Webinar Today (5/4): Differential Privacy 101

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Webinar Today (5/4): Differential Privacy 101


May 4​         

Differential Privacy 101                                                                        

This introductory webinar will explain the Census Bureau’s decision to modernize the methods we use to protect respondent confidentiality in the data we release. We will cover the basic principles and concepts of disclosure avoidance and differential privacy and discuss their implications for census data users. 

Time: 1:00 – 2:00 pm (ET)

WebEx log-in:

https://uscensus.webex.com/uscensus/onstage/g.php?MTID=e044ae9d40aab83c7bc4de8520ae64f1a

WebEx event number (If needed):  199 215 4098

WebEx event password (If needed):  @Census1

Audio: Listen to the webinar in one of two ways:

Using your computer's speakers (choose "Audio Broadcast," which is 1-way audio) -OR- Using your TELEPHONE (call 1-888-566-6168 OR 1-212-287-1827 code: 6655851)

This event will be recorded and archived (with slides) on the 2020 Census Disclosure Avoidance Modernization website.


Full Disclosure Avoidance Webinar Series - Upcoming:


See Census Academy for the full Disclosure Avoidance series

May 7​             

The Census Bureau's Simulated Reconstruction-Abetted Re-identification Attack on the 2010 Census ​ 

This webinar will examine the simulated re-identification attack that the Census Bureau performed on the published 2010 Census data and its implications for the 2020 Census. 

Time: 1:00 – 2:00 pm (ET)

WebEx log-in: https://uscensus.webex.com/uscensus/onstage/g.php?MTID=e165d99e4102c0ae5965c76698eff97f9

WebEx event number (If needed):  199 640 0790

WebEx event password (If needed):  #Censusdata1

Audio: Listen to the webinar in one of two ways:

Using your computer's speakers (choose "Audio Broadcast," which is 1-way audio) -OR- Using your TELEPHONE (call 1-888-957-9861, 4695440 #)

This event will be recorded and archived (with slides) on the 2020 Census Disclosure Avoidance Modernization website.


May 13​           

Differential Privacy 201 and the TopDown Algorithm ​                                   

This webinar will provide a deeper examination of how the Census Bureau is using the framework of differential privacy to safeguard respondent data for the 2020 Census. We will examine how the 2020 Census Disclosure Avoidance System’s TopDown Algorithm works and the parameters and settings used to produce the April 2021 demonstration data. 

*   Log-in information coming soon


May 14​           

Highlights of the April 2021 Detailed Summary Metrics ​                               

This webinar will examine how the Census Bureau uses a variety of accuracy measures to evaluate the data produced by the Disclosure Avoidance System’s TopDown Algorithm. We will explain how we developed these accuracy measures and how data users can use them to evaluate the April 2021 demonstration data. 

*   Log-in information coming soon


May 21​           

Analysis of April 2021 Demonstration Data for Redistricting and Voting Rights Act​ Use Cases              

This webinar will examine the results of the Census Bureau’s empirical evaluation of the reliability and fitness-for-use of the April 2021 demonstration data for redistricting and enforcement of the Voting Rights Act. 

*   Log-in information coming soon


PAST WEBINARS


Apr. 30

Understanding the April 2021 Demonstration Data

The webinar covered in detail the updates reflected in the new demonstration data, walked through the associated metrics, and provided an opportunity for Q&A. 

 

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Do you have specific questions you'd like us to answer in this newsletter or topics you'd like discussed? Send us an email at 2020DAS@census.gov and let us know!

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About Disclosure Avoidance Modernization

The Census Bureau is protecting 2020 Census data products with a powerful new cryptography-based disclosure avoidance system known as “differential privacy.”  We are committed to producing 2020 Census data products that are of the same high quality you've come to expect while protecting respondent confidentiality from emerging privacy threats in today's digital world. 

 

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