An implementation of Secure Aggregation algorithm based on "Practical Secure Aggregation for Privacy-Preserving Machine Learning (Bonawitz et. al)" in Python.

Privacy-Preserving Data Analysis using Pandas

Efficient Secure Aggregation for Privacy-Preserving Federated Machine Learning

A sublinear secure aggregation protocol implementation

An implementation of the secure aggregation algorithm for federated learning

Secure Aggregation with Shamir’s Method

Implementation of the Heflp, a framework enabling practical and overflow-safe federated learning.

Comparison of several approaches for the PRIvate ESTimation of KL-Divergence (PRIEST-KLD)