Webinars

Past Webinars

Title: New Developments in Synthetic Data Generation
Presenters: Brett Beaulieu-Jones, Harvard Medical School, Jingchen (Monika) Hu, Vassar College; Aaron R. Williams, Urban Institute
Date and Time: Friday, January 28, 2022, 12:00-1:00 p.m. EST
Sponsor: ASA Committee on Privacy and Confidentiality for International Data Privacy Day
Webinar slides and link to recording


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Title: Privacy Risk and Preservation for COVID-19 Contact Tracing and Information Sharing
Presenter: Fang Liu, University of Notre Dame
Date and Time: Friday, January 29, 2021, 1:00-2:00 p.m. EST
Sponsor: ASA Committee on Privacy and Confidentiality for International Data Privacy Day
Webinar slides and link to recording


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Title: A Practitioner’s Intro to Differential Privacy

Presenter: Matthew Graham, Center for Economic Studies, U.S. Census Bureau
Date and Time: Thursday, March 12, 2020, 1:00 p.m - 2:00pm EST 
Sponsor: ASA Government and Statistics Section

Webinar slides

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Title: Differential Privacy and the 2020 Census: Modernizing Disclosure Avoidance at Scale to Mitigate Growing Privacy Threats
Presenters: Michael Hawes, U.S. Census Bureau

Moderator: Joshua Snoke, RAND Corporation
Date and Time: Tuesday, January 28, 2020, 12:00-1:00 p.m. EST
Sponsor: ASA Committee on Privacy and Confidentiality for International Data Privacy Day
Webinar slides and link to recording


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Title: Toward Protecting the Privacy of Individuals When Disseminating Data: Challenges in Disclosure Risk Assessment
Presenters: Tom Krenzke, Westat, and Jianzhu Li, Westat

Moderator: Aleksandra Slavkovic, Pennsylvania State University
Date and Time: Wednesday, February 6, 2019, 12:00-1:30 p.m. EST
Sponsor: ASA Committee on Privacy and Confidentiality for International Data Privacy Day

Description:
We discuss the theory and background of useful approaches for determining the level of data disclosure risk prior to disseminating data. We focus on challenges experienced from several case studies and provide insights into the ways that the risks can be estimated. These challenges relate to risk estimate diagnostics and sensitivity analysis, longitudinal risk, when public use data already exists, variable selection, setting risk thresholds, impact of weights and missing values, query tools, geography, attribute disclosure, risk of synthetic data, and external data. Some discussion of differential privacy is provided in this context. Once the key elements that trigger the relatively high risks are understood, data protection approaches can be determined and processed while balancing the risk reduction with retention of data utility.


Tom Krenzke, senior statistician and Associate Director in the Westat statistical group. He has led research on data disclosure limitation methods working toward solutions for several Federal agencies and Disclosure Review Boards. Mr. Krenzke is an ASA Fellow and President of the Washington Statistical Society, and serves on the ASA Privacy and Confidentiality Committee and Westat Institutional Review Board.

Jianzhu Li, senior statistician at Westat. Dr. Li has 16 years of experience in survey research, including sample design, nonresponse adjustment, imputation, data confidentiality and disclosure protection, and small area estimation. She has worked on several statistical confidentiality projects over the past few years for Government agencies such as NSF, NCHS, NCES, Census Bureau, and USDA.

Webinar slides and link to recording

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Title: What is a Privacy-Loss Budget and How Is It used to Design Privacy Protection for a Confidential Database?
Presenter: John M. Abowd, Chief Scientist and Associate Director for Research and Methodology, U.S. Census Bureau
Moderator: Lars Vilhuber, Cornell University
Date and Time: Thursday, February 1, 2018, 12:30-1:30 p.m. EST
Sponsor: ASA Committee on Privacy and Confidentiality for International Data Privacy Day

