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Found 2 papers, 1 papers with code
VFL: A Verifiable Federated Learning with Privacy-Preserving for Big Data in Industrial IoT
If no more than n-2 of n participants collude with the aggregation server, VFL could guarantee the encrypted gradients of other participants not being inverted.
Cryptography and Security E.3; I.2.11
Exploiting Defenses against GAN-Based Feature Inference Attacks in Federated Learning
In this paper, we exploit defenses against GAN-based attacks in federated learning, and propose a framework, Anti-GAN, to prevent attackers from learning the real distribution of the victim's data.
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