Collecting Telemetry Data Privately

5 December 2017

Papers citing "Collecting Telemetry Data Privately"

50 / 346 papers shown

Title
Differentially Private Label Protection in Split Learning Xin Yang Jiankai Sun Yuanshun Yao Junyuan Xie Chong-Jun Wang FedML 100 36 0 04 Mar 2022
Private High-Dimensional Hypothesis Testing Shyam Narayanan FedML 80 12 0 03 Mar 2022
Private Convex Optimization via Exponential Mechanism Sivakanth Gopi Y. Lee Daogao Liu 136 54 0 01 Mar 2022
Degree-Preserving Randomized Response for Graph Neural Networks under Local Differential Privacy Seira Hidano Takao Murakami 70 9 0 21 Feb 2022
Using Illustrations to Communicate Differential Privacy Trust Models: An Investigation of Users' Comprehension, Perception, and Data Sharing Decision Aiping Xiong Chuhao Wu Tianhao Wang R. Proctor Jeremiah Blocki Ninghui Li S. Jha 54 13 0 21 Feb 2022
Nonparametric extensions of randomized response for private confidence sets Ian Waudby-Smith Zhiwei Steven Wu Aaditya Ramdas 81 9 0 17 Feb 2022
Private Quantiles Estimation in the Presence of Atoms Clément Lalanne C. Gastaud Nicolas Grislain Aurélien Garivier Rémi Gribonval 38 8 0 15 Feb 2022
One-bit Submission for Locally Private Quasi-MLE: Its Asymptotic Normality and Limitation Hajime Ono Kazuhiro Minami H. Hino 42 0 0 15 Feb 2022
Privacy Concerns Raised by Pervasive User Data Collection From Cyberspace and Their Countermeasures Yinhao Jiang Ba-Dung Le T. Zia Praveen Gauravaram 37 1 0 09 Feb 2022
Rainbow Differential Privacy Ziqi Zhou Onur Gunlu Rafael G. L. DÓliveira Muriel Médard Parastoo Sadeghi Rafael F. Schaefer 51 3 0 08 Feb 2022
Locally Differentially Private Distributed Deep Learning via Knowledge Distillation Di Zhuang Mingchen Li Jerome Chang FedML 21 2 0 07 Feb 2022
Aggregation and Transformation of Vector-Valued Messages in the Shuffle Model of Differential Privacy Mary Scott Graham Cormode Carsten Maple 80 11 0 31 Jan 2022
Plume: Differential Privacy at Scale Kareem Amin Jennifer Gillenwater Matthew Joseph Alex Kulesza Sergei Vassilvitskii 61 9 0 27 Jan 2022
Towards Private Learning on Decentralized Graphs with Local Differential Privacy Wanyu Lin Baochun Li Cong Wang FedML 92 47 0 23 Jan 2022
Differentially Private SGDA for Minimax Problems Zhenhuan Yang Shu Hu Yunwen Lei Kush R. Varshney Siwei Lyu Yiming Ying 68 21 0 22 Jan 2022
Reducing Noise Level in Differential Privacy through Matrix Masking A. Ding Samuel S. Wu G. Miao Shigang Chen 61 2 0 11 Jan 2022
Optimal and Differentially Private Data Acquisition: Central and Local Mechanisms Alireza Fallah A. Makhdoumi Azarakhsh Malekian Asuman Ozdaglar FedML 95 32 0 10 Jan 2022
On robustness and local differential privacy Mengchu Li Thomas B. Berrett Yi Yu 70 26 0 03 Jan 2022
Randomize the Future: Asymptotically Optimal Locally Private Frequency Estimation Protocol for Longitudinal Data O. Ohrimenko Anthony Wirth Hao Wu 28 5 0 22 Dec 2021
Randomized Response Mechanisms for Differential Privacy Data Analysis: Bounds and Applications Fei Ma Ping Wang 58 5 0 14 Dec 2021
Applying the Shuffle Model of Differential Privacy to Vector Aggregation Mary Scott Graham Cormode Carsten Maple FedML 95 3 0 10 Dec 2021
OPTT: Optimal Piecewise Transformation Technique for Analyzing Numerical Data under Local Differential Privacy Fei Ma Renbo Zhu Ping Wang 43 1 0 09 Dec 2021
Private Robust Estimation by Stabilizing Convex Relaxations Pravesh Kothari Pasin Manurangsi A. Velingker 71 47 0 07 Dec 2021
Locally Differentially Private Sparse Vector Aggregation Mingxun Zhou Tianhao Wang T-H. Hubert Chan Giulia Fanti E. Shi FedML 100 29 0 07 Dec 2021
Optimum Noise Mechanism for Differentially Private Queries in Discrete Finite Sets Sachin Kadam Anna Scaglione Nikhil Ravi S. Peisert B. Lunghino Aram Shumavon 32 0 0 23 Nov 2021
