By Topic

Toward Private Joins on Outsourced Data

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Carbunar, Bogdan ; Florida International University, Miami ; Sion, Radu

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.” 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 computational privacy and low overhead—the 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. The initial client computation overhead for 100,000 data items is around 5 minutes and our privacy mechanisms can sustain theoretical throughputs of several million predicate evaluations per second, even for an unoptimized OpenSSL-based implementation.

Published in:

Knowledge and Data Engineering, IEEE Transactions on  (Volume:24 ,  Issue: 9 )