Vol. 11 No. 3 (2021): Regular issue, including articles based on presentations at TPDP 2020

Regular issue, includes additional articles based on presentations at TPDP 2020 - Theory and Practice of Differential Privacy.

Managing Editor: Lars Vilhuber

Guest Editor (TPDP 2020 content): Rachel Cummings

DOI: https://doi.org/10.29012/jpc.v11i3

Published: 2021-12-24

Differentially Private Set Union

Sivakanth Gopi, Pankaj Gulhane, Janardhan Kulkarni, Judy Hanwen Shen, Milad Shokouhi, Sergey Yekhanin

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LinkedIn's Audience Engagements API
A Privacy Preserving Data Analytics System at Scale

Ryan Rogers, Subbu Subramaniam, Sean Peng, David Durfee, Seunghyun Lee, Santosh Kumar Kancha, Shraddha Sahay, Parvez Ahammad

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Winning the NIST Contest: A scalable and general approach to differentially private synthetic data

Ryan McKenna, Gerome Miklau, Daniel Sheldon

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Synthetic Data Generation with Differential Privacy via Bayesian Networks

Ergute Bao, Xiaokui Xiao, Jun Zhao, Dongping Zhang, Bolin Ding

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The Journal of Privacy and Confidentiality is an open-access multi-disciplinary journal whose purpose is to facilitate the coalescence of research methodologies and activities in the areas of privacy, confidentiality, and disclosure limitation. The JPC seeks to publish a wide range of research and review papers, not only from academia, but also from government (especially official statistical agencies) and industry, and to serve as a forum for exchange of views, discussion, and news. For more information, see the About the Journal page.

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TPDP 2020

Differentially Private Set Union

LinkedIn's Audience Engagements API A Privacy Preserving Data Analytics System at Scale

Privacy Challenges

Winning the NIST Contest: A scalable and general approach to differentially private synthetic data

Synthetic Data Generation with Differential Privacy via Bayesian Networks

LinkedIn's Audience Engagements API
A Privacy Preserving Data Analytics System at Scale