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Federated learning (FL) allows multiple parties to cooperatively learn afederated model without sharing private data with each other. The need ofprotecting such federated models from being plagiarized or misused, therefore,motivates us to propose a provable secure model ownership verification schemeusing zero-knowledge proof, named FedZKP. It is shown that the FedZKP schemewithout disclosing credentials is guaranteed to defeat a variety of existingand potential attacks. Both theoretical analysis and empirical studiesdemonstrate the security of FedZKP in the sense that the probability forattackers to breach the proposed FedZKP is negligible. Moreover, extensiveexperimental results confirm the fidelity and robustness of our scheme.

FedZKP: Federated Model Ownership Verification with Zero-knowledge Proof