Private data warehouse queries

Publisher:
ACM
Publication Type:
Conference Proceeding
Citation:
Proceedings of the 18th ACM Symposium on Access Control Models and Technologies, 2013, pp. 25 - 36 (12)
Issue Date:
2013-01
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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.
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