Reducing Risk of Model Inversion Using Privacy-Guided Training
Authors: Abigail Goldsteen, Gilad Ezov, Ariel Farkash | Published: 2020-06-29
Membership Inference
RayS: A Ray Searching Method for Hard-label Adversarial Attack
Authors: Jinghui Chen, Quanquan Gu | Published: 2020-06-23 | Updated: 2020-09-05
On Adversarial Bias and the Robustness of Fair Machine Learning
Authors: Hongyan Chang, Ta Duy Nguyen, Sasi Kumar Murakonda, Ehsan Kazemi, Reza Shokri | Published: 2020-06-15
Leakage of Dataset Properties in Multi-Party Machine Learning
Authors: Wanrong Zhang, Shruti Tople, Olga Ohrimenko | Published: 2020-06-12 | Updated: 2021-06-17
Trade-offs between membership privacy & adversarially robust learning
Authors: Jamie Hayes | Published: 2020-06-08 | Updated: 2022-01-08
Sponge Examples: Energy-Latency Attacks on Neural Networks
Authors: Ilia Shumailov, Yiren Zhao, Daniel Bates, Nicolas Papernot, Robert Mullins, Ross Anderson | Published: 2020-06-05 | Updated: 2021-05-12
An Overview of Privacy in Machine Learning
Authors: Emiliano De Cristofaro | Published: 2020-05-18
Perturbing Inputs to Prevent Model Stealing
Authors: Justin Grana | Published: 2020-05-12
When Machine Unlearning Jeopardizes Privacy
Authors: Min Chen, Zhikun Zhang, Tianhao Wang, Michael Backes, Mathias Humbert, Yang Zhang | Published: 2020-05-05 | Updated: 2021-09-14
Private Dataset Generation Using Privacy Preserving Collaborative Learning
Authors: Amit Chaulwar | Published: 2020-04-28