Differential Secrecy for Distributed Data and Applications to Robust Differentially Secure Vector Summation

22 February 2022

Papers citing "Differential Secrecy for Distributed Data and Applications to Robust Differentially Secure Vector Summation"

10 / 10 papers shown

Title
PREAMBLE: Private and Efficient Aggregation of Block Sparse Vectors and Applications Hilal Asi Vitaly Feldman Hannah Keller G. Rothblum Kunal Talwar FedML 56 1 0 14 Mar 2025
Differentially Private Secure Multiplication: Hiding Information in the Rubble of Noise V. Cadambe Ateet Devulapalli Haewon Jeong Flavio du Pin Calmon 46 1 0 20 Jan 2025
Private Vector Mean Estimation in the Shuffle Model: Optimal Rates Require Many Messages Hilal Asi Vitaly Feldman Jelani Nelson Huy Le Nguyen Kunal Talwar Samson Zhou FedML 27 5 0 16 Apr 2024
Samplable Anonymous Aggregation for Private Federated Data Analysis Kunal Talwar Shan Wang Audra McMillan Vojta Jina Vitaly Feldman ... Congzheng Song Karl Tarbe Sebastian Vogt L. Winstrom Shundong Zhou FedML 32 13 0 27 Jul 2023
Necessary Conditions in Multi-Server Differential Privacy Albert Cheu Chao Yan 24 8 0 17 Aug 2022
Differentially Private Aggregation in the Shuffle Model: Almost Central Accuracy in Almost a Single Message Badih Ghazi Ravi Kumar Pasin Manurangsi Rasmus Pagh Amer Sinha FedML 62 36 0 27 Sep 2021
Differential Privacy in the Shuffle Model: A Survey of Separations Albert Cheu FedML 28 39 0 25 Jul 2021
Private Aggregation from Fewer Anonymous Messages Badih Ghazi Pasin Manurangsi Rasmus Pagh A. Velingker FedML 39 55 0 24 Sep 2019
Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity Ulfar Erlingsson Vitaly Feldman Ilya Mironov A. Raghunathan Kunal Talwar Abhradeep Thakurta 141 420 0 29 Nov 2018
Prochlo: Strong Privacy for Analytics in the Crowd Andrea Bittau Ulfar Erlingsson Petros Maniatis Ilya Mironov A. Raghunathan David Lie Mitch Rudominer Ushasree Kode J. Tinnés B. Seefeld 88 278 0 02 Oct 2017