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1911.07101
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Glyph: Fast and Accurately Training Deep Neural Networks on Encrypted Data
Neural Information Processing Systems (NeurIPS), 2019
16 November 2019
Qian Lou
Bo Feng
Geoffrey C. Fox
Lei Jiang
FedML
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Papers citing
"Glyph: Fast and Accurately Training Deep Neural Networks on Encrypted Data"
40 / 40 papers shown
DictPFL: Efficient and Private Federated Learning on Encrypted Gradients
Jiaqi Xue
Mayank Kumar
Yuzhang Shang
Shangqian Gao
Rui Ning
Mengxin Zheng
Xiaoqian Jiang
Qian Lou
FedML
198
0
0
24 Oct 2025
Functional Encryption in Secure Neural Network Training: Data Leakage and Practical Mitigations
Alexandru Ioniţă
Andreea Ioniţă
FedML
107
0
0
25 Sep 2025
SoK: Data Minimization in Machine Learning
Robin Staab
Nikola Jovanović
Kimberly Mai
Prakhar Ganesh
Martin Vechev
Ferdinando Fioretto
Matthew Jagielski
153
0
0
14 Aug 2025
Private LoRA Fine-tuning of Open-Source LLMs with Homomorphic Encryption
Jordan Fréry
Roman Bredehoft
Jakub Klemsa
Arthur Meyre
Andrei Stoian
207
5
0
12 May 2025
Silenzio: Secure Non-Interactive Outsourced MLP Training
Jonas Sander
T. Eisenbarth
289
0
0
24 Apr 2025
SoK: Can Fully Homomorphic Encryption Support General AI Computation? A Functional and Cost Analysis
Jiaqi Xue
Xin Xin
Wei-na Zhang
Mengxin Zheng
Qianqian Song
...
Jiafeng Xie
Liqiang Wang
David Mohaisen
Hongyi Wu
Qian Lou
FedML
293
1
0
15 Apr 2025
TFHE-Coder: Evaluating LLM-agentic Fully Homomorphic Encryption Code Generation
Mayank Kumar
Jinbao Xue
Mengxin Zheng
Qian Lou
302
8
0
15 Mar 2025
TFHE-SBC: Software Designs for Fully Homomorphic Encryption over the Torus on Single Board Computers
Marin Matsumoto
Ai Nozaki
Hideki Takase
M. Oguchi
181
0
0
04 Mar 2025
CipherPrune: Efficient and Scalable Private Transformer Inference
International Conference on Learning Representations (ICLR), 2025
Yancheng Zhang
Jinbao Xue
Mengxin Zheng
Mimi Xie
Mingzhe Zhang
Lei Jiang
Qian Lou
316
11
0
24 Feb 2025
RewardDS: Privacy-Preserving Fine-Tuning for Large Language Models via Reward Driven Data Synthesis
Jianwei Wang
Junyao Yang
Haoran Li
Huiping Zhuang
Qianli Ma
Huiping Zhuang
Cen Chen
Ziqian Zeng
SyDa
382
1
0
23 Feb 2025
DataSeal: Ensuring the Verifiability of Private Computation on Encrypted Data
IEEE Symposium on Security and Privacy (S&P), 2024
M. Santriaji
Jiaqi Xue
Qian Lou
Yan Solihin
FedML
224
10
0
19 Oct 2024
CryptoTrain: Fast Secure Training on Encrypted Dataset
Jiaqi Xue
Yancheng Zhang
YanShan Wang
Xueqiang Wang
Hao Zheng
Qian Lou
334
4
0
25 Sep 2024
A Pervasive, Efficient and Private Future: Realizing Privacy-Preserving Machine Learning Through Hybrid Homomorphic Encryption
Symposium on Dependable Autonomic and Secure Computing (DASC), 2024
Khoa Nguyen
Mindaugas Budzys
E. Frimpong
Tanveer Khan
A. Michalas
156
7
0
10 Sep 2024
CURE: Privacy-Preserving Split Learning Done Right
Halil Ibrahim Kanpak
Aqsa Shabbir
Esra Genç
Alptekin Küpçü
Sinem Sav
218
3
0
12 Jul 2024
Secure Outsourced Decryption for FHE-based Privacy-preserving Cloud Computing
Xirong Ma
Chuan Li
Yuchang Hu
Yunting Tao
Yali Jiang
Yanbin Li
Fanyu Kong
Chunpeng Ge
262
0
0
28 Jun 2024
Homomorphic WiSARDs: Efficient Weightless Neural Network training over encrypted data
Leonardo Neumann
Antonio Guimarães
Diego F. Aranha
Edson Borin
AAML
163
0
0
29 Mar 2024
Taiyi: A high-performance CKKS accelerator for Practical Fully Homomorphic Encryption
Shengyu Fan
Xianglong Deng
Zhuoyu Tian
Zhicheng Hu
Liang Chang
Rui Hou
Dan Meng
Mingzhe Zhang
263
3
0
15 Mar 2024
I can't see it but I can Fine-tune it: On Encrypted Fine-tuning of Transformers using Fully Homomorphic Encryption
Prajwal Panzade
Daniel Takabi
Zhipeng Cai
121
3
0
14 Feb 2024
