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, TFHE-SBC, to accelerate client-side TFHE operations and enhance communication and energy efficiency. Experimental results demonstrate that 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.
Matsumoto et al. (Tue,) studied this question.
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