We have developed this blog series leveraging the differential privacy contributions in the de-identification tools section. This series is designed to help business process owners and privacy program personnel understand basic concepts about differential privacy and applicable use cases and to help privacy engineers and IT professionals implement the tools. Our longer term goal is to transform this series into more in-depth guidelines on differential privacy. We encourage readers to ask questions and share knowledge using the contribute section to better inform the development of these guidelines. We also can be contacted at collabspace [at] nist.gov.
Differential Privacy for Privacy-preserving Data Analysis: An Introduction to our Blog Series | July 27, 2020 | by Joseph Near, David Darais, and Katie Boeckl
Threat Models for Differential Privacy | September 15, 2020 | by Joseph Near and David Darais
Counting Queries: Extracting Key Business Metrics from Datasets | October 14, 2020 | by Joseph Near and David Darais
Summation and Average Queries: Detecting Trends in Your Data | December 17, 2020 | by Joseph Near and David Darais
Workloads of Counting Queries: Enabling Rich Statistical Analyses with Differential Privacy | February 9, 2021 | by Ryan McKenna
Differential Privacy for Complex Data: Answering Queries Across Multiple Data Tables | March 25, 2021 | by Xi He
Differentially Private Synthetic Data | May 3, 2021 | by Joseph Near and David Darais
Differential Privacy Bugs and Why They're Hard to Find | May 25, 2021 | by Joseph Near and David DaraisSee Post #8
Testing for Differential Privacy Bugs | June 22, 2021 | by Dan Kifer
Automatic Proofs of Differential Privacy | July 22, 2021 | by Chike Abuah
Stay tuned: more blog posts coming soon!