Related papers: FedZKP: Federated Model Ownership Verification with Zero-knowledge Proof

FedZKP: Federated Model Ownership Verification with Zero-knowledge Proof

URL: http://arxiv.org/abs/2305.04507v2
Date: Wed, 10 May 2023 03:51:26 GMT
Title: FedZKP: Federated Model Ownership Verification with Zero-knowledge Proof
Authors: Wenyuan Yang, Yuguo Yin, Gongxi Zhu, Hanlin Gu, Lixin Fan, Xiaochun Cao, Qiang Yang
Abstract summary: Federated learning (FL) allows multiple parties to cooperatively learn a federated model without sharing private data with each other. We propose a provable secure model ownership verification scheme using zero-knowledge proof, named FedZKP.
Score: 60.990541463214605
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Abstract: Federated learning (FL) allows multiple parties to cooperatively learn a federated model without sharing private data with each other. The need of protecting such federated models from being plagiarized or misused, therefore, motivates us to propose a provable secure model ownership verification scheme using zero-knowledge proof, named FedZKP. It is shown that the FedZKP scheme without disclosing credentials is guaranteed to defeat a variety of existing and potential attacks. Both theoretical analysis and empirical studies demonstrate the security of FedZKP in the sense that the probability for attackers to breach the proposed FedZKP is negligible. Moreover, extensive experimental results confirm the fidelity and robustness of our scheme.

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