Private Machine Learning in TensorFlow using Secure Computation

Secure computation with fixed-point numbers

Octavian Catrina and Amitabh Saxena · 2010

Earlier work this paper cites.

Multiparty Computation from Somewhat Homomorphic Encryption

Ivan Damgård, Valerio Pastro, Nigel P. Smart, and Sarah Zakarias · 2012

Earlier work this paper cites.

SecureML: A System for Scalable Privacy-Preserving Machine Learning

Payman Mohassel and Yupeng Zhang · 2017

Earlier work this paper cites.

Semi-supervised knowledge transfer for deep learning from private training data

Original

Nicolas Papernot, Martín Abadi, Ulfar Erlingsson, Ian Goodfellow, and Kunal Talwar · 2017

Cited alongside, same era.

Gazelle: A Low Latency Framework for Secure Neural Network Inference

Chiraag Juvekar, Vinod Vaikuntanathan, and Anantha Chandrakasan · 2018

Cited alongside, same era.

ABY3: A Mixed Protocol Framework for Machine Learning

Payman Mohassel and Peter Rindal · 2018

Cited alongside, same era.

TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems

Original

Martín Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Gregory S. Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Ian J. Goodfellow, Andrew Harp, Geoffrey Irving, Michael Isard, Yangqing Jia, Rafal Józefowicz, Lukasz Kaiser, Manjunath Kudlur, Josh Levenberg, Dan Mané, Rajat Monga, Sherry Moore, Derek Gordon Murray, Chris Olah, Mike Schuster, Jonathon Shlens, Benoit Steiner, Ilya Sutskever, Kunal Talwar, Paul A. Tucker, Vincent Vanhoucke, Vijay Vasudevan, Fernanda B. Viégas, Oriol Vinyals, Pete Warden, Martin Wattenberg, Martin Wicke, Yuan Yu, and Xiaoqiang Zheng

Cited in the paper.

TensorFlow: A System for Large-scale Machine Learning

Martín Abadi, Paul Barham, Jianmin Chen, Zhifeng Chen, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Geoffrey Irving, Michael Isard, Manjunath Kudlur, Josh Levenberg, Rajat Monga, Sherry Moore, Derek G. Murray, Benoit Steiner, Paul Tucker, Vijay Vasudevan, Pete Warden, Martin Wicke, Yuan Yu, and Xiaoqiang Zheng

Cited in the paper.

ABY - A Framework for Efficient Mixed-Protocol Secure Two-Party Computation

Daniel Demmler, Thomas Schneider, and Michael Zohner

Cited in the paper.

FRESCO: Framework for Efficient and Secure Computation

Peter Sebastian Nordholt, Kasper Damgård, Peter F. Frandsen, and Jonas Lindstrøm

Cited in the paper.

SCALE-MAMBA

Nigel P. Smart, Marcel Keller, Dragos Rotaru, and Peter Scholl

Cited in the paper.

PySyft: A library for encrypted, privacy preserving deep learning

Andrew Trask and OpenMined

Cited in the paper.

Obliv-C: A Language for Extensible Data-Oblivious Computation

Samee Zahur and David Evans

Cited in the paper.

Scalable Private Learning with PATE

Original

Nicolas Papernot, Shuang Song, Ilya Mironov, Ananth Raghunathan, Kunal Talwar, and Ulfar Erlingsson · 2018

Closest in time.

SecureNN: Efficient and Private Neural Network Training

Sameer Wagh, Divya Gupta, and Nishanth Chandran · 2018

Closest in time.