Federated Learning homomorphic encryption sample for API
Download and review sample files that show how to run a Federated Learning experiment with Fully Homomorphic Encryption (FHE).
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.
Parent topic: Federated Learning tutorial and samples