Welcome to the resource topic for 2014/072
Title:
Efficient Privacy-Preserving Big Data Processing through Proxy-Assisted ORAM
Authors: Nikolaos P. Karvelas, Andreas Peter, Stefan Katzenbeisser, 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.
ePrint: https://eprint.iacr.org/2014/072
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