Paper 2023/310
Ramen: Souper Fast Three-Party Computation for RAM Programs
Abstract
Secure RAM computation allows a number of parties to evaluate a function represented as a RAM program in a way that reveals nothing about the private inputs of the parties except from what is already revealed by the function output itself. In this work we present Ramen, which is a new protocol for computing RAM programs securely among three parties, tolerating up to one passive corruption. Ramen provides reasonable asymptotic guarantees and is concretely efficient at the same time. We have implemented our protocol and provide extensive benchmarks for various settings. Asymptotically, our protocol requires a constant number of rounds and a amortized sublinear amount of communication and computation per memory access. In terms of concrete efficiency, our protocol outperforms previous solutions. For a memory of size $2^{26}$ our memory accesses are \(30\times\) faster in the LAN and \(8.7\times\) faster in the WAN setting, when compared to the previously fastest solution by Vadapalli, Henry, and Goldberg (ePrint 2022). Due to our superior asymptotic guarantees, the efficiency gap is only widening as the memory gets larger and for this reason Ramen provides the currently most scalable concretely efficient solution for securely computing RAM programs.
Metadata
- Available format(s)
-
PDF
- Category
- Cryptographic protocols
- Publication info
- Preprint.
- Keywords
- multiparty computationthree-party computationramdistributed oram
- Contact author(s)
-
braun @ cs au dk
mahakp @ cs au dk
rahulrachuri @ fastmail com
mark simkin @ ethereum org - History
- 2023-03-03: approved
- 2023-03-02: received
- See all versions
- Short URL
- https://ia.cr/2023/310
- License
-
CC BY
BibTeX
@misc{cryptoeprint:2023/310, author = {Lennart Braun and Mahak Pancholi and Rahul Rachuri and Mark Simkin}, title = {Ramen: Souper Fast Three-Party Computation for RAM Programs}, howpublished = {Cryptology ePrint Archive, Paper 2023/310}, year = {2023}, note = {\url{https://eprint.iacr.org/2023/310}}, url = {https://eprint.iacr.org/2023/310} }