Invited Paper: Enhancing Privacy-Preserving Computing with Optimized CKKS Encryption: A Hardware Acceleration Approach
Year: 2024
Type: conference-paper
Abstract: The widespread adoption of the FHE (Fully Homomorphic Encryption) CKKS (Cheon-Kim-Kim-Song) encryption algorithm is stunted by its slow software implementation, driving the need for efficient hardware acceleration solutions. This paper presents a novel approach to address the challenge by optimizing a segment of the CKKS encryption and decryption process. Using the Residue Number System (RNS), the inputs are encoded into 32-bit representations and processed through the number theoretic transform (NTT). This innovative strategy reduces the utilities of the hardware resources and also accelerates calculations. This unified calculation methodology is designed to adapt inputs of diverse bit widths, seamlessly decoding them back into their original format after the CRT calculation, thereby significantly enhancing the throughput of calculations. We hope this work advances privacy-preserving computing in resource-constrained environments.
Authors: Tianyou Bao, Pengzhou He, Jiafeng Xie
Institution: Villanova University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4409282590
