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Towards Practical Privacy-Preserving Solution for Outsourced Neural
  Network Inference

Towards Practical Privacy-Preserving Solution for Outsourced Neural Network Inference

6 June 2022
Pinglan Liu
Wensheng Zhang
    FedML
ArXivPDFHTML

Papers citing "Towards Practical Privacy-Preserving Solution for Outsourced Neural Network Inference"

3 / 3 papers shown
Title
Integrating Homomorphic Encryption and Trusted Execution Technology for
  Autonomous and Confidential Model Refining in Cloud
Integrating Homomorphic Encryption and Trusted Execution Technology for Autonomous and Confidential Model Refining in Cloud
Pinglan Liu
Wensheng Zhang
29
0
0
02 Aug 2023
Citadel: Protecting Data Privacy and Model Confidentiality for
  Collaborative Learning with SGX
Citadel: Protecting Data Privacy and Model Confidentiality for Collaborative Learning with SGX
Chengliang Zhang
Junzhe Xia
Baichen Yang
Huancheng Puyang
Wei Wang
Ruichuan Chen
Istemi Ekin Akkus
Paarijaat Aditya
Feng Yan
FedML
53
39
0
04 May 2021
Slalom: Fast, Verifiable and Private Execution of Neural Networks in
  Trusted Hardware
Slalom: Fast, Verifiable and Private Execution of Neural Networks in Trusted Hardware
Florian Tramèr
Dan Boneh
FedML
114
395
0
08 Jun 2018
1