【一种利用插值验证的FL隐私保护框架】VFL: A Verifiable Federated Learning

原文标题：VFL: A Verifiable Federated Learning with Privacy-Preserving for Big Data in Industrial IoT

本文 use Lagrange interpolation to elaborately set interpolation points for verifying the correctness of the aggregated gradients. Compared with existing schemes, the verification overhead of VFL remains constant regardless of the number of participants.
具体的效果：participants can detect forged results with an overwhelming probability.

这篇文章值得关注的创新点在于用拉格朗日插值来判断聚合的参数有无问题，但是还涉及很多别的东西，所以这里不详细介绍了。