TY  - JOUR
T1  - Optimizing Homomorphic Compiler HedgeHog for DNN Model based on CKKS Homomorphic Encryption Scheme
AU  - Lee, Dongkwon 
AU  - Lee, Gyejin 
AU  - Kim, Suchan 
AU  - Song, Woosung 
AU  - Lee, Dohyung 
AU  - Kim, Hoon 
AU  - Jo, Seunghan 
AU  - Park, Kyuyeon 
AU  - Yi, Kwangkeun 
JO  - Journal of KIISE, JOK
PY  - 2022
DA  - 2022/1/14
DO  - 10.5626/JOK.2022.49.9.743
KW  - CKKS fully homomorphic encryption scheme
KW  - homomorphic compiler
KW  - optimization
KW  - DNN
AB  - We present a new state-of-the-art optimizing homomorphic compiler HedgeHog based on high-level input language. Although homomorphic encryption enables safe and secure third party computation, it is hard to build high-performance HE applications without expertise. Homomorphic compiler lowers this hurdle, but most of the existing compilers are based on HE scheme that does not support real number computation and a few compilers based on the CKKS HE scheme that supports real number computation uses low-level input language. We present an optimizing compiler HedgeHog whose input language supports high-level DNN operators. In addition to its ease of use, compiled HE code shows a maximum of 22% more of speedup than the existing state-of-the-art compiler.