From 8d64c8d5722167d34008a5006487916e29026329 Mon Sep 17 00:00:00 2001 From: Suha Sabi Hussain Date: Tue, 15 Sep 2020 15:33:32 -0400 Subject: [PATCH] Add more papers --- README.md | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/README.md b/README.md index 4615f57..9fe12b9 100644 --- a/README.md +++ b/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)