DPSyn: Experiences in the NIST Differential Privacy Data Synthesis Challenges
Main Article Content
Abstract
We summarize the experience of participating in two differential privacycompetitions organized by the National Institute of Standards and Technology (NIST). Inthis paper, we document our experiences in the competition, the approaches we have used,the lessons we have learned, and our call to the research community to further bridge thegap between theory and practice in DP research.
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Copyright is retained by the authors. By submitting to this journal, the author(s) license the article under the Creative Commons License – Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0), unless choosing a more lenient license (for instance, public domain). For situations not allowed under CC BY-NC-ND, short sections of text, not to exceed two paragraphs, may be quoted without explicit permission provided that full credit, including © notice, is given to the source.
Authors of articles published by the journal grant the journal the right to store the articles in its databases for an unlimited period of time and to distribute and reproduce the articles electronically.
Funding data
-
Helmholtz Association
Grant numbers ZT-I-OO1 4 -
National Science Foundation
Grant numbers 1931443 -
National Natural Science Foundation of China
Grant numbers 61731004;U1911401