Privacy-preserving machine learning: Methods, challenges and directions
R Xu, N Baracaldo, J Joshi - ar** that data private. This capability has great potential for machine-learning …
Delphi: A cryptographic inference system for neural networks
Many companies provide neural network prediction services to users for a wide range of
applications. However, current prediction systems compromise one party's privacy: either the …
applications. However, current prediction systems compromise one party's privacy: either the …
Low-complexity deep convolutional neural networks on fully homomorphic encryption using multiplexed parallel convolutions
Recently, the standard ResNet-20 network was successfully implemented on the fully
homomorphic encryption scheme, residue number system variant Cheon-Kim-Kim-Song …
homomorphic encryption scheme, residue number system variant Cheon-Kim-Kim-Song …
CryptGPU: Fast privacy-preserving machine learning on the GPU
We introduce CryptGPU, a system for privacy-preserving machine learning that implements
all operations on the GPU (graphics processing unit). Just as GPUs played a pivotal role in …
all operations on the GPU (graphics processing unit). Just as GPUs played a pivotal role in …
VeriFL: Communication-Efficient and Fast Verifiable Aggregation for Federated Learning
Federated learning (FL) enables a large number of clients to collaboratively train a global
model through sharing their gradients in each synchronized epoch of local training …
model through sharing their gradients in each synchronized epoch of local training …
Cryptflow2: Practical 2-party secure inference
We present CrypTFlow2, a cryptographic framework for secure inference over realistic Deep
Neural Networks (DNNs) using secure 2-party computation. CrypTFlow2 protocols are both …
Neural Networks (DNNs) using secure 2-party computation. CrypTFlow2 protocols are both …
Falcon: Honest-majority maliciously secure framework for private deep learning
We propose Falcon, an end-to-end 3-party protocol for efficient private training and
inference of large machine learning models. Falcon presents four main advantages-(i) It is …
inference of large machine learning models. Falcon presents four main advantages-(i) It is …