6 citations · 10 across the 2 of their papers we have counts for
2 papers
cs.CR2023★ 6 cited
REED: Chiplet-Based Accelerator for Fully Homomorphic Encryption
Aikata Aikata, Ahmet Can Mert, Sunmin Kwon +2
Fully Homomorphic Encryption (FHE) enables privacy-preserving computation and has many applications. However, its practical implementation faces massive computation and memory over…
cs.LG2021★ 4 cited
Privacy-Preserving Machine Learning with Fully Homomorphic Encryption for Deep Neural Network
Joon-Woo Lee, HyungChul Kang, Yongwoo Lee +8
Fully homomorphic encryption (FHE) is one of the prospective tools for privacypreserving machine learning (PPML), and several PPML models have been proposed based on various FHE sc…