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Recent advances in synthetic data generation (SDG) have been hailed as a solution to the difficult problem of sharing sensitive data while protecting privacy.
On a Least Squares Adjustment of a Sampled Frequency Table When the Expected Marginal Totals are Known
W Edwards Deming and Frederick F Stephan · 1940
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Statistical Disclosure Limitation
Donald B Rubin · 1993
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Weaving Technology and Policy Together to Maintain Confidentiality
Latanya Sweeney · 1997
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Simple demographics often identify people uniquely
Latanya Sweeney · 2000
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Revealing Information while Preserving Privacy
Irit Dinur and Kobbi Nissim · 2003
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Using CART to Generate Partially Synthetic Public Use Microdata
Jerome P Reiter · 2005
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Calibrating Noise to Sensitivity in Private Data Analysis
Cynthia Dwork, Frank McSherry, Kobbi Nissim, and Adam Smith · 2006
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The price of privacy and the limits of LP decoding
Cynthia Dwork, Frank McSherry, and Kunal Talwar · 2007
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Broken Promises of Privacy: Responding to the Surprising Failure of Anonymization
Paul Ohm · 2009
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The Power of Linear Reconstruction Attacks
Shiva Prasad Kasiviswanathan, Mark Rudelson, and Adam Smith · 2013
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The algorithmic foundations of differential privacy
Cynthia Dwork and Aaron Roth · 2014
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Privacy in Pharmacogenetics: An End-to-End Case Study of Personalized Warfarin Dosing
Matthew Fredrikson, Eric Lantz, Somesh Jha, Simon Lin, David Page, and Thomas Ristenpart · 2014
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Article 29 Data Protection Working Party. Opinion 05/2014 on anonymisation techniques
Information Commissioner’s Office · 2014
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Estimation of treatment effects from combined data: Identification versus data security
Tatiana Komarova, Denis Nekipelov, and Evgeny Yakovlev · 2015
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Copula-Based Approach to Synthetic Population Generation
Byungduk Jeong, Wonjoon Lee, Deok-Soo Kim, and Hayong Shin · 2016
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Statistical inference considered harmful
Frank McSherry · 2016
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Measurement error and the replication crisis
Eric Loken and Andrew Gelman · 2017
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DataSynthesizer: Privacy-Preserving Synthetic Datasets
Haoyue Ping, Julia Stoyanovich, and Bill Howe · 2017
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What Does The Crowd Say About You? Evaluating Aggregation-based Location Privacy
Apostolos Pyrgelis, Carmela Troncoso, and Emiliano De Cristofaro · 2017
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Membership Inference Attacks against Machine Learning Models
Reza Shokri, Marco Stronati, Congzheng Song, and Vitaly Shmatikov · 2017
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PrivBayes: Private Data Release via Bayesian Networks
Jun Zhang, Graham Cormode, Cecilia M Procopiuc, Divesh Srivastava, and Xiaokui Xiao · 2017
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The creation and use of the SIPP synthetic Beta v7.0
Gary Benedetto, Jordan C Stanley, Evan Totty, et al · 2018
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2018 Differential Privacy Synthetic Data Challenge
National Institute of Standards and Technology · 2018
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Knock Knock, Who’s There? Membership Inference on Aggregate Location Data
Apostolos Pyrgelis, Carmela Troncoso, and Emiliano De Cristofaro · 2018
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Technical Privacy Metrics: A Systematic Survey
Isabel Wagner and David Eckhoff · 2018
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Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting
Samuel Yeom, Irene Giacomelli, Matt Fredrikson, and Somesh Jha · 2018
Cited alongside, same era.
Differential privacy has disparate impact on model accuracy
Eugene Bagdasaryan, Omid Poursaeed, and Vitaly Shmatikov · 2019
Cited alongside, same era.
When the signal is in the noise: Exploiting Diffix’s Sticky Noise
Andrea Gadotti, Florimond Houssiau, Luc Rocher, Benjamin Livshits, and Yves-Alexandre de Montjoye · 2019
Cited alongside, same era.
LOGAN: Membership Inference Attacks Against Generative Models
Jamie Hayes, Luca Melis, George Danezis, and Emiliano De Cristofaro · 2019
Cited alongside, same era.
Monte Carlo and Reconstruction Membership Inference Attacks against Generative Models
Benjamin Hilprecht, Martin Härterich, and Daniel Bernau · 2019
Cited alongside, same era.
Empirical Evaluation on Synthetic Data Generation with Generative Adversarial Network
Winning the nist contest: A scalable and general approach to differentially private synthetic data
Ryan McKenna, Gerome Miklau, and Daniel Sheldon · 2021
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Chapter 2: How do we ensure anonymisation is effective?
Information Commissioner’s Office · 2021
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Challenge Design and Lessons Learned from the 2018 Differential Privacy Challenges, 2021
Diane Ridgeway, Mary F Theofanos, Terese W Manley, and Christine Task · 2021
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Benchmarking Differentially Private Synthetic Data Generation Algorithms
Yuchao Tao, Ryan McKenna, Michael Hay, Ashwin Machanavajjhala, and Gerome Miklau · 2021
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Differentially Private Learning Needs Better Features (or Much More Data)
Florian Tramer and Dan Boneh · 2021
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Pei-Hsuan Lu, Pang-Chieh Wang, and Chia-Mu Yu · 2019
Cited alongside, same era.
Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference Attacks against Centralized and Federated Learning
Milad Nasr, Reza Shokri, and Amir Houmansadr · 2019
Cited alongside, same era.
Estimating the success of re-identifications in incomplete datasets using generative models
Luc Rocher, Julien M Hendrickx, and Yves-Alexandre de Montjoye · 2019
Cited alongside, same era.
Modeling Tabular data using Conditional GAN
Lei Xu, Maria Skoularidou, Alfredo Cuesta-Infante, and Kalyan Veeramachaneni · 2019
Cited alongside, same era.
Assessing privacy and quality of synthetic health data
Andrew Yale, Saloni Dash, Ritik Dutta, Isabelle Guyon, Adrien Pavao, and Kristin P Bennett · 2019
Cited alongside, same era.
Data Metrics for 2020 Disclosure Avoidance
US Census 2020 · 2020
Cited alongside, same era.
GAN-Leaks: A Taxonomy of Membership Inference Attacks against Generative Models
Dingfan Chen, Ning Yu, Yang Zhang, and Mario Fritz · 2020
Cited alongside, same era.
Membership Inference Attacks From First Principles
Nicholas Carlini, Steve Chien, Milad Nasr, Shuang Song, Andreas Terzis, and Florian Tramer · 2022
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Attacks on Deidentification’s Defenses
Aloni Cohen · 2022
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QuerySnout: Automating the Discovery of Attribute Inference Attacks against Query-Based Systems
Ana-Maria Cretu, Florimond Houssiau, Antoine Cully, and Yves-Alexandre de Montjoye · 2022
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Pool Inference Attacks on Local Differential Privacy: Quantifying the Privacy Guarantees of Apple’s Count Mean Sketch in Practice
Andrea Gadotti, Florimond Houssiau, Meenatchi Sundaram Muthu Selva Annamalai, and Yves-Alexandre de Montjoye · 2022
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Robin Hood and Matthew Effects: Differential Privacy Has Disparate Impact on Synthetic Data
Georgi Ganev, Bristena Oprisanu, and Emiliano De Cristofaro · 2022
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TAPAS: a Toolbox for Adversarial Privacy Auditing of Synthetic Data
Florimond Houssiau, James Jordon, Samuel N Cohen, Andrew Elliott, James Geddes, Callum Mole, Camila Rangel-Smith, and Lukasz Szpruch · 2022
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Multipurpose synthetic population for policy applications
Jiri Hradec, Massimo Craglia, Margherita Di Leo, Sarah De Nigris, Nicole Ostlaender, and Nicholas Nicholson · 2022
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Are Attribute Inference Attacks Just Imputation?
Bargav Jayaraman and David Evans · 2022
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AIM: An Adaptive and Iterative Mechanism for Differentially Private Synthetic Data
Ryan McKenna, Brett Mullins, Daniel Sheldon, and Gerome Miklau · 2022
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On Utility and Privacy in Synthetic Genomic Data
Bristena Oprisanu, Georgi Ganev, and Emiliano De Cristofaro · 2022
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What is synthetic data, and how can it advance research and development?
The Royal Society · 2022
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Synthetic Data – Anonymisation Groundhog Day
Theresa Stadler, Bristena Oprisanu, and Carmela Troncoso · 2022
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Enhanced Membership Inference Attacks against Machine Learning Models
Jiayuan Ye, Aadyaa Maddi, Sasi Kumar Murakonda, Vincent Bindschaedler, and Reza Shokri · 2022
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Membership inference attacks against synthetic health data
Ziqi Zhang, Chao Yan, and Bradley A Malin · 2022
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Challenges towards the next frontier in privacy
Rachel Cummings, Damien Desfontaines, David Evans, Roxana Geambasu, Matthew Jagielski, Yangsibo Huang, Peter Kairouz, Gautam Kamath, Sewoong Oh, Olga Ohrimenko, et al · 2023
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Confidence-ranked reconstruction of census microdata from published statistics
Travis Dick, Cynthia Dwork, Michael Kearns, Terrance Liu, Aaron Roth, Giuseppe Vietri, and Zhiwei Steven Wu · 2023
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A Unified Framework for Quantifying Privacy Risk in Synthetic Data
Matteo Giomi, Franziska Boenisch, Christoph Wehmeyer, and Borbála Tasnádi · 2023
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Managing re-identification risks while providing access to the All of Us research program
Weiyi Xia, Melissa Basford, Robert Carroll, Ellen Wright Clayton, Paul Harris, Murat Kantacioglu, Yongtai Liu, Steve Nyemba, Yevgeniy Vorobeychik, Zhiyu Wan, and Bradley A Malin · 2023
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Data Forensics in Diffusion Models: A Systematic Analysis of Membership Privacy
Derui Zhu, Dingfan Chen, Jens Grossklags, and Mario Fritz · 2023
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