ...

Oxford Univ Press2017

A Cloud-Based eHealth Architecture for Privacy Preserving Data Integration

Karl Aberer, Michael Ignaz Schumacher, Matteo Vasirani, Alevtina Dubovitskaya

In this paper, we address the problem of building an anonymized medical database from multiple sources. Our proposed solution defines how to achieve data integration in a heterogeneous network of many clinical institutions, while preserving data utility an ...

Springer International Publishing2015

De-anonymizing Genomic Databases Using Phenotypic Traits

Jean-Pierre Hubaux, Joachim Ludovic Hugonot, Kévin Clément Huguenin, Erman Ayday, Mathias Jacques Jean-Marc Humbert

People increasingly have their genomes sequenced and some of them share their genomic data online. They do so for various purposes, including to find relatives and to help advance genomic research. An individual's genome carries very sensitive, private inf ...

2015

Enforcing Privacy for Teenagers in Online Inquiry Learning Spaces

Denis Gillet, Adrian Christian Holzer, Sten Govaerts, Na Li

In the Go-Lab European project, we are investigating an online lab portal that enables students to perform personalized scientific experiments with online labs. To protect sensitive student data, such as user activity data and learning preferences, this pa ...

2014

Privacy and Dynamics of Social Networks

Pedram Pedarsani

Over the past decade, investigations in different fields have focused on studying and understanding real networks, ranging from biological to social to technological. These networks, called complex networks, exhibit common topological features, such as a h ...

EPFL2013

Quantifying and Protecting Location Privacy

Reza Shokri

Recent developments in information and communication technologies have been profound and life-changing. Most people are now equipped with smart phones with high computation power and communication capabilities. These devices can efficiently run multiple so ...

EPFL2013

On the Privacy of Anonymized Networks

Matthias Grossglauser, Pedram Pedarsani

The proliferation of online social networks, and the concomitant accumulation of user data, give rise to hotly debated issues of privacy, security, and control. One specific challenge is the sharing or public release of anonymized data without accidentally ...

2011

RFID Privacy based on Public-Key Cryptography

Serge Vaudenay

RFID systems makes it possible for a server to identify known tags in wireless settings. As they become more and more pervasive, people privacy is more and more threatened. In this talk, we list a few models for privacy in RFID and compare them. We review ...

2006