Gaussian differential privacy
Author
Abstract
Suggested Citation
DOI: 10.1111/rssb.12454
Download full text from publisher
References listed on IDEAS
- John C. Duchi & Michael I. Jordan & Martin J. Wainwright, 2018. "Minimax Optimal Procedures for Locally Private Estimation," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(521), pages 182-201, January.
- Wasserman, Larry & Zhou, Shuheng, 2010. "A Statistical Framework for Differential Privacy," Journal of the American Statistical Association, American Statistical Association, vol. 105(489), pages 375-389.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Zilong Cao & Xiao Guo & Hai Zhang, 2023. "Privacy-Preserving Distributed Learning via Newton Algorithm," Mathematics, MDPI, vol. 11(18), pages 1-21, September.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Bi, Xuan & Shen, Xiaotong, 2023. "Distribution-invariant differential privacy," Journal of Econometrics, Elsevier, vol. 235(2), pages 444-453.
- John M. Abowd & Ian M. Schmutte & William Sexton & Lars Vilhuber, 2019. "Suboptimal Provision of Privacy and Statistical Accuracy When They are Public Goods," Papers 1906.09353, arXiv.org.
- Kroll, Martin, 2022. "On the universal consistency of histograms anonymised by a randomised response technique," Statistics & Probability Letters, Elsevier, vol. 185(C).
- Claire McKay Bowen & Fang Liu & Bingyue Su, 2021. "Differentially private data release via statistical election to partition sequentially," METRON, Springer;Sapienza Università di Roma, vol. 79(1), pages 1-31, April.
- Ron S. Jarmin & John M. Abowd & Robert Ashmead & Ryan Cumings-Menon & Nathan Goldschlag & Michael B. Hawes & Sallie Ann Keller & Daniel Kifer & Philip Leclerc & Jerome P. Reiter & Rolando A. RodrÃgue, 2023.
"An in-depth examination of requirements for disclosure risk assessment,"
Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 120(43), pages 2220558120-, October.
- Ron S. Jarmin & John M. Abowd & Robert Ashmead & Ryan Cumings-Menon & Nathan Goldschlag & Michael B. Hawes & Sallie Ann Keller & Daniel Kifer & Philip Leclerc & Jerome P. Reiter & Rolando A. Rodr'igue, 2023. "An In-Depth Examination of Requirements for Disclosure Risk Assessment," Papers 2310.09398, arXiv.org.
- Ron S. Jarmin & John M. Abowd & Robert Ashmead & Ryan Cumings-Menon & Nathan Goldschlag & Michael B. Hawes & Sallie Ann Keller & Daniel Kifer & Philip Leclerc & Jerome P. Reiter & Rolando A. Rodr�guez, 2023. "An In-Depth Examination of Requirements for Disclosure Risk Assessment," Working Papers 23-49, Center for Economic Studies, U.S. Census Bureau.
- Raj Chetty & John N. Friedman, 2019.
"A Practical Method to Reduce Privacy Loss When Disclosing Statistics Based on Small Samples,"
AEA Papers and Proceedings, American Economic Association, vol. 109, pages 414-420, May.
- Raj Chetty & John N. Friedman, 2019. "A Practical Method to Reduce Privacy Loss when Disclosing Statistics Based on Small Samples," NBER Working Papers 25626, National Bureau of Economic Research, Inc.
- John M. Abowd & Robert Ashmead & Ryan Cumings-Menon & Simson Garfinkel & Micah Heineck & Christine Heiss & Robert Johns & Daniel Kifer & Philip Leclerc & Ashwin Machanavajjhala & Brett Moran & William, 2022. "The 2020 Census Disclosure Avoidance System TopDown Algorithm," Papers 2204.08986, arXiv.org.
- Matthew J. Schneider & Dawn Iacobucci, 2020. "Protecting survey data on a consumer level," Journal of Marketing Analytics, Palgrave Macmillan, vol. 8(1), pages 3-17, March.
- Katherine B. Coffman & Lucas C. Coffman & Keith M. Marzilli Ericson, 2017.
"The Size of the LGBT Population and the Magnitude of Antigay Sentiment Are Substantially Underestimated,"
Management Science, INFORMS, vol. 63(10), pages 3168-3186, October.
- Katherine B. Coffman & Lucas C. Coffman & Keith M. Marzilli Ericson, 2013. "The Size of the LGBT Population and the Magnitude of Anti-Gay Sentiment are Substantially Underestimated," NBER Working Papers 19508, National Bureau of Economic Research, Inc.
- Ori Heffetz & Katrina Ligett, 2014.
"Privacy and Data-Based Research,"
Journal of Economic Perspectives, American Economic Association, vol. 28(2), pages 75-98, Spring.
- Ori Heffetz & Katrina Ligett, 2013. "Privacy and Data-Based Research," NBER Working Papers 19433, National Bureau of Economic Research, Inc.
- Toth Daniell, 2014. "Data Smearing: An Approach to Disclosure Limitation for Tabular Data," Journal of Official Statistics, Sciendo, vol. 30(4), pages 839-857, December.
- Soumya Mukherjee & Aratrika Mustafi & Aleksandra Slavkovi'c & Lars Vilhuber, 2023. "Assessing Utility of Differential Privacy for RCTs," Papers 2309.14581, arXiv.org.
- Jing Lei & Anne‐Sophie Charest & Aleksandra Slavkovic & Adam Smith & Stephen Fienberg, 2018. "Differentially private model selection with penalized and constrained likelihood," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 181(3), pages 609-633, June.
- Ryan Cumings-Menon, 2022. "Differentially Private Estimation via Statistical Depth," Papers 2207.12602, arXiv.org.
- Chongliang Luo & Md. Nazmul Islam & Natalie E. Sheils & John Buresh & Jenna Reps & Martijn J. Schuemie & Patrick B. Ryan & Mackenzie Edmondson & Rui Duan & Jiayi Tong & Arielle Marks-Anglin & Jiang Bi, 2022. "DLMM as a lossless one-shot algorithm for collaborative multi-site distributed linear mixed models," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
- Vishesh Karwa & Pavel N. Krivitsky & Aleksandra B. Slavković, 2017. "Sharing social network data: differentially private estimation of exponential family random-graph models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 66(3), pages 481-500, April.
- Jinshuo Dong & Aaron Roth & Weijie J. Su, 2022. "Authors’ reply to the Discussion of ‘Gaussian Differential Privacy’ by Dong et al," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(1), pages 50-54, February.
- Harrison Quick, 2021. "Generating Poisson‐distributed differentially private synthetic data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 184(3), pages 1093-1108, July.
- Lalanne, Clément & Gadat, Sébastien, 2024. "Privately Learning Smooth Distributions on the Hypercube by Projections," TSE Working Papers 24-1505, Toulouse School of Economics (TSE).
- Soumya Mukherjee & Aratrika Mustafi & Aleksandra Slavkovic & Lars Vilhuber, 2024. "Improving Privacy for Respondents in Randomized Controlled Trials: A Differential Privacy Approach," NBER Chapters, in: Data Privacy Protection and the Conduct of Applied Research: Methods, Approaches and their Consequences, National Bureau of Economic Research, Inc.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:jorssb:v:84:y:2022:i:1:p:3-37. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/rssssea.html .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.