Privacy-safe Measurement on the Web: Open Questions From the Privacy Sandbox

APA

(2022). Privacy-safe Measurement on the Web: Open Questions From the Privacy Sandbox. The Simons Institute for the Theory of Computing. https://old.simons.berkeley.edu/talks/privacy-safe-measurement-web-open-questions-privacy-sandbox

MLA

Privacy-safe Measurement on the Web: Open Questions From the Privacy Sandbox. The Simons Institute for the Theory of Computing, Nov. 07, 2022, https://old.simons.berkeley.edu/talks/privacy-safe-measurement-web-open-questions-privacy-sandbox

BibTex

          @misc{ scivideos_22919,
            doi = {},
            url = {https://old.simons.berkeley.edu/talks/privacy-safe-measurement-web-open-questions-privacy-sandbox},
            author = {},
            keywords = {},
            language = {en},
            title = {Privacy-safe Measurement on the Web: Open Questions From the Privacy Sandbox},
            publisher = {The Simons Institute for the Theory of Computing},
            year = {2022},
            month = {nov},
            note = {22919 see, \url{https://scivideos.org/simons-institute/22919}}
          }
          
Christina Ilvento (Google)
Source Repository Simons Institute

Abstract

The Privacy Sandbox aims "to create technologies that both protect people's privacy online and give companies and developers tools to build thriving digital businesses." This talk will describe some of the design, implementation and practical challenges in evolving measurement solutions away from persistent cross-site identifiers.