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A Critical Review on the Use (and Misuse) of Differential Privacy in
  Machine Learning
v1v2 (latest)

A Critical Review on the Use (and Misuse) of Differential Privacy in Machine Learning

9 June 2022
Alberto Blanco-Justicia
David Sánchez
J. Domingo-Ferrer
K. Muralidhar
ArXiv (abs)PDFHTML

Papers citing "A Critical Review on the Use (and Misuse) of Differential Privacy in Machine Learning"

25 / 25 papers shown
Title
Federated Learning on Non-IID Data: A Survey
Federated Learning on Non-IID Data: A Survey
Hangyu Zhu
Jinjin Xu
Shiqing Liu
Yaochu Jin
OODFedML
98
803
0
12 Jun 2021
Achieving Security and Privacy in Federated Learning Systems: Survey,
  Research Challenges and Future Directions
Achieving Security and Privacy in Federated Learning Systems: Survey, Research Challenges and Future Directions
Alberto Blanco-Justicia
J. Domingo-Ferrer
Sergio Martínez
David Sánchez
Adrian Flanagan
K. E. Tan
FedML
56
113
0
12 Dec 2020
The Limits of Differential Privacy (and its Misuse in Data Release and
  Machine Learning)
The Limits of Differential Privacy (and its Misuse in Data Release and Machine Learning)
J. Domingo-Ferrer
David Sánchez
Alberto Blanco-Justicia
90
109
0
04 Nov 2020
Voting-based Approaches For Differentially Private Federated Learning
Voting-based Approaches For Differentially Private Federated Learning
Yuqing Zhu
Xiang Yu
Yi-Hsuan Tsai
Francesco Pittaluga
M. Faraki
Manmohan Chandraker
Yu Wang
FedML
51
22
0
09 Oct 2020
Local and Central Differential Privacy for Robustness and Privacy in
  Federated Learning
Local and Central Differential Privacy for Robustness and Privacy in Federated Learning
Mohammad Naseri
Jamie Hayes
Emiliano De Cristofaro
FedML
83
150
0
08 Sep 2020
Tempered Sigmoid Activations for Deep Learning with Differential Privacy
Tempered Sigmoid Activations for Deep Learning with Differential Privacy
Nicolas Papernot
Abhradeep Thakurta
Shuang Song
Steve Chien
Ulfar Erlingsson
AAML
204
179
0
28 Jul 2020
LDP-Fed: Federated Learning with Local Differential Privacy
LDP-Fed: Federated Learning with Local Differential Privacy
Stacey Truex
Ling Liu
Ka-Ho Chow
Mehmet Emre Gursoy
Wenqi Wei
FedML
69
395
0
05 Jun 2020
Federated Learning with Bayesian Differential Privacy
Federated Learning with Bayesian Differential Privacy
Aleksei Triastcyn
Boi Faltings
FedML
78
178
0
22 Nov 2019
Federated Learning for Emoji Prediction in a Mobile Keyboard
Federated Learning for Emoji Prediction in a Mobile Keyboard
Swaroop Indra Ramaswamy
Rajiv Mathews
Kanishka Rao
Franccoise Beaufays
FedML
70
313
0
11 Jun 2019
Federated Learning for Mobile Keyboard Prediction
Federated Learning for Mobile Keyboard Prediction
Andrew Straiton Hard
Kanishka Rao
Zhifeng Lin
Swaroop Indra Ramaswamy
Youjie Li
S. Augenstein
Alex Schwing
M. Annavaram
A. Avestimehr
FedML
138
1,549
0
08 Nov 2018
DP-ADMM: ADMM-based Distributed Learning with Differential Privacy
DP-ADMM: ADMM-based Distributed Learning with Differential Privacy
Zonghao Huang
Rui Hu
Yuanxiong Guo
Eric Chan-Tin
Yanmin Gong
FedML
82
197
0
30 Aug 2018
Differentially-Private "Draw and Discard" Machine Learning
Differentially-Private "Draw and Discard" Machine Learning
Vasyl Pihur
Aleksandra Korolova
Frederick Liu
Subhash Sankuratripati
M. Yung
Dachuan Huang
Ruogu Zeng
FedML
74
39
0
11 Jul 2018
ML-Leaks: Model and Data Independent Membership Inference Attacks and
  Defenses on Machine Learning Models
ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models
A. Salem
Yang Zhang
Mathias Humbert
Pascal Berrang
Mario Fritz
Michael Backes
MIACVMIALM
115
951
0
04 Jun 2018
D$^2$: Decentralized Training over Decentralized Data
D2^22: Decentralized Training over Decentralized Data
Hanlin Tang
Xiangru Lian
Ming Yan
Ce Zhang
Ji Liu
54
352
0
19 Mar 2018
Differentially Private Federated Learning: A Client Level Perspective
Differentially Private Federated Learning: A Client Level Perspective
Robin C. Geyer
T. Klein
Moin Nabi
FedML
140
1,300
0
20 Dec 2017
Collecting Telemetry Data Privately
Collecting Telemetry Data Privately
Bolin Ding
Janardhan Kulkarni
Sergey Yekhanin
68
689
0
05 Dec 2017
Renyi Differential Privacy
Renyi Differential Privacy
Ilya Mironov
91
1,268
0
24 Feb 2017
Deep Models Under the GAN: Information Leakage from Collaborative Deep
  Learning
Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning
Briland Hitaj
G. Ateniese
Fernando Perez-Cruz
FedML
133
1,413
0
24 Feb 2017
Membership Inference Attacks against Machine Learning Models
Membership Inference Attacks against Machine Learning Models
Reza Shokri
M. Stronati
Congzheng Song
Vitaly Shmatikov
SLRMIALMMIACV
280
4,168
0
18 Oct 2016
Semi-supervised Knowledge Transfer for Deep Learning from Private
  Training Data
Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data
Nicolas Papernot
Martín Abadi
Ulfar Erlingsson
Ian Goodfellow
Kunal Talwar
94
1,021
0
18 Oct 2016
Federated Optimization: Distributed Machine Learning for On-Device
  Intelligence
Federated Optimization: Distributed Machine Learning for On-Device Intelligence
Jakub Konecný
H. B. McMahan
Daniel Ramage
Peter Richtárik
FedML
145
1,909
0
08 Oct 2016
Deep Learning with Differential Privacy
Deep Learning with Differential Privacy
Martín Abadi
Andy Chu
Ian Goodfellow
H. B. McMahan
Ilya Mironov
Kunal Talwar
Li Zhang
FedMLSyDa
218
6,172
0
01 Jul 2016
Concentrated Differential Privacy: Simplifications, Extensions, and
  Lower Bounds
Concentrated Differential Privacy: Simplifications, Extensions, and Lower Bounds
Mark Bun
Thomas Steinke
97
840
0
06 May 2016
RAPPOR: Randomized Aggregatable Privacy-Preserving Ordinal Response
RAPPOR: Randomized Aggregatable Privacy-Preserving Ordinal Response
Ulfar Erlingsson
Vasyl Pihur
Aleksandra Korolova
109
2,001
0
25 Jul 2014
Differentially Private Empirical Risk Minimization
Differentially Private Empirical Risk Minimization
Kamalika Chaudhuri
C. Monteleoni
Anand D. Sarwate
164
1,490
0
01 Dec 2009
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