r/FederatedLearning

Y'all see that it protects the privacy of the client but does it actually? Attackers can try to hack the model and reverse engineering might be possible to rebuild the data. Not just that, attackers even manipulate the model by either poisoning the data or the model. Some use multiple accounts to shape the model their own way.

Their are many ways the models can be hurt to avoid convergence, so how do they actually protect their models? I would love to discuss it with people who have read about this.

Thank you

so I am new to federated learning I have grasp of basic concepts of it. Recently I selected Federated learning project for my final year and to my surprise I get allotted to one of the most notoriously strict guide. So I am now being over cautious about how to implement it. Long story short my project data is raw csv and I am now panicking how will they react if in demo I will show them to drop raw csv as input from client side doubting it would be counter intuitive and wont show end to end pipeline if any of you guys know how to prepare and present projects around federated learning I would love to get some advice.