Label-Only Membership Inference Attacks
Authors: Christopher A. Choquette-Choo, Florian Tramer, Nicholas Carlini, Nicolas Papernot | Published: 2020-07-28 | Updated: 2021-12-05
Membership Inference
How Does Data Augmentation Affect Privacy in Machine Learning?
Authors: Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu | Published: 2020-07-21 | Updated: 2021-02-26
Sharing Models or Coresets: A Study based on Membership Inference Attack
Authors: Hanlin Lu, Changchang Liu, Ting He, Shiqiang Wang, Kevin S. Chan | Published: 2020-07-06
Robust and Accurate Authorship Attribution via Program Normalization
Authors: Yizhen Wang, Mohannad Alhanahnah, Ke Wang, Mihai Christodorescu, Somesh Jha | Published: 2020-07-01 | Updated: 2022-02-25
Reducing Risk of Model Inversion Using Privacy-Guided Training
Authors: Abigail Goldsteen, Gilad Ezov, Ariel Farkash | Published: 2020-06-29
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