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Author

Puneet Garg

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Conference Open access Jul 2026

Federated Learning with Differential Privacy: A Comprehensive Framework for Privacy-Preserving Distributed Machine Learning

This study implemented a comprehensive experimental framework for analysing FL performance using standard FL aggregation protocols FedAvg, FedProx, and SCAFFOLD in conjunction with Differential Privacy mechanisms; specifically, the Gaussian noise mechanism with Rényi Differential Privacy (RDP) accountants.

Himanshi Singh, Kahksha Ahmed, Priyanshu Prajapati et al. · 0 citations