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Computers 2018, 7(4), 56; https://doi.org/10.3390/computers7040056

Locality Aware Path ORAM: Implementation, Experimentation and Analytical Modeling

College of Computer and Information Sciences, King Saud University, Riyadh 11451, Saudi Arabia
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Received: 10 October 2018 / Revised: 25 October 2018 / Accepted: 25 October 2018 / Published: 29 October 2018
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Abstract

In this paper, we propose an advanced implementation of Path ORAM to hide the access pattern to outsourced data into the cloud. This implementation takes advantage of eventual data locality and popularity by introducing a small amount of extra storage at the client side. Two replacement strategies are used to manage this extra storage (cache): the Least Recently Used (LRU) and the Least Frequently Used (LFU). Using the same test bed, conducted experiments clearly show the superiority of the advanced implementation compared to the traditional Path ORAM implementation, even for a small cache size and reduced data locality. We then present a mathematical model that provides closed form solutions when data requests follow a Zipf distribution with non-null parameter. This model is showed to have a small and acceptable relative error and is then well validated by the conducted experimental results. View Full-Text
Keywords: oblivious RAM; Path ORAM; data locality; Zeta function; caching; performance evaluation oblivious RAM; Path ORAM; data locality; Zeta function; caching; performance evaluation
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Al-Saleh, K.; Belghith, A. Locality Aware Path ORAM: Implementation, Experimentation and Analytical Modeling. Computers 2018, 7, 56.

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