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Next is the implementation of SAFELearn with homomorphic encryption. Using a server with a single semi-honest server (acting as an aggregator), [Gt] and [Wi] are the results of HE of the model parameters. The clients use a multi-party encryption scheme to encrypt their updates. The HE keys are securely assigned to the clients to decrypt and access the global updates in plaintext for local training. The clients then re-encrypt the generated local model updates and return them to the server, which uses the additive homomorphic property of the encryption scheme to aggregate the encrypted data into a new global model [Gt]. This full HE is computationally intensive and should only be used if a non-complicit server cannot be used due to application and security requirements. |
IEEE/ICACT20220347 Slide.33
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