Smart Policy Control for Securing Federated Learning Management System. (arXiv:2305.09134v1 [cs.CR])

The widespread adoption of Internet of Things (IoT) devices in smart cities,
intelligent healthcare systems, and various real-world applications have
resulted in the generation of vast amounts of data, often analyzed using
different Machine Learning (ML) models. Federated learning (FL) has been
acknowledged as a privacy-preserving machine learning technology, where
multiple parties cooperatively train ML models without exchanging raw data.
However, the current FL architecture does not allow for an audit of the
training process due to the various data-protection …

adoption applications cities control data devices federated learning healthcare internet internet of things iot machine machine learning management policy privacy smart smart cities system systems technology things vast world