williamdevena / Defending-federated-learning-system

Implementation of a client reputation, gradient checking and homomorphic encryption mechanism to defend a federated learning system from data/model poisoning and reverse engineering attacks.
12Updated last year

Alternatives and similar repositories for Defending-federated-learning-system:

Users that are interested in Defending-federated-learning-system are comparing it to the libraries listed below