Author

U. Atmaca

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Preprint Jul 2026

PRoVeFL: Private Robust and Verifiable Aggregation in Federated Learning

This work proposes PRoVeFL-a novel, modular FL framework that is Privacy-preserving, Byzantine-Robust, and ensures Verifiable aggregation, and improves runtime over the prior works, Prio and ELSA, based on distributed trust with comparable security guarantees, up to 100x and 10x, respectively.

Harsh Kasyap, Anil Kumar Pradhan, U. Atmaca et al. · 0 citations