Mitigation of poisoning attack in federated learning by using historical distance detection

The federated learning makes it possible for users to jointly train a model while keeps their data stored locally. It is an original privacy preserving machine learning framework. Meanwhile, there exists availability and integrity threats in the framework. There may be malicious clients pretending the benign ones to interfere global model owning to the local model's indifference at server aggregat...