OLYMPIA: A Simulation Framework for Evaluating the Concrete Scalability
of Secure Aggregation Protocols

v1v2 (latest)

OLYMPIA: A Simulation Framework for Evaluating the Concrete Scalability of Secure Aggregation Protocols

20 February 2023

Ivoline C. Ngong

Nicholas J. Gibson

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Papers citing "OLYMPIA: A Simulation Framework for Evaluating the Concrete Scalability of Secure Aggregation Protocols"

8 / 8 papers shown

Title
On Lattices, Learning with Errors, Random Linear Codes, and Cryptography O. Regev LRM 112 1,081 0 08 Jan 2024
EIFFeL: Ensuring Integrity for Federated Learning A. Chowdhury Chuan Guo S. Jha Laurens van der Maaten FedML 124 78 0 23 Dec 2021
Differentially Private Secure Multi-Party Computation for Federated Learning in Financial Applications David Byrd Antigoni Polychroniadou FedML 52 157 0 12 Oct 2020
FastSecAgg: Scalable Secure Aggregation for Privacy-Preserving Federated Learning S. Kadhe Nived Rajaraman O. O. Koyluoglu Kannan Ramchandran FedML 85 164 0 23 Sep 2020
ARIANN: Low-Interaction Privacy-Preserving Deep Learning via Function Secret Sharing T. Ryffel Pierre Tholoniat D. Pointcheval Francis R. Bach FedML 127 99 0 08 Jun 2020
Advances and Open Problems in Federated Learning Peter Kairouz H. B. McMahan Brendan Avent A. Bellet M. Bennis ... Zheng Xu Qiang Yang Felix X. Yu Han Yu Sen Zhao FedML AI4CE 270 6,285 0 10 Dec 2019
ABIDES: Towards High-Fidelity Market Simulation for AI Research David Byrd Maria Hybinette T. Balch 51 68 0 26 Apr 2019
Prio: Private, Robust, and Scalable Computation of Aggregate Statistics Henry Corrigan-Gibbs Dan Boneh 36 353 0 18 Mar 2017

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