Ring Learning With Error (RLWE) algorithm is used in Post Quantum Cryptography (PQC) and Homomorphic Encryption (HE) algorithm. The existing classical crypto algorithms may be broken in quantum computers. The adversaries can store all encrypted data. While the quantum computer will be available, these encrypted data can be exposed by the quantum computer. Therefore, the PQC algorithms are an essential solution in recent applications. On the other hand, the HE allows operations on encrypted data which is appropriate for getting services from third parties without revealing confidential plain-texts. The FPGA based PQC and HE hardware accelerators like RLWE is much cost-effective than processor based platform and Application Specific Integrated Circuit (ASIC). FPGA based hardware accelerators still consume more power compare to ASIC based design. Near Threshold Computation (NTC) may be a convenient solution for FPGA based RLWE implementation. In this paper, we have implemented RLWE hardware accelerator which has 14 subcomponents. This paper creates clusters based on the critical path of all 14 subcomponents. Each cluster is implemented in an FPGA partition which has the same biasing voltage $V_{ccint}$. The clusters that have higher critical paths use higher Vccint to avoid timing failure. The clusters have lower critical paths use lower biasing voltage Vccint. This voltage scaled, partitioned RLWE can save ~6% and ~11% power in Vivado and VTR platform respectively. The resource usage and throughput of the implemented RLWE hardware accelerator is comparatively better than existing literature.
翻译:使用错误的 PQC 算法( RLWE ) 。 现有的古典加密算法可能会在量子计算机中被打破。 对手可以存储所有加密数据。 虽然量子计算机可以提供, 这些加密数据也可以通过量子计算机暴露。 因此, PQC 算法可能是最近应用程序中的一个基本解决方案。 另一方面, 高能允许使用加密数据操作, 这适合于从第三方获取服务, 而不透露机密的普通文本。 以 PQC 和 HE 硬件加速器如 RLWE 为基础的 FPGA PQC 和 HE 硬件加速器可能会在量子计算机中被打破。 以量子计算机为基础的 FPGA 硬件加速器仍然比以量子计算机为基础的设计使用更多的能量。 近端点 Comptation (NTC) 可能是基于 RLWE 执行FGA 的 FL6 硬硬件集集, 我们实施了14个子部件的RWE 硬件加速器。 这张纸上创建了以关键路径为基础的分类组, 使用每组的RFPD 的精度的精度路径。