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OptORAMa: Optimal Oblivious RAM

Publication ,  Conference
Asharov, G; Komargodski, I; Lin, WK; Nayak, K; Peserico, E; Shi, E
Published in: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
January 1, 2020

Oblivious RAM (ORAM), first introduced in the ground-breaking work of Goldreich and Ostrovsky (STOC ’87 and J. ACM ’96) is a technique for provably obfuscating programs’ access patterns, such that the access patterns leak no information about the programs’ secret inputs. To compile a general program to an oblivious counterpart, it is well-known that Ω (log N) amortized blowup is necessary, where N is the size of the logical memory. This was shown in Goldreich and Ostrovksy’s original ORAM work for statistical security and in a somewhat restricted model (the so called balls-and-bins model), and recently by Larsen and Nielsen (CRYPTO ’18) for computational security. A long standing open question is whether there exists an optimal ORAM construction that matches the aforementioned logarithmic lower bounds (without making large memory word assumptions, and assuming a constant number of CPU registers). In this paper, we resolve this problem and present the first secure ORAM with O(log N) amortized blowup, assuming one-way functions. Our result is inspired by and non-trivially improves on the recent beautiful work of Patel et al. (FOCS ’18) who gave a construction with O(log N· log log N) amortized blowup, assuming one-way functions. One of our building blocks of independent interest is a linear-time deterministic oblivious algorithm for tight compaction: Given an array of n elements where some elements are marked, we permute the elements in the array so that all marked elements end up in the front of the array. Our O(n) algorithm improves the previously best known deterministic or randomized algorithms whose running time is O(n · log n) or O(n · log log n), respectively.

Duke Scholars

Published In

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

DOI

EISSN

1611-3349

ISSN

0302-9743

ISBN

9783030457235

Publication Date

January 1, 2020

Volume

12106 LNCS

Start / End Page

403 / 432

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences
 

Citation

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ICMJE
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Asharov, G., Komargodski, I., Lin, W. K., Nayak, K., Peserico, E., & Shi, E. (2020). OptORAMa: Optimal Oblivious RAM. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12106 LNCS, pp. 403–432). https://doi.org/10.1007/978-3-030-45724-2_14
Asharov, G., I. Komargodski, W. K. Lin, K. Nayak, E. Peserico, and E. Shi. “OptORAMa: Optimal Oblivious RAM.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12106 LNCS:403–32, 2020. https://doi.org/10.1007/978-3-030-45724-2_14.
Asharov G, Komargodski I, Lin WK, Nayak K, Peserico E, Shi E. OptORAMa: Optimal Oblivious RAM. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2020. p. 403–32.
Asharov, G., et al. “OptORAMa: Optimal Oblivious RAM.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12106 LNCS, 2020, pp. 403–32. Scopus, doi:10.1007/978-3-030-45724-2_14.
Asharov G, Komargodski I, Lin WK, Nayak K, Peserico E, Shi E. OptORAMa: Optimal Oblivious RAM. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2020. p. 403–432.
Journal cover image

Published In

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

DOI

EISSN

1611-3349

ISSN

0302-9743

ISBN

9783030457235

Publication Date

January 1, 2020

Volume

12106 LNCS

Start / End Page

403 / 432

Related Subject Headings

  • Artificial Intelligence & Image Processing
  • 46 Information and computing sciences