5 papers
High-Capacity Robust Medical Image Exfiltration via Neural Network Weight Replacement
Elie Thellier, Huiyu Li, Nicholas Ayache +1
Collaborative medical AI platforms allow researchers to train models on sensitive imaging data while restricting data export. However, trained models can serve as covert carriers o…
Data Exfiltration by Compression Attack: Definition and Evaluation on Medical Image Data
Huiyu Li, Nicholas Ayache, Hervé Delingette
With the rapid expansion of data lakes storing health data and hosting AI algorithms, a prominent concern arises: how safe is it to export machine learning models from these data l…
Mitigating Data Exfiltration Attacks through Layer-Wise Learning Rate Decay Fine-Tuning
Elie Thellier, Huiyu Li, Nicholas Ayache +1
Data lakes enable the training of powerful machine learning models on sensitive, high-value medical datasets, but also introduce serious privacy risks due to potential leakage of p…
Spatial regularisation for improved accuracy and interpretability in keypoint-based registration
Benjamin Billot, Ramya Muthukrishnan, Esra Abaci-Turk +4
Unsupervised registration strategies bypass requirements in ground truth transforms or segmentations by optimising similarity metrics between fixed and moved volumes. Among these m…
Generative Medical Image Anonymization Based on Latent Code Projection and Optimization
Huiyu Li, Nicholas Ayache, Hervé Delingette
Medical image anonymization aims to protect patient privacy by removing identifying information, while preserving the data utility to solve downstream tasks. In this paper, we addr…