Neural Network Training on Encrypted Data with TFHE
Luis Montero
Jordan Fréry
Celia Kherfallah
Roman Bredehoft
Andrei Stoian
FedML
125
4
0
29 Jan 2024
GuardML: Efficient Privacy-Preserving Machine Learning Services Through Hybrid Homomorphic Encryption
ACM Symposium on Applied Computing (SAC), 2024
E. Frimpong
Khoa Nguyen
Mindaugas Budzys
Tanveer Khan
A. Michalas
169
29
0
26 Jan 2024
MedBlindTuner: Towards Privacy-preserving Fine-tuning on Biomedical Images with Transformers and Fully Homomorphic Encryption
Prajwal Panzade
Daniel Takabi
Zhipeng Cai
MedIm
179
4
0
17 Jan 2024
Practical, Private Assurance of the Value of Collaboration
Proceedings on Privacy Enhancing Technologies (PoPETs), 2023
Hassan Jameel Asghar
Zhigang Lu
Zhongrui Zhao
Dali Kaafar
FedML
240
0
0
04 Oct 2023
SABLE: Secure And Byzantine robust LEarning
Antoine Choffrut
R. Guerraoui
Rafael Pinot
Renaud Sirdey
John Stephan
Martin Zuber
AAML
381
2
0
11 Sep 2023
Data Privacy with Homomorphic Encryption in Neural Networks Training and Inference
International Symposium on Distributed Computing and Artificial Intelligence (DCAI), 2023
Ivone Amorim
Eva Maia
Pedro Barbosa
Isabel Praça
89
4
0
03 May 2023
CHEM: Efficient Secure Aggregation with Cached Homomorphic Encryption in Federated Machine Learning Systems
Dongfang Zhao
FedML
127
1
0
22 Dec 2022
Trustworthy Graph Neural Networks: Aspects, Methods and Trends
Proceedings of the IEEE (Proc. IEEE), 2022
He Zhang
Bang Wu
Lizhen Qu
Shirui Pan
Hanghang Tong
Jian Pei
373
150
0
16 May 2022
Protecting Data from all Parties: Combining FHE and DP in Federated Learning
Arnaud Grivet Sébert
Renaud Sirdey
Oana Stan
Cédric Gouy-Pailler
FedML
122
0
0
09 May 2022
FHEBench: Benchmarking Fully Homomorphic Encryption Schemes
Lei Jiang
Lei Ju
FedML
96
17
0
01 Mar 2022
Report: State of the Art Solutions for Privacy Preserving Machine Learning in the Medical Context
J. Zalonis
Frederik Armknecht
Björn Grohmann
Manuel Koch
186
4
0
27 Jan 2022
Privacy-Preserving Biometric Matching Using Homomorphic Encryption
Gaëtan Pradel
C. Mitchell
PICV
230
27
0
24 Nov 2021
A methodology for training homomorphicencryption friendly neural networks
Moran Baruch
Nir Drucker
L. Greenberg
Guy Moshkowich
216
17
0
05 Nov 2021
Privacy-Preserving Machine Learning: Methods, Challenges and Directions
Runhua Xu
Nathalie Baracaldo
J. Joshi
183
140
0
10 Aug 2021
Secure Quantized Training for Deep Learning
Marcel Keller
Ke Sun
MQ
221
76
0
01 Jul 2021
Adam in Private: Secure and Fast Training of Deep Neural Networks with Adaptive Moment Estimation
IACR Cryptology ePrint Archive (IACR ePrint), 2021
Nuttapong Attrapadung
Koki Hamada
Dai Ikarashi
Ryo Kikuchi
Takahiro Matsuda
Ibuki Mishina
Hiraku Morita
Jacob C. N. Schuldt
157
29
0
04 Jun 2021
Differential Privacy for Text Analytics via Natural Text Sanitization
Findings (Findings), 2021
Xiang Yue
Minxin Du
Tianhao Wang
Yaliang Li
Huan Sun
Sherman S. M. Chow
246
112
0
02 Jun 2021
SIRNN: A Math Library for Secure RNN Inference
IEEE Symposium on Security and Privacy (IEEE S&P), 2021
Deevashwer Rathee
Mayank Rathee
R. Goli
Divya Gupta
Rahul Sharma
Nishanth Chandran
Aseem Rastogi
154
139
0
10 May 2021
Practical Two-party Privacy-preserving Neural Network Based on Secret Sharing
ZhengQiang Ge
Zhipeng Zhou
Dong Guo
Qiang Li
FedML
117
7
0
10 Apr 2021
Accelerating 2PC-based ML with Limited Trusted Hardware
M. Nawaz
Aditya Gulati
Kunlong Liu
Vishwajeet Agrawal
P. Ananth
Trinabh Gupta
236
2
0
11 Sep 2020
SPEED: Secure, PrivatE, and Efficient Deep learning
Arnaud Grivet Sébert
Rafael Pinot
Martin Zuber
Cédric Gouy-Pailler
Renaud Sirdey
FedML
167
24
0
16 Jun 2020
Attacks on Image Encryption Schemes for Privacy-Preserving Deep Neural Networks
Alexander Chang
Benjamin M. Case
177
33
0
28 Apr 2020
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