LAUSR

Homomorphic encryption (HE) has emerged as an ideal cryptographic technology for meaningful computations on encrypted data. Not only does HE secure private information even if the ciphertext is leaked, but it also maintains data integrity when inferring cloud-side services. However, homomorphic computations include expensive polynomial arithmetic, especially polynomial multiplication. Prior studies proposed number theoretic transform (NTT) hardware designs to accelerate polynomial multiplication. However, the trade-off between hardware complexity and throughput of NTT designs was not considered carefully. This paper proposes an area-efficient NTT architecture suitable for HE schemes. Center of the proposed NTT architecture is a high-throughput butterfly unit array, which communicates with a single data memory unit through a conflict-free memory access pattern. Additionally, we developed a twiddle factor generator to reduce memory consumption. The proposed NTT architecture was successfully accelerated on the Xilinx FPGA devices. Performing with a large number of moduli, the proposed NTT design achieves higher hardware efficiency than the prior arts. Especially, our NTT design consumes less on-chip memory with efficiency improvement of $8.8\times $ over the most related work. The implementation results confirm that our design methodology has advantages to deploy many NTT accelerators on an FPGA device for practical HE-based applications.