Split Leverage: Attacking the Condentiality of Linked Databases by Partitioning

Rai, T; Hall, JL

Split Leverage: Attacking the Condentiality of Linked Databases by Partitioning

Rai, T

Hall, JL

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Publisher:: Australian Mathematical Society
Publication Type:: Journal Article
Citation:: ANZIAM, 2014
Issue Date:: 2014-01

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Field	Value	Language
dc.contributor.author	Rai, T https://orcid.org/0000-0003-1610-8983	en_US
dc.contributor.author	Hall, JL	en_US
dc.date.issued	2014-01	en_US
dc.identifier.citation	ANZIAM, 2014	en_US
dc.identifier.issn	1446-8735	en_US
dc.identifier.uri	http://hdl.handle.net/10453/30288
dc.description.abstract	This paper considers the risk of disclosure in linked databases when statistical analysis of micro-data is permitted. The risk of dis- closure needs to be balanced against the utility of the linked data. The current work specifically considers the disclosure risks in permit- ting regression analysis to be performed on linked data. A new attack based on partitioning of the database is presented.	en_US
dc.publisher	Australian Mathematical Society	en_US
dc.relation.ispartof	ANZIAM	en_US
dc.subject.classification	General Mathematics	en_US
dc.subject.classification	Numerical & Computational Mathematics	en_US
dc.title	Split Leverage: Attacking the Condentiality of Linked Databases by Partitioning	en_US
dc.type	Journal Article
utslib.for	0104 Statistics	en_US
utslib.for	01 Mathematical Sciences	en_US
utslib.for	09 Engineering	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/DVC (Research)
pubs.organisational-group	/University of Technology Sydney/DVC (Research)/Graduate Research School
utslib.copyright.status	open_access
pubs.consider-herdc	true	en_US

Abstract:

This paper considers the risk of disclosure in linked databases when statistical analysis of micro-data is permitted. The risk of dis- closure needs to be balanced against the utility of the linked data. The current work specifically considers the disclosure risks in permit- ting regression analysis to be performed on linked data. A new attack based on partitioning of the database is presented.

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http://hdl.handle.net/10453/30288