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RAMPARTS: A Programmer-Friendly System for Building Homomorphic Encryption Applications

Authors:

David W. Archer,

José Manuel Calderón Trilla,

Alex Malozemoff,

Yuriy Polyakov,

Gerard RyanAuthors Info & Claims

WAHC'19: Proceedings of the 7th ACM Workshop on Encrypted Computing & Applied Homomorphic Cryptography

Pages 57 - 68

https://doi.org/10.1145/3338469.3358945

Published: 11 November 2019 Publication History

Abstract

Homomorphic Encryption (HE) is an emerging technology that enables computing on data while the data is encrypted. A major challenge with homomorphic encryption is that it takes extensive expert knowledge to design meaningful and useful programs that are constructed from atomic HE operations.

We present RAMPARTS to address this challenge. RAMPARTS provides an environment for developing HE applications in Julia, a high-level language, the same way as "cleartext'' applications are typically written in Julia. RAMPARTS makes the following three contributions. First, we use symbolic execution to automate the construction of an optimized computation circuit where both the circuit size and multiplicative depth are chosen by the compiler. Second, RAMPARTS automatically selects the HE parameters for the generated circuit, which is typically done manually by an HE expert. Third, RAMPARTS automatically selects the plaintext encoding for input values, and performs input and output data transformations. These three operations are not easily performed by programmers who are not HE experts. Thus, RAMPARTS makes HE more widely available and usable by the the population of programmers.

We compare our approach with Cingulata, the only previously known system that automatically generates circuits for HE computations. The HE circuits generated by RAMPARTS are significantly more efficient than the circuits compiled by Cingulata. For instance, our runtimes for key generation/circuit compilation and all online operations are more than one order of magnitude lower for a sample image processing application used for performance evaluation in our study.

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Index Terms

RAMPARTS: A Programmer-Friendly System for Building Homomorphic Encryption Applications
1. Security and privacy

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Published In

cover image ACM Conferences

WAHC'19: Proceedings of the 7th ACM Workshop on Encrypted Computing & Applied Homomorphic Cryptography

November 2019

74 pages

ISBN:9781450368292

DOI:10.1145/3338469

General Chairs:
Michael Brenner
Leibniz Universität Hannover
,
Tancrède Lepoint
Google LLC
,
Kurt Rohloff
NJIT & Duality Technologies

Copyright © 2019 ACM.

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Published: 11 November 2019

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November 11, 2019

London, United Kingdom

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Overall Acceptance Rate 6 of 17 submissions, 35%

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https://doi.org/10.23919/DATE58400.2024.10546534
Mouchet CChatel SPyrgelis ATroncoso CLuo BLiao XXu JKirda ELie D(2024)Helium: Scalable MPC among Lightweight Participants and under ChurnProceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications Security10.1145/3658644.3670346(3038-3052)Online publication date: 2-Dec-2024
https://dl.acm.org/doi/10.1145/3658644.3670346
Gouert CMouris DTsoutsos N(2024)Juliet: A Configurable Processor for Computing on Encrypted DataIEEE Transactions on Computers10.1109/TC.2024.341675273:9(2335-2349)Online publication date: Sep-2024
https://doi.org/10.1109/TC.2024.3416752
Kim DLee YCheon SChoi HLee JYoum HLee DKim H(2024)Privacy Set: Privacy-Authority-Aware Compiler for Homomorphic Encryption on Edge-Cloud SystemIEEE Internet of Things Journal10.1109/JIOT.2024.343735611:21(35167-35184)Online publication date: 1-Nov-2024
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