From 154a881ce98b2e21fa4be3dc8dcd2adb9b8679f4 Mon Sep 17 00:00:00 2001 From: MariaRigaki Date: Thu, 28 Apr 2022 08:44:56 +0200 Subject: [PATCH] Fixed paper link to point to abstract --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 6feb401..cb79845 100755 --- a/README.md +++ b/README.md @@ -175,7 +175,7 @@ Reconstruction attacks cover also attacks known as *model inversion* and *attrib - [**Property Inference Attacks on Convolutional Neural Networks: Influence and Implications of Target Model's Complexity**](https://arxiv.org/abs/2104.13061) (Parisot et al., 2021) - [**Honest-but-Curious Nets: Sensitive Attributes of Private Inputs can be Secretly Coded into the Entropy of Classifiers' Outputs**](https://arxiv.org/abs/2105.12049) (Malekzadeh et al. 2021) ([code](https://github.com/mmalekzadeh/honest-but-curious-nets)) - [**Property Inference Attacks Against GANs**](https://arxiv.org/abs/2111.07608) (Zhou et al., 2021) ([code](https://github.com/Zhou-Junhao/PIA_GAN)) -- [**Formalizing and Estimating Distribution Inference Risks**](https://arxiv.org/pdf/2109.06024.pdf) (Suri et al., 2022) ([code](https://github.com/iamgroot42/FormEstDistRisks)) +- [**Formalizing and Estimating Distribution Inference Risks**](https://arxiv.org/abs/2109.06024) (Suri et al., 2022) ([code](https://github.com/iamgroot42/FormEstDistRisks)) ## Model extraction