Fast ORAM with Server-Aided Preprocessing and Pragmatic Privacy-Efficiency Trade-Off

Vladimir Kolesnikov, Stanislav Peceny, Ni Trieu, Xiao Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Data-dependent accesses to memory are necessary for many real-world applications, but their cost remains prohibitive in secure computation. Prior work either focused on minimizing the need for data-dependent access in these applications, or reduced its cost by improving oblivious RAM for secure computation (SC-ORAM). Despite extensive efforts to improve SC-ORAM, the most concretely efficient solutions still require ≈ 0.7 s per access to arrays of 230 entries. This plainly precludes using MPC in a number of settings. In this work, we take a pragmatic approach, exploring how concretely cheap MPC RAM access could be made if we are willing to allow one of the participants to learn the access pattern. We design a highly efficient Shared-Output Client-Server ORAM (SOCS- ORAM ) that has constant overhead, uses one round-trip of interaction per access, and whose access cost is independent of array size. SOCS- ORAM is useful in settings with hard performance constraints, where one party in the computation is more trust-worthy and is allowed to learn the RAM access pattern. Our SOCS- ORAM is assisted by a third helper party that helps initialize the protocol and is designed for the honest-majority semi-honest corruption model. We implement our construction in C++ and report its performance. For an array of length 230 with 4B entries, we communicate 13B per access and take essentially no overhead beyond network latency.

Original languageEnglish (US)
Title of host publicationCyber Security, Cryptology, and Machine Learning - 7th International Symposium, CSCML 2023, Proceedings
EditorsShlomi Dolev, Ehud Gudes, Pascal Paillier
PublisherSpringer Science and Business Media Deutschland GmbH
Pages439-457
Number of pages19
ISBN (Print)9783031346705
DOIs
StatePublished - 2023
Event7th International Symposium on Cyber Security, Cryptology, and Machine Learning, CSCML 2023 - Be'er Sheva, Israel
Duration: Jun 29 2023Jun 30 2023

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13914 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference7th International Symposium on Cyber Security, Cryptology, and Machine Learning, CSCML 2023
Country/TerritoryIsrael
CityBe'er Sheva
Period6/29/236/30/23

Keywords

  • Oblivious RAM
  • Secure Computation

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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