How To Scale Multi-Party Computation

We propose a solution for optimized scaling of multi-party computation using the MP-SPDZ framework (CCS'20).It does not use manual optimization but extends the compiler and the virtual machine of the framework, thus providing an improvement for any user.We found that our solution improves timings four-fold for a simple example in MP-SPDZ, and it improves an order of magnitude on every framework using secret sharing considered by Hastings et al. (S&P'19) either in terms of time or RAM usage.The core of our approach is finding a balance between communication round optimization and memory usage.

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Publication Details

Published
2025-02-10
DOI
https://doi.org/10.1145/3727166.3727167
Primary Topic
Cryptography and Data Security
Type
article
Field-Weighted Citation Impact
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article

How To Scale Multi-Party Computation

Marcel Keller
Cryptography and Data Security
article

How To Scale Multi-Party Computation

Marcel Keller
article en

Abstract

We propose a solution for optimized scaling of multi-party computation using the MP-SPDZ framework (CCS'20).It does not use manual optimization but extends the compiler and the virtual machine of the framework, thus providing an improvement for any user.We found that our solution improves timings four-fold for a simple example in MP-SPDZ, and it improves an order of magnitude on every framework using secret sharing considered by Hastings et al. (S&P'19) either in terms of time or RAM usage.The core of our approach is finding a balance between communication round optimization and memory usage.

Commonwealth Scientific and Industrial Research Organisation (AU), Data61 (AU)
Openalex Percentile: Top 93%
Cryptography and Data Security
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