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Gazelle: A Low Latency Framework for Secure Neural Network Inference

Gazelle: A Low Latency Framework for Secure Neural Network Inference

16 January 2018
Chiraag Juvekar
Vinod Vaikuntanathan
A. Chandrakasan
ArXiv (abs)PDFHTML

Papers citing "Gazelle: A Low Latency Framework for Secure Neural Network Inference"

15 / 15 papers shown
Title
Theoretical Insights in Model Inversion Robustness and Conditional Entropy Maximization for Collaborative Inference Systems
Theoretical Insights in Model Inversion Robustness and Conditional Entropy Maximization for Collaborative Inference Systems
Song Xia
Yi Yu
Wenhan Yang
Meiwen Ding
Zhuo Chen
Lingyu Duan
Alex C. Kot
Xudong Jiang
114
4
0
01 Mar 2025
SecPE: Secure Prompt Ensembling for Private and Robust Large Language Models
SecPE: Secure Prompt Ensembling for Private and Robust Large Language Models
Jiawen Zhang
Kejia Chen
Zunlei Feng
Jian Lou
Mingli Song
Qingbin Liu
Xiaoyu Yang
AAMLSILMFedML
158
1
0
02 Feb 2025
Flash: A Hybrid Private Inference Protocol for Deep CNNs with High Accuracy and Low Latency on CPU
Flash: A Hybrid Private Inference Protocol for Deep CNNs with High Accuracy and Low Latency on CPU
H. Roh
Jinsu Yeo
Yeongil Ko
Gu-Yeon Wei
David Brooks
Woo-Seok Choi
168
2
0
20 Jan 2025
DCT-CryptoNets: Scaling Private Inference in the Frequency Domain
DCT-CryptoNets: Scaling Private Inference in the Frequency Domain
Arjun Roy
Kaushik Roy
426
1
0
27 Aug 2024
Privacy-Preserving Logistic Regression Training on Large Datasets
Privacy-Preserving Logistic Regression Training on Large Datasets
John Chiang
122
2
0
19 Jun 2024
VeriSplit: Secure and Practical Offloading of Machine Learning Inferences across IoT Devices
VeriSplit: Secure and Practical Offloading of Machine Learning Inferences across IoT Devices
Han Zhang
Zifan Wang
Mihir Dhamankar
Matt Fredrikson
Yuvraj Agarwal
106
2
0
02 Jun 2024
Hyena: Optimizing Homomorphically Encrypted Convolution for Private CNN Inference
Hyena: Optimizing Homomorphically Encrypted Convolution for Private CNN Inference
H. Roh
Woo-Seok Choi
111
1
0
21 Nov 2023
Chameleon: A Hybrid Secure Computation Framework for Machine Learning
  Applications
Chameleon: A Hybrid Secure Computation Framework for Machine Learning Applications
M. Riazi
Christian Weinert
Oleksandr Tkachenko
Ebrahim M. Songhori
T. Schneider
F. Koushanfar
FedML
48
496
0
10 Jan 2018
DeepSecure: Scalable Provably-Secure Deep Learning
DeepSecure: Scalable Provably-Secure Deep Learning
B. Rouhani
M. Riazi
F. Koushanfar
FedML
54
415
0
24 May 2017
Efficient Processing of Deep Neural Networks: A Tutorial and Survey
Efficient Processing of Deep Neural Networks: A Tutorial and Survey
Vivienne Sze
Yu-hsin Chen
Tien-Ju Yang
J. Emer
AAML3DV
120
3,032
0
27 Mar 2017
Stealing Machine Learning Models via Prediction APIs
Stealing Machine Learning Models via Prediction APIs
Florian Tramèr
Fan Zhang
Ari Juels
Michael K. Reiter
Thomas Ristenpart
SILMMLAU
113
1,814
0
09 Sep 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.3K
194,774
0
10 Dec 2015
FaceNet: A Unified Embedding for Face Recognition and Clustering
FaceNet: A Unified Embedding for Face Recognition and Clustering
Florian Schroff
Dmitry Kalenichenko
James Philbin
3DH
393
13,180
0
12 Mar 2015
Going Deeper with Convolutions
Going Deeper with Convolutions
Christian Szegedy
Wei Liu
Yangqing Jia
P. Sermanet
Scott E. Reed
Dragomir Anguelov
D. Erhan
Vincent Vanhoucke
Andrew Rabinovich
509
43,732
0
17 Sep 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition
Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan
Andrew Zisserman
FAttMDE
1.7K
100,622
0
04 Sep 2014
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