VFEFL introduces a CC-DVFE scheme and robust aggregation to achieve privacy-preserving federated learning with malicious client detection without dual-server or trusted-party assumptions.
Model inversion attacks that exploit confidence information and basic countermeasures,
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VFEFL: Privacy-Preserving Federated Learning against Malicious Clients via Verifiable Functional Encryption
VFEFL introduces a CC-DVFE scheme and robust aggregation to achieve privacy-preserving federated learning with malicious client detection without dual-server or trusted-party assumptions.