Understanding Differential Privacy in Decentralized Federated Learning: A Controlled Privacy–Utility Comparison
Centralized Federated Learning (FL) enables collaborative model training without sharing raw data. Differential privacy (DP) is widely used to protect sensitive information in FL; however, its behavior in decentralized environments remains poorly understood. This study empirically compares centralized FL and sequential...