TECHNOLOGY Outsourced Data By Using Hamming Joins
Vijay J. Chaudhari · 2014
In this paper we introduce a mechanism f or executing general binary JOIN operations (for predicates that satisfy certain properties) in an outsourced relational database framework with computational privacy and low overhead – a first, to the best of our knowledge. In an outsourced database framework, clients place data management responsibilities 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”. We experimentally evaluate the main overhead components and show they are reasonable. We illustrate via a set of r ele-vant 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 – m apping antibiotics to bacteria). The initial client computation overhead for 100000 data items is around 5 minutes and our privacy mechanisms can sustain theoretical throughputs of several million predicate evaluations per second, even for an un-optimized Open SSL based implementation.