6 papers
Publishing Wikipedia usage data with strong privacy guarantees
Temilola Adeleye, Skye Berghel, Damien Desfontaines +9
For almost 20 years, the Wikimedia Foundation has been publishing statistics about how many people visited each Wikipedia page on each day. This data helps Wikipedia editors determ…
SafeTab-H: Disclosure Avoidance for the 2020 Census Detailed Demographic and Housing Characteristics File B (Detailed DHC-B)
William Sexton, Skye Berghel, Bayard Carlson +10
This article describes SafeTab-H, a disclosure avoidance algorithm applied to the release of the U.S. Census Bureau's Detailed Demographic and Housing Characteristics File B (Detai…
SafeTab-P: Disclosure Avoidance for the 2020 Census Detailed Demographic and Housing Characteristics File A (Detailed DHC-A)
Sam Haney, Skye Berghel, Bayard Carlson +11
This article describes the disclosure avoidance algorithm that the U.S. Census Bureau used to protect the Detailed Demographic and Housing Characteristics File A (Detailed DHC-A) o…
PHSafe: Disclosure Avoidance for the 2020 Census Supplemental Demographic and Housing Characteristics File (S-DHC)
William Sexton, Skye Berghel, Bayard Carlson +10
This article describes the disclosure avoidance algorithm that the U.S. Census Bureau used to protect the 2020 Census Supplemental Demographic and Housing Characteristics File (S-D…
Slowly Scaling Per-Record Differential Privacy
Brian Finley, Anthony M Caruso, Justin C Doty +5
We develop formal privacy mechanisms for releasing statistics from data with many outlying values, such as income data. These mechanisms ensure that a per-record differential priva…
Privately Answering Queries on Skewed Data via Per Record Differential Privacy
Jeremy Seeman, William Sexton, David Pujol +1
We consider the problem of the private release of statistics (like aggregate payrolls) where it is critical to preserve the contribution made by a small number of outlying large en…