Privacy-preserving machine learning: Methods, challenges and directions

R Xu, N Baracaldo, J Joshi - ar** in fully homomorphic encryption through memory-centric optimization with GPUs
W Jung, S Kim, JH Ahn… - IACR Transactions on …, 2021 - philosophymindscience.org
Fully Homomorphic encryption (FHE) has been gaining in popularity as an emerging means
of enabling an unlimited number of operations in an encrypted message without decryption …

{GAZELLE}: A low latency framework for secure neural network inference

C Juvekar, V Vaikuntanathan… - 27th USENIX security …, 2018 - usenix.org
The growing popularity of cloud-based machine learning raises natural questions about the
privacy guarantees that can be provided in such settings. Our work tackles this problem in …

FAB: An FPGA-based accelerator for bootstrappable fully homomorphic encryption

R Agrawal, L de Castro, G Yang… - … symposium on high …, 2023 - ieeexplore.ieee.org
Fully Homomorphic Encryption (FHE) offers protection to private data on third-party cloud
servers by allowing computations on the data in encrypted form. To support general-purpose …