Fetching the paper…
Reading the bibliography…
This work presents a novel protocol for fast secure inference of neural networks applied to computer vision applications.
Learning multiple layers of features from tiny images
Krizhevsky, A. 2009 · 2009
Earlier work this paper cites.
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Dosovitskiy, A.; Beyer, L.; Kolesnikov, A.; Weissenborn, D.; Zhai, X.; Unterthiner, T.; Dehghani, M.; Minderer, M.; Heigold, G.; Gelly, S.; Uszkoreit, J.; and Houlsby, N. 2021 · 2010
Earlier work this paper cites.
Unleashing the Tiger: Inference Attacks on Split Learning
Pasquini, D.; Ateniese, G.; and Bernaschi, M. 2020 · 2012
Earlier work this paper cites.
Deep Residual Learning for Image Recognition
He, K.; Zhang, X.; Ren, S.; and Sun, J. 2015 · 2015
Earlier work this paper cites.
Distilling the knowledge in a neural network
Hinton, G.; Vinyals, O.; and Dean, J. 2015 · 2015
Earlier work this paper cites.
Deep learning with differential privacy
Abadi, M.; Chu, A.; Goodfellow, I.; McMahan, H. B.; Mironov, I.; Talwar, K.; and Zhang, L. 2016 · 2016
Earlier work this paper cites.
Homomorphic Encryption for Arithmetic of Approximate Numbers , volume 10624 of Lecture Notes in Computer Science , 409–437
Cheon, J. H.; Kim, A.; Kim, M.; and Song, Y. 2017 · 2017
Earlier work this paper cites.
Membership inference attacks against machine learning models
Shokri, R.; Stronati, M.; Song, C.; and Shmatikov, V. 2017 · 2017
Earlier work this paper cites.
Gazelle: A Low Latency Framework for Secure Neural Network Inference
Juvekar, C.; Vaikuntanathan, V.; and Chandrakasan, A. 2018 · 2018
Earlier work this paper cites.
mia: A library for running membership inference attacks against ML models
Kulynych, B.; and Yaghini, M. 2018 · 2018
Cited alongside, same era.
Split learning for health: Distributed deep learning without sharing raw patient data
Vepakomma, P.; Gupta, O.; Swedish, T.; and Raskar, R. 2018 · 2018
Cited alongside, same era.
Privacy risk in machine learning: Analyzing the connection to overfitting
Yeom, S.; Giacomelli, I.; Fredrikson, M.; and Jha, S. 2018 · 2018
Cited alongside, same era.
Un handbook on privacy-preserving computation techniques
Group, B. D. U. G. W.; and others. 2019 · 2019
Cited alongside, same era.
Yu, F.; Wang, D.; Shelhamer, E.; and Darrell, T. 2019 · 2019
Cited alongside, same era.
Microsoft SEAL (release 3.6)
SEAL. 2020 · 2020
Later among the works it cites.
NoPeek: Information leakage reduction to share activations in distributed deep learning
Vepakomma, P.; Singh, A.; Gupta, O.; and Raskar, R. 2020 · 2020
Later among the works it cites.
TenSEAL: A library for encrypted tensor operations using homomorphic encryption
Benaissa, A.; Retiat, B.; Cebere, B.; and Belfedhal, A. E. 2021 · 2021
Later among the works it cites.
Intel HEXL: Accelerating Homomorphic Encryption with Intel AVX512-IFMA52
Boemer, F.; Kim, S.; Seifu, G.; de Souza, F. D. M.; and Gopal, V. 2021 · 2021
Later among the works it cites.
Programmable Bootstrapping Enables Efficient Homomorphic Inference of Deep Neural Networks
Chillotti, I.; Joye, M.; and Paillier, P. 2021 · 2021
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cryptanalytic Extraction of Neural Network Models
Carlini, N.; Jagielski, M.; and Mironov, I. 2020 · 2020
Cited alongside, same era.
TFHE: fast fully homomorphic encryption over the torus
Chillotti, I.; Gama, N.; Georgieva, M.; and Izabachène, M. 2020 · 2020
Cited alongside, same era.
Delphi: A cryptographic inference service for neural networks
Mishra, P.; Lehmkuhl, R.; Srinivasan, A.; Zheng, W.; and Popa, R. A. 2020 · 2020
Cited alongside, same era.
CrypTFlow2: Practical 2-Party Secure Inference
Rathee, D.; Rathee, M.; Kumar, N.; Chandran, N.; Gupta, D.; Rastogi, A.; and Sharma, R. 2020 · 2020
Cited alongside, same era.
Hall, A. J.; Jay, M.; Cebere, T.; Cebere, B.; van der Veen, K. L.; Muraru, G.; Xu, T.; Cason, P.; Abramson, W.; Benaissa, A.; Shah, C.; Aboudib, A.; Ryffel, T.; Prakash, K.; Titcombe, T.; Khare, V. K.; Shang, M.; Junior, I.; Gupta, A.; Paumier, J.; Kang, N.; Manannikov, V.; and Trask, A. 2021 · 2021
Later among the works it cites.
DISCO: Dynamic and Invariant Sensitive Channel Obfuscation for deep neural networks
Singh, A.; Chopra, A.; Garza, E.; Zhang, E.; Vepakomma, P.; Sharma, V.; and Raskar, R. 2021 · 2021
Later among the works it cites.
Systematic evaluation of privacy risks of machine learning models
Song, L.; and Mittal, P. 2021 · 2021
Later among the works it cites.
Data-Free Model Extraction
Truong, J.-B.; Maini, P.; Walls, R. J.; and Papernot, N. 2021 · 2021
Later among the works it cites.