Rethinking Privacy Preserving Deep Learning: How to Evaluate and Thwart Privacy Attacks

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Cynthia Dwork · 2006

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Cynthia Dwork, Frank McSherry, Kobbi Nissim, and Adam Smith · 2006

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Model inversion attacks that exploit confidence information and basic countermeasures

Matt Fredrikson, Somesh Jha, and Thomas Ristenpart · 2015

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Privacy-preserving deep learning

Reza Shokri and Vitaly Shmatikov · 2015

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Deep learning with differential privacy

Martin Abadi, Andy Chu, Ian Goodfellow, H Brendan McMahan, Ilya Mironov, Kunal Talwar, and Li Zhang · 2016

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Ran Gilad-Bachrach, Nathan Dowlin, Kim Laine, Kristin Lauter, Michael Naehrig, and John Wernsing · 2016

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Privacy-preserving deep learning via additively homomorphic encryption

Yoshinori Aono, Takuya Hayashi, Lihua Wang, Shiho Moriai, et al · 2017

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Exposed! a survey of attacks on private data

Cynthia Dwork, Adam Smith, Thomas Steinke, and Jonathan Ullman · 2017

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Private federated learning on vertically partitioned data via entity resolution and additively homomorphic encryption

Original

Stephen Hardy, Wilko Henecka, Hamish Ivey-Law, Richard Nock, Giorgio Patrini, Guillaume Smith, and Brian Thorne · 2017

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Communication-efficient learning of deep networks from decentralized data

H. Brendan McMahan, Eider Moore, Daniel Ramage, Seth Hampson, and Blaise Aguera y Arcas · 2017

Cited alongside, same era.

Membership inference attacks against machine learning models

Reza Shokri, Marco Stronati, Congzheng Song, and Vitaly Shmatikov · 2017

Cited alongside, same era.

The alexnet moment for homomorphic encryption: Hcnn, the first homomorphic CNN on encrypted data with gpus

Original

Ahmad Al Badawi, Jin Chao, Jie Lin, Chan Fook Mun, Sim Jun Jie, Benjamin Hong Meng Tan, Xiao Nan, Khin Mi Mi Aung, and Vijay Ramaseshan Chandrasekhar · 2018

Exploiting unintended feature leakage in collaborative learning

Luca Melis, Congzheng Song, Emiliano De Cristofaro, and Vitaly Shmatikov · 2019

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A survey on deep learning techniques for privacy-preserving

Harry Chandra Tanuwidjaja, Rakyong Choi, and Kwangjo Kim · 2019

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Beyond inferring class representatives: User-level privacy leakage from federated learning

Zhibo Wang, Mengkai Song, Zhifei Zhang, Yang Song, Qian Wang, and Hairong Qi · 2019

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Federated machine learning: Concept and applications

Qiang Yang, Yang Liu, Tianjian Chen, and Yongxin Tong · 2019

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Deep leakage from gradients

Original

Ligeng Zhu, Zhijian Liu, and Song Han · 2019

Later among the works it cites.