Private data warehouse queries

Yi, X; Paulet, R; Bertino, E; Xu, G

Private data warehouse queries

Yi, X Paulet, R Bertino, E Xu, G

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Publication Type:: Conference Proceeding
Citation:: Proceedings of ACM Symposium on Access Control Models and Technologies, SACMAT, 2013, pp. 25 - 35
Issue Date:: 2013-09-02

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Field	Value	Language
dc.contributor.author	Yi, X	en_US
dc.contributor.author	Paulet, R	en_US
dc.contributor.author	Bertino, E	en_US
dc.contributor.author	Xu, G https://orcid.org/0000-0003-4493-6663	en_US
dc.date.issued	2013-09-02	en_US
dc.identifier.citation	Proceedings of ACM Symposium on Access Control Models and Technologies, SACMAT, 2013, pp. 25 - 35	en_US
dc.identifier.isbn	9781450319508	en_US
dc.identifier.uri	http://hdl.handle.net/10453/33781
dc.identifier.uri	http://hdl.handle.net/10453/28337
dc.description.abstract	Publicly accessible data warehouses are an indispensable resource for data analysis. But they also pose a significant risk to the privacy of the clients, since a data warehouse operator may follow the client's queries and infer what the client is interested in. Private Information Retrieval (PIR) techniques allow the client to retrieve a cell from a data warehouse without revealing to the operator which cell is retrieved. However, PIR cannot be used to hide OLAP operations performed by the client, which may disclose the client's interest. This paper presents a solution for private data warehouse queries on the basis of the Boneh-Goh-Nissim cryptosystem which allows one to evaluate any multi-variate polynomial of total degree 2 on ciphertexts. By our solution, the client can perform OLAP operations on the data warehouse and retrieve one (or more) cell without revealing any information about which cell is selected. Furthermore, our solution supports some types of statistical analysis on data warehouse, such as regression and variance analysis, without revealing the client's interest. Our solution ensures both the server's security and the client's security. Copyright 2013 ACM.	en_US
dc.relation.ispartof	Proceedings of ACM Symposium on Access Control Models and Technologies, SACMAT	en_US
dc.relation.isbasedon	10.1145/2462410.2462418	en_US
dc.title	Private data warehouse queries	en_US
dc.type	Conference Proceeding
utslib.for	0806 Information Systems	en_US
dc.location.activity	Amsterdam	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Strength - AAI - Advanced Analytics Institute Research Centre
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

Publicly accessible data warehouses are an indispensable resource for data analysis. But they also pose a significant risk to the privacy of the clients, since a data warehouse operator may follow the client's queries and infer what the client is interested in. Private Information Retrieval (PIR) techniques allow the client to retrieve a cell from a data warehouse without revealing to the operator which cell is retrieved. However, PIR cannot be used to hide OLAP operations performed by the client, which may disclose the client's interest. This paper presents a solution for private data warehouse queries on the basis of the Boneh-Goh-Nissim cryptosystem which allows one to evaluate any multi-variate polynomial of total degree 2 on ciphertexts. By our solution, the client can perform OLAP operations on the data warehouse and retrieve one (or more) cell without revealing any information about which cell is selected. Furthermore, our solution supports some types of statistical analysis on data warehouse, such as regression and variance analysis, without revealing the client's interest. Our solution ensures both the server's security and the client's security. Copyright 2013 ACM.

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http://hdl.handle.net/10453/28337