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Hear No Evil: Detecting Gradient Leakage by Malicious Servers in Federated Learning
and-cluster-computingartificial-intelligencecryptography-and-securitydistributedmachine-learningparallel
Recent work has shown that gradient updates in federated learning (FL) can unintentionally reveal sensitive information about a client's local data. This risk becomes significantly greater when a malicious server manipulates the global model to provoke information-rich updates from clients. In this
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