Large-scale secure computation: Multi-party computation for (parallel) RAM programs

Elette Boyle; Kai Min Chung; Rafael Pass

doi:https://doi.org/10.1007/978-3-662-48000-7_36

Large-scale secure computation: Multi-party computation for (parallel) RAM programs

Elette Boyle, Kai Min Chung, Rafael Pass

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

We present the first efficient (i.e., polylogarithmic overhead) method for securely and privately processing large data sets over multiple parties with parallel, distributed algorithms. More specifically, we demonstrate load-balanced, statistically secure computation protocols for computing Parallel RAM (PRAM) programs, handling (1/3−ϵ) fraction malicious players, while preserving up to polylogarithmic factors the computation, parallel time, and memory complexities of the PRAM program, aside from a one-time execution of a broadcast protocol per party. Additionally, our protocol has polylog communication locality—that is, each of the n parties speaks only with polylog(n) other parties.

Original language	English
Title of host publication	Advances in Cryptology - CRYPTO 2015 - 35th Annual Cryptology Conference, Proceedings
Editors	Matthew Robshaw, Rosario Gennaro
Pages	742-762
Number of pages	21
DOIs	https://doi.org/10.1007/978-3-662-48000-7_36
State	Published - 2015
Externally published	Yes
Event	35th Annual Cryptology Conference, CRYPTO 2015 - Santa Barbara, United States Duration: 16 Aug 2015 → 20 Aug 2015

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9216

Conference

Conference	35th Annual Cryptology Conference, CRYPTO 2015
Country/Territory	United States
City	Santa Barbara
Period	16/08/15 → 20/08/15

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
Computer Science(all)

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https://doi.org/10.1007/978-3-662-48000-7_36

Cite this

Boyle, E., Chung, K. M., & Pass, R. (2015). Large-scale secure computation: Multi-party computation for (parallel) RAM programs. In M. Robshaw, & R. Gennaro (Eds.), Advances in Cryptology - CRYPTO 2015 - 35th Annual Cryptology Conference, Proceedings (pp. 742-762). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9216). https://doi.org/10.1007/978-3-662-48000-7_36

Boyle, Elette ; Chung, Kai Min ; Pass, Rafael. / Large-scale secure computation : Multi-party computation for (parallel) RAM programs. Advances in Cryptology - CRYPTO 2015 - 35th Annual Cryptology Conference, Proceedings. editor / Matthew Robshaw ; Rosario Gennaro. 2015. pp. 742-762 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "We present the first efficient (i.e., polylogarithmic overhead) method for securely and privately processing large data sets over multiple parties with parallel, distributed algorithms. More specifically, we demonstrate load-balanced, statistically secure computation protocols for computing Parallel RAM (PRAM) programs, handling (1/3−ϵ) fraction malicious players, while preserving up to polylogarithmic factors the computation, parallel time, and memory complexities of the PRAM program, aside from a one-time execution of a broadcast protocol per party. Additionally, our protocol has polylog communication locality—that is, each of the n parties speaks only with polylog(n) other parties.",

author = "Elette Boyle and Chung, {Kai Min} and Rafael Pass",

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Boyle, E, Chung, KM & Pass, R 2015, Large-scale secure computation: Multi-party computation for (parallel) RAM programs. in M Robshaw & R Gennaro (eds), Advances in Cryptology - CRYPTO 2015 - 35th Annual Cryptology Conference, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9216, pp. 742-762, 35th Annual Cryptology Conference, CRYPTO 2015, Santa Barbara, United States, 16/08/15. https://doi.org/10.1007/978-3-662-48000-7_36

Large-scale secure computation: Multi-party computation for (parallel) RAM programs. / Boyle, Elette; Chung, Kai Min; Pass, Rafael.
Advances in Cryptology - CRYPTO 2015 - 35th Annual Cryptology Conference, Proceedings. ed. / Matthew Robshaw; Rosario Gennaro. 2015. p. 742-762 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9216).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - We present the first efficient (i.e., polylogarithmic overhead) method for securely and privately processing large data sets over multiple parties with parallel, distributed algorithms. More specifically, we demonstrate load-balanced, statistically secure computation protocols for computing Parallel RAM (PRAM) programs, handling (1/3−ϵ) fraction malicious players, while preserving up to polylogarithmic factors the computation, parallel time, and memory complexities of the PRAM program, aside from a one-time execution of a broadcast protocol per party. Additionally, our protocol has polylog communication locality—that is, each of the n parties speaks only with polylog(n) other parties.

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Boyle E, Chung KM, Pass R. Large-scale secure computation: Multi-party computation for (parallel) RAM programs. In Robshaw M, Gennaro R, editors, Advances in Cryptology - CRYPTO 2015 - 35th Annual Cryptology Conference, Proceedings. 2015. p. 742-762. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: https://doi.org/10.1007/978-3-662-48000-7_36

Large-scale secure computation: Multi-party computation for (parallel) RAM programs

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