Publications associées à Crypt4GH: a file format standard enabling native access to encrypted data

Scalable and Privacy-Preserving Federated Principal Component Analysis

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

Principal component analysis (PCA) is an essential algorithm for dimensionality reduction in many data science domains. We address the problem of performing a federated PCA on private data distributed among multiple data providers while ensuring data confi ...

IEEE COMPUTER SOC2023

Practical considerations of diffusion-weighted MRS with ultra-strong diffusion gradients

André Döring

IntroductionDiffusion-weighted magnetic resonance spectroscopy (DW-MRS) offers improved cellular specificity to microstructure-compared to water-based methods alone-but spatial resolution and SNR is severely reduced and slow-diffusing metabolites necessita ...

Frontiers Media Sa2023

A Practical Influence Approximation for Privacy-Preserving Data Filtering in Federated Learning

Boi Faltings, Ljubomir Rokvic, Panayiotis Danassis

Federated Learning by nature is susceptible to low-quality, corrupted, or even malicious data that can severely degrade the quality of the learned model. Traditional techniques for data valuation cannot be applied as the data is never revealed. We present ...

2023

Arbitrary Decisions are a Hidden Cost of Differentially Private Training

Carmela González Troncoso, Bogdan Kulynych

Mechanisms used in privacy-preserving machine learning often aim to guarantee differential privacy (DP) during model training. Practical DP-ensuring training methods use randomization when fitting model parameters to privacy-sensitive data (e.g., adding Ga ...

Assoc Computing Machinery2023

Interactive-time Exploration, Querying, and Analysis of Large High-dimensional Datasets

Sachin Basil John

In the current era of big data, aggregation queries on high-dimensional datasets are frequently utilized to uncover hidden patterns, trends, and correlations critical for effective business decision-making. Data cubes facilitate such queries by employing p ...

EPFL2023

Thwarting Malicious Adversaries in Homomorphic Encryption Pipelines

Sylvain Chatel

Homomorphic Encryption (HE) enables computations to be executed directly on encrypted data. As such, it is an auspicious solution for protecting the confidentiality of sensitive data without impeding its usability. However, HE does not provide any guarant ...

EPFL2023

Streamline RimNet: Tools for Automatic Classification of Paramagnetic Rim Lesions in MRI of Multiple Sclerosis

Meritxell Bach Cuadra, Cristina Granziera, Francesco La Rosa, Maxence Charles F Wynen

This site provides two software tools related to "RimNet: A deep 3D multimodal MRI architecture for paramagnetic rim lesion assessment in multiple sclerosis" by Barquero et al. NeuroImage: Clinical (2020). People using in part or f ...

Zenodo2023

A robust walking detection algorithm using a single foot-worn inertial sensor: validation in real-life settings

Kamiar Aminian, Anisoara Ionescu, Gaëlle Prigent, Francesca Salis

Walking activity and gait parameters are considered among the most relevant mobility-related parameters. Currently, gait assessments have been mainly analyzed in laboratory or hospital settings, which only partially reflect usual performance (i.e., real wo ...

SPRINGER HEIDELBERG2023

Health data privacy through homomorphic encryption and distributed ledger computing: an ethical-legal qualitative expert assessment study

Marcello Ienca

Background: Increasingly, hospitals and research institutes are developing technical solutions for sharing patient data in a privacy preserving manner. Two of these technical solutions are homomorphic encryption and distributed ledger technology. Homomorph ...

BMC2022

Boosting Efficiency of External Pipelines by Blurring Application Boundaries

Anastasia Ailamaki, Anna Patricia Herlihy, Periklis Chrysogelos

Modern application development addresses increasingly specialized problems using domain-specific utilities, such as Optical Code Recognition and standalone statistical tools. The diversity of tooling, combined with the ever-growing volume of data, requires ...

2022