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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Vydáno v:IEEE transactions on computers Ročník 73; číslo 9; s. 2335 - 2349
Hlavní autoři: Gouert, Charles, Mouris, Dimitris, Tsoutsos, Nektarios Georgios
Médium: Journal Article
Jazyk:angličtina
Vydáno: IEEE 01.09.2024
Témata:
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
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Shrnutí: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