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Privacy integrated queries: an extensible platform for privacy-preserving data analysis
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International Conference on Management of Data archive
Proceedings of the 35th SIGMOD international conference on Management of data table of contents
Providence, Rhode Island, USA
SESSION: Research session 1: security I table of contents
Pages 19-30  
Year of Publication: 2009
ISBN:978-1-60558-551-2
Author
Frank D. McSherry  Microsoft Research, Mountain View, CA, USA
Sponsors
ACM: Association for Computing Machinery
SIGMOD: ACM Special Interest Group on Management of Data
Publisher
ACM  New York, NY, USA
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ABSTRACT

We report on the design and implementation of the Privacy Integrated Queries (PINQ) platform for privacy-preserving data analysis. PINQ provides analysts with a programming interface to unscrubbed data through a SQL-like language. At the same time, the design of PINQ's analysis language and its careful implementation provide formal guarantees of differential privacy for any and all uses of the platform. PINQ's unconditional structural guarantees require no trust placed in the expertise or diligence of the analysts, substantially broadening the scope for design and deployment of privacy-preserving data analysis, especially by non-experts.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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F. McSherry and K. Talwar, "Synthetic data via differential privacy," Manuscript.