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InfoResearchPeer-reviewed
CVFL-Pro: A Collusion-Resistant Verification Federated Learning Framework With Adaptive Communication Optimization
- Published
- Record updated
Summary
CVFL-Pro is a verifiable federated learning framework that lets clients check whether a malicious server has falsified aggregation results, without a trusted authority. It combines masking and Shamir's secret sharing for privacy and dropout robustness, a lightweight MAC scheme with auxiliary nodes for verifiability, and an adaptive compression algorithm, AOTop-k. On MNIST, CIFAR-10 and CIFAR-100 it cuts communication overhead by 58.07% versus Top-k and 95.81% versus SecAgg, while maintaining accuracy.