An Algorithmic Framework For Differentially Private Data Analysis on Trusted Processors

2 July 2018

Papers citing "An Algorithmic Framework For Differentially Private Data Analysis on Trusted Processors"

9 / 9 papers shown

Title
Adore: Differentially Oblivious Relational Database Operators Lianke Qin Rajesh Jayaram E. Shi Zhao Song Danyang Zhuo Shumo Chu 30 14 0 10 Dec 2022
Differentially Private Synthetic Data: Applied Evaluations and Enhancements Lucas Rosenblatt Xiao-Yang Liu Samira Pouyanfar Eduardo de Leon Anuj M. Desai Joshua Allen SyDa 21 64 0 11 Nov 2020
Distributed Differentially Private Mutual Information Ranking and Its Applications Ankit Srivastava Samira Pouyanfar Joshua Allen Ken Johnston Qida Ma 18 0 0 22 Sep 2020
Differentially private cross-silo federated learning Mikko A. Heikkilä A. Koskela Kana Shimizu Samuel Kaski Antti Honkela FedML 29 24 0 10 Jul 2020
Towards Probabilistic Verification of Machine Unlearning David M. Sommer Liwei Song Sameer Wagh Prateek Mittal AAML 13 71 0 09 Mar 2020
SoK: Differential Privacies Damien Desfontaines Balázs Pejó 33 122 0 04 Jun 2019
Contamination Attacks and Mitigation in Multi-Party Machine Learning Jamie Hayes O. Ohrimenko AAML FedML 17 74 0 08 Jan 2019
Amplification by Shuffling: From Local to Central Differential Privacy via Anonymity Ulfar Erlingsson Vitaly Feldman Ilya Mironov A. Raghunathan Kunal Talwar Abhradeep Thakurta 150 420 0 29 Nov 2018
Privacy-Preserving Access of Outsourced Data via Oblivious RAM Simulation M. Goodrich Michael Mitzenmacher 63 269 0 07 Jul 2010