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2011.02352
Cited By
The Limits of Differential Privacy (and its Misuse in Data Release and Machine Learning)
4 November 2020
J. Domingo-Ferrer
David Sánchez
Alberto Blanco-Justicia
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Papers citing
"The Limits of Differential Privacy (and its Misuse in Data Release and Machine Learning)"
41 / 41 papers shown
Privacy Mechanism Design based on Empirical Distributions
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Sara Saeidian
Mikael Skoglund
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147
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26 Sep 2025
Generative Data Refinement: Just Ask for Better Data
Minqi Jiang
João G. M. Araújo
Will Ellsworth
Sian Gooding
Edward Grefenstette
242
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0
10 Sep 2025
Train Once, Forget Precisely: Anchored Optimization for Efficient Post-Hoc Unlearning
Prabhav Sanga
Jaskaran Singh
Arun K. Dubey
MU
133
1
0
17 Jun 2025
Evaluating Differentially Private Synthetic Data Generation in High-Stakes Domains
Conference on Empirical Methods in Natural Language Processing (EMNLP), 2024
Krithika Ramesh
Nupoor Gandhi
Pulkit Madaan
Lisa Bauer
Charith Peris
Anjalie Field
SyDa
240
11
0
10 Oct 2024
Sharper Bounds for Chebyshev Moment Matching, with Applications
Cameron Musco
Christopher Musco
Lucas Rosenblatt
A. Singh
FedML
325
2
0
22 Aug 2024
Reconstructing training data from document understanding models
Jérémie Dentan
Arnaud Paran
A. Shabou
AAML
SyDa
279
3
0
05 Jun 2024
Words Blending Boxes. Obfuscating Queries in Information Retrieval using Differential Privacy
Francesco Luigi De Faveri
G. Faggioli
Nicola Ferro
AAML
199
2
0
15 May 2024
Conciliating Privacy and Utility in Data Releases via Individual Differential Privacy and Microaggregation
Jordi Soria-Comas
David Sánchez
J. Domingo-Ferrer
Sergio Martínez
Luis Del Vasto-Terrientes
198
1
0
21 Dec 2023
A Survey on Privacy of Health Data Lifecycle: A Taxonomy, Review, and Future Directions
Sunanda Bose
D. Marijan
140
4
0
09 Nov 2023
An Examination of the Alleged Privacy Threats of Confidence-Ranked Reconstruction of Census Microdata
Privacy in Statistical Databases (PSD), 2023
David Sánchez
N. Jebreel
J. Domingo-Ferrer
K. Muralidhar
Alberto Blanco-Justicia
182
3
0
06 Nov 2023
Statistical properties and privacy guarantees of an original distance-based fully synthetic data generation method
Rémy Chapelle
Bruno Falissard
170
0
0
10 Oct 2023
A Survey of Data Security: Practices from Cybersecurity and Challenges of Machine Learning
Padmaksha Roy
Jaganmohan Chandrasekaran
Erin Lanus
Laura J. Freeman
Jeremy Werner
388
5
0
06 Oct 2023
Unraveling the Interconnected Axes of Heterogeneity in Machine Learning for Democratic and Inclusive Advancements
Conference on Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO), 2023
Maryam Molamohammadi
Afaf Taik
Nicolas Le Roux
G. Farnadi
250
2
0
11 Jun 2023
Patchwork Learning: A Paradigm Towards Integrative Analysis across Diverse Biomedical Data Sources
Patterns (Patterns), 2023
Suraj Rajendran
Weishen Pan
M. Sabuncu
Yong Chen
Jiayu Zhou
Fei Wang
272
26
0
10 May 2023
When Evolutionary Computation Meets Privacy
IEEE Computational Intelligence Magazine (IEEE CIM), 2023
Bowen Zhao
Wei Chen
Xiaoguo Li
Ximeng Liu
Qingqi Pei
Jun Zhang
198
8
0
22 Mar 2023
Blockchain-Empowered Trustworthy Data Sharing: Fundamentals, Applications, and Challenges
ACM Computing Surveys (ACM Comput. Surv.), 2023
Linh-TX Nguyen
L. Nguyen
Thong Hoang
Dilum Bandara
Qin Wang
Qinghua Lu
Xiwei Xu
Liming Zhu
P. Popovski
Shiping Chen
209
46
0
12 Mar 2023
Algorithmically Effective Differentially Private Synthetic Data
Annual Conference Computational Learning Theory (COLT), 2023
Yi He
Roman Vershynin
Yizhe Zhu
SyDa
237
12
0
11 Feb 2023
Database Reconstruction Is Not So Easy and Is Different from Reidentification
Social Science Research Network (SSRN), 2023
K. Muralidhar
J. Domingo-Ferrer
178
21
0
24 Jan 2023
BDSP: A Fair Blockchain-enabled Framework for Privacy-Enhanced Enterprise Data Sharing
International Conference on Blockchain (ICB), 2022
L. Nguyen
James Hoang
Qin Wang
Qinghua Lu
Sherry Xu
Shiping Chen
FedML
267
6
0
16 Dec 2022
Lessons Learned: Surveying the Practicality of Differential Privacy in the Industry
Proceedings on Privacy Enhancing Technologies (PoPETs), 2022
Gonzalo Munilla Garrido
Xiaoyuan Liu
Florian Matthes
Basel Alomair
280
33
0
07 Nov 2022
GRAIMATTER Green Paper: Recommendations for disclosure control of trained Machine Learning (ML) models from Trusted Research Environments (TREs)
E. Jefferson
J. Liley
Maeve Malone
S. Reel
Alba Crespi-Boixader
...
