TFHE-SBC：面向单板计算机上环面全同态加密的软件设计
TFHE-SBC: Software Designs for Fully Homomorphic Encryption over the Torus on Single Board Computers
AI总结：
针对单板计算机上TFHE加密效率低、密文大及硬件加速受限的问题，提出专用软件设计TFHE-SBC，加速客户端操作，使加密速度提升2486倍、通信效率提升512倍、能效提升12至2004倍。
AI中文摘要：
全同态加密（FHE）是一项能够在保护数据（包括单板计算机（SBCs）收集的敏感信息）的同时，在云服务器上进行统计处理和机器学习的技术。在FHE方案中，TFHE方案能够执行同态NAND操作，并且与其他FHE方案不同，它可以执行最小值、最大值和比较等各种操作。然而，TFHE需要Torus Learning With Error（TLWE）加密，该加密每次仅加密一位，导致其加密效率较低且密文尺寸较其他方案更大。此外，与服务器相比，SBC拥有的硬件加速器数量有限，这使得实现与服务器同等水平的优化极具挑战性。在本研究中，我们提出了一种新颖的针对SBC的专用设计TFHE-SBC，以加速客户端TFHE操作并提升通信与能效。实验结果表明，TFHE-SBC加密速度最高提升2486倍，通信效率提升512倍，且能效比现有技术高出12至2004倍。
英文摘要：
Fully homomorphic encryption (FHE) is a technique that enables statistical processing and machine learning while protecting data, including sensitive information collected by single board computers (SBCs), on a cloud server. Among FHE schemes, the TFHE scheme is capable of homomorphic NAND operations and, unlike other FHE schemes, can perform various operations such as minimum, maximum, and comparison. However, TFHE requires Torus Learning With Error (TLWE) encryption, which encrypts one bit at a time, leading to less efficient encryption and larger ciphertext size compared to other schemes. Additionally, SBCs have a limited number of hardware accelerators compared to servers, making it challenging to achieve the same level of optimization as on servers. In this study, we propose a novel SBC-specific design, \textsf{TFHE-SBC}, to accelerate client-side TFHE operations and enhance communication and energy efficiency. Experimental results demonstrate that \textsf{TFHE-SBC} encryption is up to 2486 times faster, improves communication efficiency by 512 times, and achieves 12 to 2004 times greater energy efficiency than the state-of-the-art.
