Privacy accounting $\varepsilon$conomics: Improving differential privacy composition via a posteriori bounds
Authors: Valentin Hartmann, Vincent Bindschaedler, Alexander Bentkamp, Robert West | Published: 2022-05-06 | Updated: 2023-06-19
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Sisyphus: A Cautionary Tale of Using Low-Degree Polynomial Activations in Privacy-Preserving Deep Learning
Authors: Karthik Garimella, Nandan Kumar Jha, Brandon Reagen | Published: 2021-07-26 | Updated: 2021-11-02
Exploiting Explanations for Model Inversion Attacks
Authors: Xuejun Zhao, Wencan Zhang, Xiaokui Xiao, Brian Y. Lim | Published: 2021-04-26 | Updated: 2022-03-14
Efficient Quantification of Profile Matching Risk in Social Networks
Authors: Anisa Halimi, Erman Ayday | Published: 2020-09-07
Tempered Sigmoid Activations for Deep Learning with Differential Privacy
Authors: Nicolas Papernot, Abhradeep Thakurta, Shuang Song, Steve Chien, Úlfar Erlingsson | Published: 2020-07-28
An Overview of Privacy in Machine Learning
Authors: Emiliano De Cristofaro | Published: 2020-05-18
On the (Un)Reliability of Privacy Policies in Android Apps
Authors: Luca Verderame, Davide Caputo, Andrea Romdhana, Alessio Merlo | Published: 2020-04-18
Partially Encrypted Machine Learning using Functional Encryption
Authors: Theo Ryffel, Edouard Dufour-Sans, Romain Gay, Francis Bach, David Pointcheval | Published: 2019-05-24 | Updated: 2021-09-23
Reconstruction of Privacy-Sensitive Data from Protected Templates
Authors: Shideh Rezaeifar, Behrooz Razeghi, Olga Taran, Taras Holotyak, Slava Voloshynovskiy | Published: 2019-05-08
Privacy-Preserving Deep Neural Networks with Pixel-based Image Encryption Considering Data Augmentation in the Encrypted Domain
Authors: Warit Sirichotedumrong, Takahiro Maekawa, Yuma Kinoshita, Hitoshi Kiya | Published: 2019-05-06