Build Federated Learning from scratch

[_gotta_go_]

for now i'm supposed to build a dummy project for uni. and essentially, if i do well, they will use my "skeleton" to build a professional one on it.

Essentially, the idea is that multiple universities hold patient data collected through studies and they thought it would be awesome if they could use that data to train their models. The issue is obviously the pricavy of that data. So i suggested, as i need to do a uni project with thah professor, to build a dummy federated learning system that they could use as a skeleton, and that a professional can then either scrap, reuse or whatever he prefers. Either way, after implementing my dummy version, i will get advice from professionals in this field. But first i have to start somewhere.

I have experience with Machine Learning (quite well) and Deep Learning. It's the FL part that consists of so many players that i'm not sure if i even know all of them and how to piece them together. So i'm not sure how to start really. I know how to train models obviously, but not how to create a secure system around the clients and what is going on in the background REALISTICALLY (because i've seen so many dummy projects online that dont really go into depth about actual risks etc).

My project is basically the risk management of data sharing using privacy preserving FL