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Found 2 papers, 1 papers with code
POSEIDON: Privacy-Preserving Federated Neural Network Learning
In this paper, we address the problem of privacy-preserving training and evaluation of neural networks in an $N$-party, federated learning setting.
Privacy and Integrity Preserving Computations with CRISP
Service providers are interested in verifying the integrity of the users' data to improve their services and obtain useful knowledge for their business.
Cryptography and Security
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