Fully homomorphic encryption (FHE) has experienced significant development and continuous breakthroughs in theory, enabling its widespread application in various fields, like outsourcing computation and secure multi-party computing, in order to preserve privacy. Nonetheless, the application of FHE is constrained by its substantial computing overhead and storage cost. Researchers have proposed practical acceleration solutions to address these issues. This paper aims to provide a comprehensive survey for systematically comparing and analyzing the strengths and weaknesses of FHE acceleration schemes, which is currently lacking in the literature. The relevant researches conducted between 2019 and 2022 are investigated. We first provide a comprehensive summary of the latest research findings on accelerating FHE, aiming to offer valuable insights for researchers interested in FHE acceleration. Secondly, we classify existing acceleration schemes from algorithmic and hardware perspectives. We also propose evaluation metrics and conduct a detailed comparison of various methods. Finally, our study presents the future research directions of FHE acceleration, and also offers both guidance and support for practical application and theoretical research in this field.
翻译:全同态加密(Fully Homomorphic Encryption, FHE) 在理论上得到了重大的发展和不断的突破,从而使其在保护隐私方面的各个领域得到了广泛的应用,如计算外包和安全多方计算。但是,FHE 的应用受到其大量的计算开销和存储成本的限制。为了解决这些问题,研究人员提出了实用的加速方案。本文旨在提供一份全面的调查,对 FHE 加速方案的优缺点进行了系统性比较和分析,这在现有文献中目前缺乏。研究人员调查了 2019 年到 2022 年期间开展的相关研究。本文首先提供了最新的有关 FHE 加速的研究结果的全面总结,旨在为对 FHE 加速感兴趣的研究人员提供有价值的洞察力。其次,我们从算法和硬件两个角度对现有的加速方案进行分类,提出评估指标并对各种方法进行了详细的比较。最后,我们的研究提出了 FHE 加速的未来研究方向,并为这个领域的实际应用和理论研究提供了指导和支持。