Model-based attribute inference attacks outperform gradient-based attacks for federated regression, especially when the attacker approximates the client's local model.
This suggests that σ2 min(Θout) grows linearly with nc and then it is possible to lower bound λmin ΘT outΘout nc with a positive constant
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Attribute Inference Attacks for Federated Regression Tasks
Model-based attribute inference attacks outperform gradient-based attacks for federated regression, especially when the attacker approximates the client's local model.