Revisiting Square Root ORAM

Efficient Random Access in Multi-Party Computation

Hiding memory access patterns is required for secure computation, but remains prohibitively expensive for many interesting applications. Prior work has either developed custom algorithms that minimize the need for data-dependant memory access, or proposed the use of Oblivious RAM (ORAM) to provide a general-purpose solution. However, most ORAMs are designed for client-server scenarios, and provide only asymptotic benefits in secure computation.

We show how the classical square-root ORAM of Goldreich and Ostrovsky can be modified to provide a practical ORAM for use in secure computation, even though it is asymptotically worse than the best known schemes. Specifically, we show a design that has over 100x lower initialization cost, and provides benefits over linear scan for just 8 blocks of data. Our scheme outperforms alternate approaches across a wide range of parameters, often by several orders of magnitude.

Code

https://github.com/samee/sqrtOram

This repository includes the implementation of Square-Root ORAM in Obliv-C, as well as several example applications and benchmarks.

Paper

Samee Zahur, Xiao Wang, Mariana Raykova, Adrià Gascón, Jack Doerner, David Evans, Jonathan Katz. Revisiting Square-Root ORAM Efficient Random Access in Multi-Party Computation. In 37th IEEE Symposium on Security and Privacy (“Oakland”). San Jose, CA. 23-25 May 2016.

People

Samee Zahur (University of Virginia), Project Founder and Leader
Xiao Wang (University of Maryland)
Mariana Raykova (Yale University)
Adrià Gascón (University of Edinburgh)
Jack Doerner (University of Virginia)
David Evans (University of Virginia)
Jonathan Katz (University of Maryland)