Twitter Hashtag: #ASAwebinar

Description:
For statistical agencies, the Big Bang event in disclosure avoidance occurred in 2003 when Irit Dinur and Kobbi Nissim, two well-known cryptographers, turned their attention to properties of safe systems for data publication from confidential sources. And the paradigm-shifting message was a very strong result showing that most of the confidentiality protection systems used by statistical agencies around the world, collectively known as statistical disclosure limitation, were not designed to defend against a database reconstruction attack. Such an attack recreates increasingly accurate record-level images of the confidential data as an agency publishes more and more accurate statistics from the same database. Why are we still talking about this theorem fifteen years later? What is required to modernize our disclosure limitation systems? The answer is recognizing that the database reconstruction theorem identified a real constraint on agency publication systems—there is only a finite amount of information in any confidential database. We can’t repeal that constraint. But it doesn’t help with the public-good mission of statistical agencies to publish data that are suitable for their intended uses. The hard work is incorporating the required privacy-loss budget constraint into the decision-making processes of statistical agencies. This means balancing the interests of data accuracy and privacy loss. A leading example of this process is the need for accurate redistricting data, to enforce the Voting Rights Act, and the protection of sensitive racial and ethnic information in the detailed data required for this activity. Wrestling with this tradeoff stares-down the database reconstruction theorem, and uses the formal privacy results that it inspired to specify the technologies. Specifying the decision framework for selecting a point on that technology has proven much more challenging. We still have a lot of work to do.

Dr Abowd leads a directorate of research centers at the Census Bureau, each devoted to domains of investigation important to the future of social and economic statistics. During the past two years he has led critical work to modernize the Census Bureau’s operations and products.

Webinar slides and link to recording


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Title: Differential Privacy: Protecting Individuals from Re-Identification

Presenters: Daniel Kifer, Pennsylvania State University, Vishesh Karwa, Harvard University

Moderator: Aleksandra Slavkovic, Pennsylvania State University

Date and Time: Friday, February 10, 2017, 1:00 p.m. – 2:00 p.m. Eastern time

Sponsor: ASA Committee on Privacy and Confidentiality for International Data Privacy Day

Description:

Differential privacy is a mathematical framework for protecting privacy interests in statistical databases by focusing on the disclosure risk to an individual being included in a data set. In this webinar, two research experts explain this methodology and how they apply differential privacy methodology as a data protection method for protecting data files from the risk of re-identification. A key benefit of the Differential Privacy methodology is that in many cases, appropriate privacy protection can be achieved if random noise is properly added to the actual results. For example, rather than simply reporting the sum, the data provider can inject noise based on a distribution. The calculation of “how much” noise to inject can be made based only on knowledge of the function to be computed. This webinar will cover the basic principles of differential privacy, how it works, and how it can successfully be applied to current statistical databases.

Webinar slides and link to recording 

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Title: The New European Union General Data Protection Regulation: Implications for Data Privacy and Research Activities for the United States

Presenters: Stefan Bender, Head of Research Data and Service Center, Deutsche Bundesbank, Vice-Chair of the German Data Forum and Edward Bartlett, International Human Research Liaison, Office for Human Research Protections, US Department of Health and Human Services

Date and Time: Thursday, January 28, 2016, 12:00 p.m. – 1:00 p.m. Eastern time

Sponsor: ASA Privacy and Confidentiality Committee

Description: This webinar provides attendees with insights into the new Data Protection Regulation adopted by the European Union (EU) and the policy and regulatory issues facing researchers in the United States.  The first part of the presentation will focus on what the new protections are that affect the collection and processing of personal data, and the policy drivers that led to the need to revise the existing privacy directive.  The second part of the presentation will focus on the policy and regulatory issues facing researchers in the United States.

Webinar slides

 
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Title: Producing Government Data with Statistical Confidentiality Controls

Presenters: Tom Krenzke, Westat Statistical Group, and Ed Christopher, Federal Highway Administration

Date and Time: Wednesday, December 17, 2014, 12:00 p.m. - 1:00 p.m. Eastern time 

Sponsor: ASA Committee on Privacy and Confidentiality

Description:
Plans to disseminate data to the public include statistical and confidentiality controls. Learn about statistical disclosure control (SDC) methods that have been used effectively in government data production processes. From data collection to data delivery and post-delivery trainings on data usage, this webinar will review statistical methods that are used in government data production processes to ensure the integrity of the released data while maintaining data subjects’ confidentiality. Participants will gain insights on various SDC approaches that also achieve feasible implementation. The discussion will conclude with an example from a special tabulation generated from the American Community Survey for the transportation community of over 400 transportation planning agencies across the US. The discussion illustrates a confidentiality protection perturbation technique that satisfied the Census Bureau’s Disclosure Review Board and data production staff, while at the same time provided the transportation planners with data they could use. In this webinar, statistical disclosure methods will be discussed along with the views of the user community.

Webinar slides and supporting document