Joining Privately on Outsourced Data

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Joining Privately on Outsourced Data
In an outsourced database framework, clients place data management with specialized service providers. Of essential concern in such frameworks is data privacy. Potential clients are reluctant to outsource sensitive data to a foreign party without strong privacy assurances beyond policy “fine–prints”. In this paper we introduce a mechanism for executing general binary JOIN operations (for predicates that satisfy certain properties) in an outsourced relational database framework with full computational privacy and low overheads – a first, to the best of our knowledge. We illustrate via a set of relevant instances of JOIN predicates, including: range and equality (e.g., for geographical data), Hamming distance (e.g., for DNA matching) and semantics (i.e., in health-care scenarios – mapping antibiotics to bacteria). We experimentally evaluate the main overhead components and show they are reasonable. For example, the initial client computation overhead for 100000 data items is ...
Bogdan Carbunar, Radu Sion
Added 30 Jan 2011
Updated 30 Jan 2011
Type Journal
Year 2010
Where SDMW
Authors Bogdan Carbunar, Radu Sion
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