Enhancing Trust by a Keycloak-Flower Integration for Federated Machine Learning

Since its introduction, federated learning (FL) has attracted a lot of attention in the medical field, but its actual application in healthcare organisations remains limited. Flower is a leading FL framework known for its good documentation and wide application. To close security gaps, we propose to integrate Keycloak with gRPC and Flower to improve identity and access management. We have developed a lightweight Python module that integrates both and also validates the client's code with the server before execution. The system has been tested in a simple prototype, but further work and security testing is required for a complex evaluation.