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DarKnight: A Data Privacy Scheme for Training and Inference of Deep
  Neural Networks
v1v2 (latest)

DarKnight: A Data Privacy Scheme for Training and Inference of Deep Neural Networks

1 June 2020
H. Hashemi
Yongqin Wang
M. Annavaram
    FedML
ArXiv (abs)PDFHTML

Papers citing "DarKnight: A Data Privacy Scheme for Training and Inference of Deep Neural Networks"

11 / 11 papers shown
Characterization of GPU TEE Overheads in Distributed Data Parallel ML Training
Characterization of GPU TEE Overheads in Distributed Data Parallel ML Training
Jonghytun Lee
Yongqin Wang
Rachit Rajat
M. Annavaram
306
3
0
20 Jan 2025
Fastrack: Fast IO for Secure ML using GPU TEEs
Fastrack: Fast IO for Secure ML using GPU TEEs
Yongqin Wang
Rachit Rajat
Jonghyun Lee
Tingting Tang
M. Annavaram
276
6
0
20 Oct 2024
PristiQ: A Co-Design Framework for Preserving Data Security of Quantum
  Learning in the Cloud
PristiQ: A Co-Design Framework for Preserving Data Security of Quantum Learning in the Cloud
Zhepeng Wang
Yi Sheng
Nirajan Koirala
Kanad Basu
Taeho Jung
Cheng-Chang Lu
Weiwen Jiang
312
5
0
20 Apr 2024
CompactTag: Minimizing Computation Overheads in Actively-Secure MPC for
  Deep Neural Networks
CompactTag: Minimizing Computation Overheads in Actively-Secure MPC for Deep Neural Networks
Yongqin Wang
Pratik Sarkar
Nishat Koti
A. Patra
Murali Annavaram
319
3
0
08 Nov 2023
Data-Centric Long-Tailed Image Recognition
Data-Centric Long-Tailed Image Recognition
Yanbiao Ma
Licheng Jiao
Fang Liu
Shuyuan Yang
Xu Liu
Puhua Chen
408
1
0
03 Nov 2023
Efficient Privacy-Preserving Machine Learning with Lightweight Trusted
  Hardware
Efficient Privacy-Preserving Machine Learning with Lightweight Trusted HardwareProceedings on Privacy Enhancing Technologies (PoPETs), 2022
Pengzhi Huang
Thang Hoang
Yueying Li
Elaine Shi
G. E. Suh
414
6
0
18 Oct 2022
MPC-Pipe: an Efficient Pipeline Scheme for Secure Multi-party Machine
  Learning Inference
MPC-Pipe: an Efficient Pipeline Scheme for Secure Multi-party Machine Learning InferenceInternational Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), 2022
Yongqin Wang
Rachit Rajat
Murali Annavaram
232
6
0
27 Sep 2022
LAORAM: A Look Ahead ORAM Architecture for Training Large Embedding
  Tables
LAORAM: A Look Ahead ORAM Architecture for Training Large Embedding TablesInternational Symposium on Computer Architecture (ISCA), 2021
Rachit Rajat
Yongqin Wang
M. Annavaram
254
11
0
16 Jul 2021
Enabling Inference Privacy with Adaptive Noise Injection
Enabling Inference Privacy with Adaptive Noise Injection
Sanjay Kariyappa
Ousmane Amadou Dia
Moinuddin K. Qureshi
257
6
0
06 Apr 2021
FedML: A Research Library and Benchmark for Federated Machine Learning
FedML: A Research Library and Benchmark for Federated Machine Learning
Chaoyang He
Songze Li
Jinhyun So
Xiao Zeng
Mi Zhang
...
Yang Liu
Ramesh Raskar
Qiang Yang
M. Annavaram
Salman Avestimehr
FedML
788
686
0
27 Jul 2020
Privacy in Deep Learning: A Survey
Privacy in Deep Learning: A Survey
Fatemehsadat Mirshghallah
Mohammadkazem Taram
Praneeth Vepakomma
Abhishek Singh
Ramesh Raskar
H. Esmaeilzadeh
FedML
608
149
0
25 Apr 2020
1
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