Protect privacy of deep classification networks by exploiting their generative power

DOI10.1007/s10994-021-05951-6OpenAlexW3156534051MaRDI QIDQ2051265

Qianjun Zheng, Jiyu Chen, Hao Chen, Yiwen Guo

Publication date: 24 November 2021

Published in: Machine Learning (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10994-021-05951-6

zbMATH Keywords

data privacydeep neural networksgenerative modelingmembership inference attack

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Related Items

meminf-defense ⋮ Parameter identifiability of a deep feedforward ReLU neural network

Uses Software

• CIFAR
• t-SNE
• GitHub

Cites Work

• Differential Privacy: A Survey of Results
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