Juliet: A Configurable Processor for Computing on Encrypted Data

Fully homomorphic encryption (FHE) has become progressively more viable in the years since its original inception in 2009. At the same time, leveraging state-of-the-art schemes in an efficient way for general computation remains prohibitively difficult for the average programmer. In this work, we in...

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Bibliographic Details
Published in:IEEE transactions on computers Vol. 73; no. 9; pp. 2335 - 2349
Main Authors: Gouert, Charles, Mouris, Dimitris, Tsoutsos, Nektarios Georgios
Format: Journal Article
Language:English
Published: IEEE 01.09.2024
Subjects:
Applied cryptography
Assembly
Circuits
Cloud computing
Computers
Cryptography
encrypted processor
hardware acceleration
homomorphic encryption
Libraries
Noise
privacy-enhancing technologies
privacy-preserving ISA
private computation
secure cloud computing
ISSN:0018-9340, 1557-9956
Online Access:Get full text
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Summary:Fully homomorphic encryption (FHE) has become progressively more viable in the years since its original inception in 2009. At the same time, leveraging state-of-the-art schemes in an efficient way for general computation remains prohibitively difficult for the average programmer. In this work, we introduce a new design for a fully homomorphic processor, dubbed Juliet, to enable faster operations on encrypted data using the state-of-the-art TFHE and cuFHE libraries for both CPU and GPU evaluation. To improve usability, we define an expressive assembly language and instruction set architecture (ISA) judiciously designed for end-to-end encrypted computation. We demonstrate Juliet's capabilities with a broad range of realistic benchmarks including cryptographic algorithms, such as the lightweight ciphers Simon and Speck , as well as logistic regression (LR) inference and matrix multiplication.
ISSN:0018-9340
1557-9956
DOI:10.1109/TC.2024.3416752