Techniques for providing secure federated machine-learning

Abstract

Embodiments of the invention are directed to systems, methods, and devices for securely performing federated tasks (e.g., the generation and utilizing of machine-learning models). A secure platform computer may operate a secure memory space. Entities participating in a federated project may transmit respective portions of project data defining the federated project. Each entity may provide their respective (encrypted) data sets for the project that in turn can be used to generate a machine-learning model in accordance with the project data. The machine-learning model may be stored in the secure memory space and accessed through an interface provided by the secure platform computer Utilizing the techniques discussed herein, a machine-learning models may be generated and access to these models may be restricted while protect each participant's data set from being exposed to the other project participants.