VERT defends federated learning against large-scale model poisoning by selecting, in each round, the users whose gradients best match an autoregressive prediction from each user's own history.
Wild patterns reloaded: A survey of machine learning security against training data poisoning,
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How to Defend Against Large-scale Model Poisoning Attacks in Federated Learning: A Vertical Solution
VERT defends federated learning against large-scale model poisoning by selecting, in each round, the users whose gradients best match an autoregressive prediction from each user's own history.