Conventional ML training has the safety concern of collecting all data in a single place and violating the privacy of the data owners. DLFi aims to solve this.
We demonstrate the benefits of a Federated Learning framework for collaborative training of ML-assisted solutions for multi-domain multi-vendor ecosystems.
The demonstration showcases the recent addition of the framework, Secure Aggregation based on Secure Multi Party Computation, which protect the privacy of the parties contributing to the global ML model.
The live demonstration will be carried out on a Kubernetes cluster using Fraunhofer HHI’s Distributed Learning Framework (DLFi) software solution.