335 citations · 583 across the 23 of their papers we have counts for
4 papers · 1 filter
Split HE: Fast Secure Inference Combining Split Learning and Homomorphic Encryption
George-Liviu Pereteanu, Amir Alansary, Jonathan Passerat-Palmbach
This work presents a novel protocol for fast secure inference of neural networks applied to computer vision applications. It focuses on improving the overall performance of the onl…
Privacy-preserving medical image analysis
Alexander Ziller, Jonathan Passerat-Palmbach, Théo Ryffel +8
The utilisation of artificial intelligence in medicine and healthcare has led to successful clinical applications in several domains. The conflict between data usage and privacy pr…
A Systematic Comparison of Encrypted Machine Learning Solutions for Image Classification
Veneta Haralampieva, Daniel Rueckert, Jonathan Passerat-Palmbach
This work provides a comprehensive review of existing frameworks based on secure computing techniques in the context of private image classification. The in-depth analysis of these…
Robust Aggregation for Adaptive Privacy Preserving Federated Learning in Healthcare
Matei Grama, Maria Musat, Luis Muñoz-González +3
Federated learning (FL) has enabled training models collaboratively from multiple data owning parties without sharing their data. Given the privacy regulations of patient's healthc…