With the expansion of cloud services, serious concerns about the privacy of users' data arise due to the exposure of the unencrypted data to the server during computation. Various security primitives are under investigation to preserve privacy while evaluating private data, including Fully Homomorphic Encryption (FHE), Private Set Intersection (PSI), and others. However, the prohibitive processing time of these primitives hinders their practical applications. This work proposes and implements an architecture for accelerating third-generation FHE with Amazon Web Services (AWS) cloud FPGAs, marking the first hardware acceleration solution for third-generation FHE. We also introduce a novel unbalanced PSI protocol based on third-generation FHE, optimized for the proposed hardware architecture. Several algorithm-architecture co-optimization techniques are introduced to allow the communication and computation costs to be independent of the Sender's set size. The measurement results show that the proposed accelerator achieves $>21\times$ performance improvement compared to a software implementation for various crucial subroutines of third-generation FHE and the proposed PSI.
翻译:随着云层服务的扩大,由于在计算过程中未加密的数据暴露在服务器上,用户数据隐私问题引起了严重关切。正在调查各种安全原始材料,以维护隐私,同时评价私人数据,包括全单态加密(FHE)、私立Set交叉路段(PSI)和其他数据。然而,这些原始材料的令人望而却步的处理时间妨碍了它们的实际应用。这项工作提议并执行一项结构,以加速第三代FHE与亚马逊网络服务(AWS)云层FPGAs的第三代FGAs的FHE加速方案,标志着第三代FHE的首个硬件加速解决方案。我们还采用了基于第三代FHE(FHE)的新颖的PSI不平衡协议,优化了拟议硬件结构。采用了几种算法结构共同优化技术,使通信和计算成本独立于发件人设定的尺寸。测量结果显示,与第三代FHE和拟议PSI的各种关键次路段的软件实施相比,拟议的加速器的性能改进为21美元以上。