Add more papers

README.md

@@ -58,6 +58,9 @@ This repository contains a curated list of papers related to privacy attacks aga
 - [**Differential Privacy Defenses and Sampling Attacks for Membership Inference**](https://priml-workshop.github.io/priml2019/papers/PriML2019_paper_47.pdf) (Rahimian et al., 2019)
 - [**privGAN: Protecting GANs from membership inference attacks at low cost**](https://arxiv.org/abs/2001.00071) (Mukherjee et al., 2020)
 - [**Sharing Models or Coresets: A Study based on Membership Inference Attack**](https://arxiv.org/abs/2007.02977) (Lu et al., 2020)
+- [**Privacy Analysis of Deep Learning in the Wild: Membership Inference Attacks against Transfer Learning**](https://arxiv.org/abs/2009.04872) (Zou et al., 2020)
+- [**Quantifying Membership Inference Vulnerability via Generalization Gap and Other Model Metrics**](https://arxiv.org/abs/2009.05669) (Bentley et al., 2020)
+- [**MACE: A Flexible Framework for Membership Privacy Estimation in Generative Models**](https://arxiv.org/abs/2009.05683) (Liu et al., 2020)
 
 ## Reconstruction
 Reconstruction attacks cover also attacks known as *model inversion* and *attribute inference*.
@@ -93,6 +96,7 @@ Reconstruction attacks cover also attacks known as *model inversion* and *attrib
 - [**Robust Transparency Against Model Inversion Attacks**](https://ieeexplore.ieee.org/abstract/document/9178452) (Alufaisan et al., 2020)
 - [**Does AI Remember? Neural Networks and the Right to be Forgotten**](https://uwspace.uwaterloo.ca/handle/10012/15754) (Graves et al., 2020)
 - [**Improving Robustness to Model Inversion Attacks via Mutual Information Regularization**](https://arxiv.org/abs/2009.05241) (Wang et al., 2020)
+- [**SAPAG: A Self-Adaptive Privacy Attack From Gradients**](https://arxiv.org/abs/2009.06228) (Wang et al., 2020)
 
 ## Property inference
 - [**Hacking smart machines with smarter ones: How to extract meaningful data from machine learning classifiers**](https://dl.acm.org/doi/10.1504/IJSN.2015.071829) (Ateniese et al., 2015)