$98\%$ of encrypted local models are recovered within 21 h). Then, we propose VerSA, a verifiable secure aggregation protocol for cross-device federated learning. VerSA does not require any trusted setup for verification between users while minimizing the verification cost by enabling both the central server and users to utilize only a lightweight pseudorandom generator to prove and verify the correctness of model aggregation. We experimentally confirm the efficiency of VerSA under diverse datasets, demonstrating that VerSA is orders of magnitude faster than verification in prior work.">

VerSA: Verifiable Secure Aggregation for Cross-Device Federated Learning (original) (raw)

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