On the importance of difficulty calibration in membership inference attacks

L Watson, C Guo, G Cormode… - arXiv preprint arXiv …, 2021 - arxiv.org
The vulnerability of machine learning models to membership inference attacks has received
much attention in recent years. However, existing attacks mostly remain impractical due to …
被引用次数：94 相关文章

On the Importance of Difficulty Calibration in Membership Inference Attacks

L Watson, C Guo, G Cormode… - … Conference on Learning … - openreview.net
The vulnerability of machine learning models to membership inference attacks has received
much attention in recent years. However, existing attacks mostly remain impractical due to …
[PDF] rutgers.edu

[PDF][PDF] ON THE IMPORTANCE OF DIFFICULTY CALIBRATION IN MEMBERSHIP INFERENCE ATTACKS

L Watson, C Guo, G Cormode, A Sablayrolles - archive.dimacs.rutgers.edu
The vulnerability of machine learning models to membership inference attacks has received
much attention in recent years. Existing attacks mostly remain impractical due to having high …

On the Importance of Difficulty Calibration in Membership Inference Attacks

L Watson, C Guo, G Cormode… - arXiv e-prints, 2021 - ui.adsabs.harvard.edu
The vulnerability of machine learning models to membership inference attacks has received
much attention in recent years. However, existing attacks mostly remain impractical due to …
[PDF] rutgers.edu

[PDF][PDF] ON THE IMPORTANCE OF DIFFICULTY CALIBRATION IN MEMBERSHIP INFERENCE ATTACKS

L Watson, C Guo, G Cormode, A Sablayrolles - dimacs.rutgers.edu
The vulnerability of machine learning models to membership inference attacks has received
much attention in recent years. Existing attacks mostly remain impractical due to having high …