QUOTIENT: Two-Party Secure Neural Network Training and Prediction
Authors: Nitin Agrawal, Ali Shahin Shamsabadi, Matt J. Kusner, Adrià Gascón | Published: 2019-07-08
Privacy Protection
Diffprivlib: The IBM Differential Privacy Library
Authors: Naoise Holohan, Stefano Braghin, Pól Mac Aonghusa, Killian Levacher | Published: 2019-07-04
Capacity Bounded Differential Privacy
Authors: Kamalika Chaudhuri, Jacob Imola, Ashwin Machanavajjhala | Published: 2019-07-03
Protecting Privacy of Users in Brain-Computer Interface Applications
Authors: Anisha Agarwal, Rafael Dowsley, Nicholas D. McKinney, Dongrui Wu, Chin-Teng Lin, Martine De Cock, Anderson C. A. Nascimento | Published: 2019-07-02
DP-LSSGD: A Stochastic Optimization Method to Lift the Utility in Privacy-Preserving ERM
Authors: Bao Wang, Quanquan Gu, March Boedihardjo, Farzin Barekat, Stanley J. Osher | Published: 2019-06-28 | Updated: 2019-12-07
Secure Summation via Subset Sums: A New Primitive for Privacy-Preserving Distributed Machine Learning
Authors: Valentin Hartmann, Robert West | Published: 2019-06-27 | Updated: 2023-06-19
Stolen Memories: Leveraging Model Memorization for Calibrated White-Box Membership Inference
Authors: Klas Leino, Matt Fredrikson | Published: 2019-06-27 | Updated: 2020-06-24
The Cost of a Reductions Approach to Private Fair Optimization
Authors: Daniel Alabi | Published: 2019-06-23 | Updated: 2021-05-23
Deep Leakage from Gradients
Authors: Ligeng Zhu, Zhijian Liu, Song Han | Published: 2019-06-21 | Updated: 2019-12-19
Scalable and Differentially Private Distributed Aggregation in the Shuffled Model
Authors: Badih Ghazi, Rasmus Pagh, Ameya Velingker | Published: 2019-06-19 | Updated: 2019-12-02