A Hardware Accelerator Designed For The Homomorphic SEAL-Embedded Library


A technical paper titled “VLSI Design and FPGA Implementation of an NTT Hardware Accelerator for Homomorphic SEAL-Embedded Library” was published by researchers at University of Pisa.


“Homomorphic Encryption (HE) allows performing specific algebraic computations on encrypted data without the need for decryption. For this reason, HE is emerging as a strong privacy-preserving solution in cloud computing environments since it allows to keep data secure even in the case the cloud server is not trusted. HE libraries such as Microsoft SEAL have been recently released; however, such libraries are not specifically designed for resource-constrained platforms and they are often expensive in terms of computational resources and memory consumption, which limits their usage in edge devices. This limitation is contained by the SEAL-Embedded library, the first C-based HE library specifically designed for embedded platforms. In this article, we propose a hardware accelerator specifically designed for the SEAL-Embedded library and its implementation of the CKKS scheme: the proposed hardware presents a configurable Number Theoretic Transform (NTT) unit for all the polynomial degrees available on the SEAL-Embedded, a memory architecture able to reduce the I/O latency and a dedicated module for the generation of roots of unity. A complete system that includes a 32-bit RISC-V processor has been implemented on a Xilinx ZCU106 FPGA board to test the functionality of the hardware accelerator and to measure performance improvements. The results showed a speed-up of around x1000 with the hardware acceleration respect to the pure software implementation of the SEAL-Embedded library for the symmetric encryption function.”

Find the technical paper here. Published: July 2023.

S. Di Matteo, M. L. Gerfo and S. Saponara, “VLSI Design and FPGA Implementation of an NTT Hardware Accelerator for Homomorphic SEAL-Embedded Library,” in IEEE Access, doi: 10.1109/ACCESS.2023.3295245.

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