| Title | Accelerating Fully Homomorphic Encryption Through Microarchitecture-Aware Analysis and Optimization |
| Publication Type | Conference Paper |
| Year of Publication | 2021 |
| Authors | Jung, Wonkyung, Lee, Eojin, Kim, Sangpyo, Kim, Namhoon, Lee, Keewoo, Min, Chohong, Cheon, Jung Hee, Ahn, Jung Ho |
| Conference Name | 2021 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS) |
| Keywords | Acceleration, application analysis, cloud computing, computational complexity, Encryption, homomorphic encryption, human factors, Metrics, microarchitecture, Multicore processing, Performance analysis, pubcrawl, resilience, Resiliency, Scalability, Software |
| Abstract | Homomorphic Encryption (HE) [11] draws significant attention as a privacy-preserving way for cloud computing because it allows computation on encrypted messages called ciphertexts. Among numerous FHE schemes [2]-[4], [8], [9], HE for Arithmetic of Approximate Numbers (HEAAN [3]), which is also known as CKKS (Cheon-Kim-Kim-Song), is rapidly gaining popularity [10] as it supports computation on real numbers. A critical shortcoming of HE is the high computational complexity of ciphertext arithmetic, especially, HE multiplication (HE Mul). For example, the execution time for computation on encrypted data (ciphertext) increases from 100s to 10,000s of times compared to that on native, unen-crypted messages. However, a large body of HE acceleration studies, including ones exploiting GPUs and FPGAs, lack a rigorous analysis of computational complexity and data access patterns of HE Mul with large parameter sets on CPUs, the most popular computing platform. |
| DOI | 10.1109/ISPASS51385.2021.00045 |
| Citation Key | jung_accelerating_2021 |
Accelerating Fully Homomorphic Encryption Through Microarchitecture-Aware Analysis and Optimization