Suleiman A. Khan

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.