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.
Fast and scalable private genotype imputation us- ing machine learning and partially homomorphic encryption,
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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.