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Juliet: A Configurable Processor for Computing on Encrypted Data
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AI
DOI：10.1109/TC.2024.3416752.png)
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Abstract
En 中文
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.
Keywords:
Cryptography
Noise
Circuits
Libraries
Cloud computing
Computers
Assembly
Applied cryptography
encrypted processor
hardware acceleration
homomorphic encryption
privacy-enhancing technologies
privacy-preserving ISA
private computation
secure cloud computing
Journal
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3.8
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5.3K
Citations:
9.8K
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