Oblivious RAM: A dissection and experimental evaluation

Zhao Chang, Dong Xie, Feifei Li

Research output: Contribution to journalConference articlepeer-review

Abstract

Many companies choose the cloud as their data and IT infrastructure platform. The remote access of the data brings the issue of trust. Despite the use of strong encryption schemes, adversaries can still learn valuable information regarding encrypted data by observing the data access patterns. To that end, one can hide the access patterns, which may leak sensitive information, using Oblivious RAMs (ORAMs). Numerous works have proposed different ORAM constructions, but they have never been thoroughly compared against and tested on large databases. There are also no open source implementation of these schemes. These limitations make it difficult for researchers and practitioners to choose and adopt a suitable ORAM for their applications. To address this issue, we provide a thorough study over several practical ORAM constructions, and implement them under the same library. We perform extensive experiments to provide insights into their performance characteristics with respect to efficiency, scalability, and communication cost.

Original languageEnglish (US)
Pages (from-to)1113-1124
Number of pages12
JournalProceedings of the VLDB Endowment
Volume9
Issue number12
DOIs
StatePublished - 2016
Event42nd International Conference on Very Large Data Bases, VLDB 2016 - New Delhi, India
Duration: Sep 5 2016Sep 9 2016

All Science Journal Classification (ASJC) codes

  • Computer Science (miscellaneous)
  • Computer Science(all)

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