Privacy Integrated Queries (PINQ) is an extensible data analysis platform designed to provide unconditional privacy guarantees for the records of the underlying data sets. PINQ provides analysts with access to records through an SQL-like declarative language (LINQ) amidst otherwise arbitrary C-Sharp code. 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 guarantees require no trust placed in the expertise or diligence of the analysts, broadening the scope for design and deployment of privacy-preserving data analyses, especially by privacy nonexperts.
%0 Journal Article
%1 McSherry10cacm
%A McSherry, Frank
%D 2010
%J Communications of the ACM
%K 01841 acm paper database secure user data analysis
%N 9
%P 89--97
%R 10.1145/1810891.1810916
%T Privacy Integrated Queries: An Extensible Platform for Privacy-Preserving Data Analysis
%V 53
%X Privacy Integrated Queries (PINQ) is an extensible data analysis platform designed to provide unconditional privacy guarantees for the records of the underlying data sets. PINQ provides analysts with access to records through an SQL-like declarative language (LINQ) amidst otherwise arbitrary C-Sharp code. 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 guarantees require no trust placed in the expertise or diligence of the analysts, broadening the scope for design and deployment of privacy-preserving data analyses, especially by privacy nonexperts.
@article{McSherry10cacm,
abstract = {Privacy Integrated Queries (PINQ) is an extensible data analysis platform designed to provide unconditional privacy guarantees for the records of the underlying data sets. PINQ provides analysts with access to records through an SQL-like declarative language (LINQ) amidst otherwise arbitrary C-Sharp code. 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 guarantees require no trust placed in the expertise or diligence of the analysts, broadening the scope for design and deployment of privacy-preserving data analyses, especially by privacy nonexperts.},
added-at = {2012-05-30T10:50:47.000+0200},
author = {McSherry, Frank},
biburl = {https://www.bibsonomy.org/bibtex/2e07c8c8a3c8fd5c4aaae206366d995ca/flint63},
doi = {10.1145/1810891.1810916},
file = {ACM Digital Library:2010/McSherry10cacm.pdf:PDF},
groups = {public},
interhash = {e540d86e2866d781bf5b664c5c557241},
intrahash = {e07c8c8a3c8fd5c4aaae206366d995ca},
issn = {0001-0782},
journal = {Communications of the ACM},
keywords = {01841 acm paper database secure user data analysis},
number = 9,
pages = {89--97},
timestamp = {2018-04-16T12:09:24.000+0200},
title = {Privacy Integrated Queries: An Extensible Platform for Privacy-Preserving Data Analysis},
username = {flint63},
volume = 53,
year = 2010
}