A theory of utility and privacy of data sources

Lalitha Sankar; S. Raj Rajagopalan; H. Vincent Poor

doi:10.1109/ISIT.2010.5513684

A theory of utility and privacy of data sources

Lalitha Sankar, S. Raj Rajagopalan, H. Vincent Poor

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

28 Scopus citations

Abstract

The problem of frequent private information "leakage" from the myriad large centralized searchable data repositories in use today drives the need for an analytical framework that quantifies unequivocally how safe private data can be (privacy) while still providing measurable benefit (utility) to multiple legitimate information consumers. Rate distortion theory is shown to be a natural choice to develop such a framework which includes modeling of data sources, developing application independent utility and privacy metrics, quantifying utility-privacy tradeoffs irrespective of the type of data sources or the methods of providing privacy, and developing a side-information model for dealing with questions of external knowledge.

Original language	English (US)
Title of host publication	2010 IEEE International Symposium on Information Theory, ISIT 2010 - Proceedings
Pages	2642-2646
Number of pages	5
DOIs	https://doi.org/10.1109/ISIT.2010.5513684
State	Published - Aug 23 2010
Event	2010 IEEE International Symposium on Information Theory, ISIT 2010 - Austin, TX, United States Duration: Jun 13 2010 → Jun 18 2010

Other

Other	2010 IEEE International Symposium on Information Theory, ISIT 2010
Country/Territory	United States
City	Austin, TX
Period	6/13/10 → 6/18/10

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
Information Systems
Modeling and Simulation
Applied Mathematics

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10.1109/ISIT.2010.5513684

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title = "A theory of utility and privacy of data sources",

abstract = "The problem of frequent private information {"}leakage{"} from the myriad large centralized searchable data repositories in use today drives the need for an analytical framework that quantifies unequivocally how safe private data can be (privacy) while still providing measurable benefit (utility) to multiple legitimate information consumers. Rate distortion theory is shown to be a natural choice to develop such a framework which includes modeling of data sources, developing application independent utility and privacy metrics, quantifying utility-privacy tradeoffs irrespective of the type of data sources or the methods of providing privacy, and developing a side-information model for dealing with questions of external knowledge.",

author = "Lalitha Sankar and Rajagopalan, {S. Raj} and Poor, {H. Vincent}",

year = "2010",

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day = "23",

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language = "English (US)",

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N2 - The problem of frequent private information "leakage" from the myriad large centralized searchable data repositories in use today drives the need for an analytical framework that quantifies unequivocally how safe private data can be (privacy) while still providing measurable benefit (utility) to multiple legitimate information consumers. Rate distortion theory is shown to be a natural choice to develop such a framework which includes modeling of data sources, developing application independent utility and privacy metrics, quantifying utility-privacy tradeoffs irrespective of the type of data sources or the methods of providing privacy, and developing a side-information model for dealing with questions of external knowledge.

AB - The problem of frequent private information "leakage" from the myriad large centralized searchable data repositories in use today drives the need for an analytical framework that quantifies unequivocally how safe private data can be (privacy) while still providing measurable benefit (utility) to multiple legitimate information consumers. Rate distortion theory is shown to be a natural choice to develop such a framework which includes modeling of data sources, developing application independent utility and privacy metrics, quantifying utility-privacy tradeoffs irrespective of the type of data sources or the methods of providing privacy, and developing a side-information model for dealing with questions of external knowledge.

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BT - 2010 IEEE International Symposium on Information Theory, ISIT 2010 - Proceedings

T2 - 2010 IEEE International Symposium on Information Theory, ISIT 2010

Y2 - 13 June 2010 through 18 June 2010

ER -

A theory of utility and privacy of data sources

Abstract

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All Science Journal Classification (ASJC) codes

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