Learning to Live with Privacy-Preserving Analytics-Reference-Cited by-同舟云学术

Learning to Live with Privacy-Preserving Analytics

Published:2023-06-22 Issue:7 Volume:66 Page:24-27
ISSN:0001-0782
Container-title:Communications of the ACM
language:en
Short-container-title:Commun. ACM

Author:

Acquisti Alessandro¹,Steed Ryan¹

Affiliation:

1. Carnegie Mellon University, Pittsburgh, PA, USA

Abstract

Seeking to close the gap between research and real-world applications of PPAs.

Publisher

Association for Computing Machinery (ACM)

Subject

General Computer Science

Link

https://dl.acm.org/doi/pdf/10.1145/3597173

Reference15 articles.

1. An Economic Analysis of Privacy Protection and Statistical Accuracy as Social Choices

2. Agarwal A. and Singh R. Causal Inference with Corrupted Data: Measurement Error Missing Values Discretization and Differential Privacy. (2022); https://bit.ly/3I2wi9j. Agarwal A. and Singh R. Causal Inference with Corrupted Data: Measurement Error Missing Values Discretization and Differential Privacy. (2022); https://bit.ly/3I2wi9j.

3. Bouk , D. and boyd , d. Democracy's Data Infrastructure . Knight First Amendment Institute . https://bit.ly/3pwPANM. Bouk, D. and boyd, d. Democracy's Data Infrastructure. Knight First Amendment Institute. https://bit.ly/3pwPANM.

4. Buntain C. Measuring the Ideology of Audiences for Web Links and Domains Using Differentially Private Engagement Data. (2021); https://bit.ly/41oCyzj Buntain C. Measuring the Ideology of Audiences for Web Links and Domains Using Differentially Private Engagement Data. (2021); https://bit.ly/41oCyzj

5. Cyphers , B. Google's FLoC Is a Terrible Idea . Electronic Frontier Foundation . ( Oct. 2021 ); https://bit.ly/42LiWX9. Cyphers, B. Google's FLoC Is a Terrible Idea. Electronic Frontier Foundation. (Oct. 2021); https://bit.ly/42LiWX9.

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