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This paper studies model-inversion attacks, in which the access to a model is abused to infer information about the training data.
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Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2015
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Xiaosong Wang, Yifan Peng, Le Lu, Zhiyong Lu, Mohammadhadi Bagheri, and Ronald M Summers · 2017
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Semantic image inpainting with deep generative models
Raymond A Yeh, Chen Chen, Teck Yian Lim, Alexander G Schwing, Mark Hasegawa-Johnson, and Minh N Do · 2017
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Privacy risk in machine learning: Analyzing the connection to overfitting
Samuel Yeom, Irene Giacomelli, Matt Fredrikson, and Somesh Jha · 2018
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Xi Wu, Matthew Fredrikson, Somesh Jha, and Jeffrey F Naughton · 2016
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Model inversion attacks for prediction systems: Without knowledge of non-sensitive attributes
Seira Hidano, Takao Murakami, Shuichi Katsumata, Shinsaku Kiyomoto, and Goichiro Hanaoka · 2017
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Privacy in pharmacogenetics: An end-to-end case study of personalized warfarin dosing
Matthew Fredrikson, Eric Lantz, Somesh Jha, Simon Lin, David Page, and Thomas Ristenpart
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Adversarial neural network inversion via auxiliary knowledge alignment
Ziqi Yang, Ee-Chien Chang, and Zhenkai Liang · 2019
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