Preprint
Aug 2026
Similarity Weighted Aggregation with Global Differential Privacy for Federated Brain Lesion Segmentation
The proposed DP-SimAgg framework is a privacy-preserving federated learning framework that integrates similarity-weighted aggregation with a server-side differential privacy mechanism, and injects calibrated Gaussian noise at the central server, providing per-round privacy guarantees under the assumed sensitivity bound.
Muhammad Irfan Khan, E. Lehtonen, Joni Obradovic et al.
· 0 citations