Cryptology ePrint Archive: Report 2014/072
Efficient Privacy-Preserving Big Data Processing through Proxy-Assisted ORAM
Nikolaos P. Karvelas and Andreas Peter and Stefan Katzenbeisser and Sebastian Biedermann
Abstract: We present a novel mechanism that allows a client
to securely outsource his private data to the cloud while at the same
time to delegate to a third party the right to run
certain algorithms on his data. The mechanism is
privacy-preserving, meaning that the third party only learns the result
of his algorithm on the client's data, while at the same time the access
pattern on the client's data is hidden from the cloud. To achieve this we
combine recent advances in the field of Oblivious RAM and Secure Two-Party
Computation: We develop an Oblivious RAM which is ran between the cloud and a
proxy server, and which does not need the data to be decrypted at any
point. The evaluation on the data is done by employing Yao's garbled
circuit solution for Secure Two-Party Computation.
Category / Keywords:
Date: received 3 Feb 2014
Contact author: karvelas at seceng informatik tu-darmstadt de
Available format(s): PDF | BibTeX Citation
Version: 20140204:170100 (All versions of this report)
Short URL: ia.cr/2014/072
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