Poisoning Attacks to Local Differential Privacy Protocols for Key-Value Data Yongji Wu Xiaoyu Cao Jinyuan Jia Neil Zhenqiang Gong AAML 61 34 0 22 Nov 2021
The Internet of Federated Things (IoFT): A Vision for the Future and In-depth Survey of Data-driven Approaches for Federated Learning Raed Al Kontar Naichen Shi Xubo Yue Seokhyun Chung E. Byon ... Chinedum Okwudire Garvesh Raskutti R. Saigal Karandeep Singh Ye Zhisheng FedML 106 52 0 09 Nov 2021
Distribution-Invariant Differential Privacy Xuan Bi Xiaotong Shen 44 14 0 08 Nov 2021
Improving the utility of locally differentially private protocols for longitudinal and multidimensional frequency estimates Héber H. Arcolezi Jean-François Couchot Bechara al Bouna X. Xiao 50 29 0 08 Nov 2021
Locally Differentially Private Bayesian Inference Tejas D. Kulkarni Hibiki Ito Samuel Kaski Antti Honkela 73 2 0 27 Oct 2021
An Uncertainty Principle is a Price of Privacy-Preserving Microdata John M. Abowd Robert Ashmead Ryan Cumings-Menon S. Garfinkel Daniel Kifer Philip Leclerc William Sexton Ashley Simpson Christine Task Pavel I Zhuravlev 72 16 0 25 Oct 2021
User-Level Private Learning via Correlated Sampling Badih Ghazi Ravi Kumar Pasin Manurangsi FedML 125 13 0 21 Oct 2021
AHEAD: Adaptive Hierarchical Decomposition for Range Query under Local Differential Privacy L. Du Zhikun Zhang Shaojie Bai Changchang Liu S. Ji Peng Cheng Jiming Chen 142 38 0 14 Oct 2021
Infinitely Divisible Noise in the Low Privacy Regime Rasmus Pagh N. Stausholm FedML 50 2 0 13 Oct 2021
"I need a better description'': An Investigation Into User Expectations For Differential Privacy Rachel Cummings Gabriel Kaptchuk Elissa M. Redmiles 81 84 0 13 Oct 2021
Offset-Symmetric Gaussians for Differential Privacy Parastoo Sadeghi Mehdi Korki 78 8 0 13 Oct 2021
Task-aware Privacy Preservation for Multi-dimensional Data Jiangnan Cheng A. Tang Sandeep P. Chinchali 68 7 0 05 Oct 2021
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 127 37 0 27 Sep 2021
A Validated Privacy-Utility Preserving Recommendation System with Local Differential Privacy Seryne Rahali M. Laurent Souha Masmoudi Charles Roux Brice Mazeau 15 7 0 23 Sep 2021
The power of private likelihood-ratio tests for goodness-of-fit in frequency tables Emanuele Dolera Stefano Favaro 23 1 0 20 Sep 2021
DPGen: Automated Program Synthesis for Differential Privacy Yuxin Wang Zeyu Ding Yingtai Xiao Daniel Kifer Qiang Yan SyDa 78 12 0 15 Sep 2021
Random Sampling Plus Fake Data: Multidimensional Frequency Estimates With Local Differential Privacy Héber H. Arcolezi Jean-François Couchot Bechara al Bouna Xiaokui Xiao 53 27 0 15 Sep 2021
Statistical Quantification of Differential Privacy: A Local Approach Önder Askin T. Kutta Holger Dette 78 15 0 21 Aug 2021
Real-World Trajectory Sharing with Local Differential Privacy Teddy Cunningham Graham Cormode Hakan Ferhatosmanoglu D. Srivastava 60 50 0 04 Aug 2021
Bit-efficient Numerical Aggregation and Stronger Privacy for Trust in Federated Analytics Graham Cormode I. Markov FedML 55 10 0 03 Aug 2021
Privacy-Aware Rejection Sampling Jordan Awan Vinayak A. Rao 63 7 0 02 Aug 2021
Faster Rates of Private Stochastic Convex Optimization Jinyan Su Lijie Hu Di Wang 53 13 0 31 Jul 2021
Selective MPC: Distributed Computation of Differentially Private Key-Value Statistics Thomas Humphries Rasoul Akhavan Mahdavi Shannon Veitch Florian Kerschbaum 69 12 0 26 Jul 2021
High Dimensional Differentially Private Stochastic Optimization with Heavy-tailed Data Lijie Hu Shuo Ni Hanshen Xiao Di Wang 132 53 0 23 Jul 2021
Renyi Differential Privacy of the Subsampled Shuffle Model in Distributed Learning Antonious M. Girgis Deepesh Data Suhas Diggavi FedML 69 21 0 19 Jul 2021