Christian Cole
F. Ritchie
A. Daly
Simon Rogers
Jim Q. Smith
199
9
0
03 Nov 2022
On the Impossible Safety of Large AI Models
El-Mahdi El-Mhamdi
Sadegh Farhadkhani
R. Guerraoui
Nirupam Gupta
L. Hoang
Rafael Pinot
Sébastien Rouault
John Stephan
363
37
0
30 Sep 2022
"Am I Private and If So, how Many?" - Communicating Privacy Guarantees of Differential Privacy with Risk Communication Formats
Conference on Computer and Communications Security (CCS), 2022
Daniel Franzen
Saskia Nuñez von Voigt
Peter Sorries
Florian Tschorsch
Claudia Muller-Birn
218
26
0
23 Aug 2022
Enhanced Security and Privacy via Fragmented Federated Learning
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022
N. Jebreel
J. Domingo-Ferrer
Alberto Blanco-Justicia
David Sánchez
FedML
251
40
0
13 Jul 2022
Conflicting Interactions Among Protection Mechanisms for Machine Learning Models
AAAI Conference on Artificial Intelligence (AAAI), 2022
S. Szyller
Nadarajah Asokan
AAML
370
13
0
05 Jul 2022
A Roadmap for Greater Public Use of Privacy-Sensitive Government Data: Workshop Report
Chris Clifton
B. Malin
A. Oganian
Ramesh Raskar
Vivek Sharma
FedML
113
1
0
17 Jun 2022
A Critical Review on the Use (and Misuse) of Differential Privacy in Machine Learning
ACM Computing Surveys (ACM CSUR), 2022
Alberto Blanco-Justicia
David Sánchez
J. Domingo-Ferrer
K. Muralidhar
211
93
0
09 Jun 2022
Statistical Data Privacy: A Song of Privacy and Utility
Annual Review of Statistics and Its Application (ARSIA), 2022
Aleksandra B. Slavkovic
Jeremy Seeman
164
32
0
06 May 2022
Private measures, random walks, and synthetic data
M. Boedihardjo
Thomas Strohmer
Roman Vershynin
203
0
0
20 Apr 2022
"Am I Private and If So, how Many?" -- Using Risk Communication Formats for Making Differential Privacy Understandable
Daniel Franzen
Saskia Nuñez von Voigt
Peter Sorries
Florian Tschorsch
Claudia Muller-Birn Freie Universitat Berlin
373
9
0
08 Apr 2022
Privacy: An axiomatic approach
Alexander Ziller
Tamara T. Mueller
R. Braren
Daniel Rueckert
Georgios Kaissis
161
3
0
22 Mar 2022
A review of Generative Adversarial Networks for Electronic Health Records: applications, evaluation measures and data sources
ACM Computing Surveys (ACM CSUR), 2022
Ghadeer O. Ghosheh
Jin Li
T. Zhu
326
55
0
14 Mar 2022
Statistical anonymity: Quantifying reidentification risks without reidentifying users
Gecia Bravo Hermsdorff
R. Busa-Fekete
L. Gunderson
Andrés Munoz Medina
Umar Syed
156
1
0
28 Jan 2022
Fairness, Integrity, and Privacy in a Scalable Blockchain-based Federated Learning System
Timon Rückel
Johannes Sedlmeir
Peter Hofmann
FedML
220
70
0
11 Nov 2021
Bit-efficient Numerical Aggregation and Stronger Privacy for Trust in Federated Analytics
Graham Cormode
I. Markov
FedML
182
10
0
03 Aug 2021
Revealing the Landscape of Privacy-Enhancing Technologies in the Context of Data Markets for the IoT: A Systematic Literature Review
Journal of Network and Computer Applications (JNCA), 2021
Gonzalo Munilla Garrido
Johannes Sedlmeir
Ömer Uludağ
Ilias Soto Alaoui
André Luckow
Florian Matthes
254
55
0
25 Jul 2021
Dynamically Adjusting Case Reporting Policy to Maximize Privacy and Utility in the Face of a Pandemic
J. T. Brown
Chao Yan
Weiyi Xia
Zhijun Yin
Zhiyu Wan
A. Gkoulalas-Divanis
Murat Kantarcioglu
B. Malin
141
2
0
21 Jun 2021
Differential Privacy for Government Agencies -- Are We There Yet?
Journal of the American Statistical Association (JASA), 2021
Joerg Drechsler
235
28
0
17 Feb 2021
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-Anonymity in Practice: How Generalisation and Suppression Affect Machine Learning Classifiers
Computers & security (CS), 2021
D. Slijepcevic
Maximilian Henzl
Lukas Daniel Klausner
Tobias Dam
Peter Kieseberg
Matthias Zeppelzauer
203
52
0
09 Feb 2021
Achieving Security and Privacy in Federated Learning Systems: Survey, Research Challenges and Future Directions
Engineering applications of artificial intelligence (EAAI), 2020
Alberto Blanco-Justicia
J. Domingo-Ferrer
Sergio Martínez
David Sánchez
Adrian Flanagan
K. E. Tan
FedML
218
138
0
12 Dec 2020
Graph Neural Networks in Recommender Systems: A Survey
Shiwen Wu
Fei Sun
Wentao Zhang
Xu Xie
Tengjiao Wang
GNN
948
1,632
0
04 Nov 2020
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