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Joining privately on outsourced data
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Carbunar, B, Sion, R. (2010). Joining privately on outsourced data .
EURO-PAR 2011 PARALLEL PROCESSING, PT 1,
6358 LNCS 70-86. 10.1007/978-3-642-15546-8_6
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Carbunar, B, Sion, R. (2010). Joining privately on outsourced data .
EURO-PAR 2011 PARALLEL PROCESSING, PT 1,
6358 LNCS 70-86. 10.1007/978-3-642-15546-8_6
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cited authors
Carbunar, B; Sion, R
authors
Carbunar, Bogdan O.P.
abstract
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 around 5 minutes. Moreover, our privacy mechanisms can sustain theoretical throughputs of over 30 million predicate evaluations per second, even for an un-optimized OpenSSL based implementation. © 2010 Springer-Verlag.
publication date
January 1, 2010
published in
DISTRIBUTED COMPUTING (DISC 2014)
Book
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Digital Object Identifier (DOI)
https://doi.org/10.1007/978-3-642-15546-8_6
Additional Document Info
start page
70
end page
86
volume
6358 LNCS