ByzSFL combines partial homomorphic encryption with zk-SNARKs to let clients prove FLTrust aggregation weights in secure federated learning, claiming large speedups, but the protocol math and evaluation are not yet coherent.
Fedatm: Adap- tive trimmed mean based federated learning against model poison- ing attacks,
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ByzSFL: Achieving Byzantine-Robust Secure Federated Learning with Zero-Knowledge Proofs
ByzSFL combines partial homomorphic encryption with zk-SNARKs to let clients prove FLTrust aggregation weights in secure federated learning, claiming large speedups, but the protocol math and evaluation are not yet coherent.