Homomorphic encryption

FHE is an advanced, optional method to provide additional security and privacy for your data by encrypting data sent between parties and the aggregator. This method still creates a computational result that is the same as if the computations were done on unencrypted data. For more details on applying homomorphic encryption in Federated Learning, see Applying encryption.

Download the Federated Learning sample files

Download the following notebooks.

Federated Learning FHE Demo

Parent topic: Federated Learning tutorial and samples