Added latest papers

README.md

@@ -84,6 +84,8 @@ This repository contains a curated list of papers related to privacy attacks aga
 - [**Node-Level Membership Inference Attacks Against Graph Neural Networks**](https://arxiv.org/abs/2102.05429) (He et al., 2021)
 - [**Practical Blind Membership Inference Attack via Differential Comparisons**](https://arxiv.org/abs/2101.01341) (Hui et al., 2021)
 - [**ADePT: Auto-encoder based Differentially Private Text Transformation**](https://arxiv.org/abs/2102.01502) (Krishna et al., 2021)
+- [**Membership Inference Attack Susceptibility of Clinical Language Models**](https://arxiv.org/abs/2104.08305) (Jagannatha et al., 2021)
+- [**Membership Inference Attacks on Knowledge Graphs**](https://arxiv.org/abs/2104.08273) (Wang & Sun, 2021)
 
 
 ## Reconstruction
@@ -134,7 +136,7 @@ Reconstruction attacks cover also attacks known as *model inversion* and *attrib
 - [**KART: Privacy Leakage Framework of Language Models Pre-trained with Clinical Records**](https://arxiv.org/abs/2101.00036) (Nakamura et al., 2020)
 - [**Derivation of Constraints from Machine Learning Models and Applications to Security and Privacy**](https://hal.archives-ouvertes.fr/hal-03091740/) (Falaschi et al., 2021)
 - [**On the (In)Feasibility of Attribute Inference Attacks on Machine Learning Models**](https://arxiv.org/abs/2103.07101) (Zhao et al., 2021)
-
+- [**Exploiting Explanations for Model Inversion Attacks**](https://arxiv.org/abs/2104.12669) (Zhao et al., 2021)
 
 ## 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)
@@ -143,6 +145,7 @@ Reconstruction attacks cover also attacks known as *model inversion* and *attrib
 - [**Overlearning Reveals Sensitive Attributes**](https://openreview.net/pdf?id=SJeNz04tDS) (Song C. et al., 2020) ([code](https://drive.google.com/file/d/1hu0PhN3pWXe6LobxiPFeYBm8L-vQX2zJ/view?usp=sharing))
 - [**Subject Property Inference Attack in Collaborative Learning**](https://ieeexplore.ieee.org/document/9204357) (Xu and Li, 2020)
 - [**Property Inference From Poisoning**](https://arxiv.org/abs/2101.11073) (Chase et al., 2021)
+- [**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)
 
 
 ## Model extraction
@@ -186,6 +189,7 @@ Reconstruction attacks cover also attacks known as *model inversion* and *attrib
 - [**Protecting Decision Boundary of Machine Learning Model With Differentially Private Perturbation**](https://ieeexplore.ieee.org/abstract/document/9286504) (Zheng et al., 2021)
 - [**Special-Purpose Model Extraction Attacks: Stealing Coarse Model with Fewer Queries**](https://ieeexplore.ieee.org/abstract/document/9343086?casa_token=Fn4CtwOZsbQAAAAA:4n3tZGcwFochwREqn4fRWcmA9YeLRxikwB1LN8t2ui1NbRPHSHjTuoqHrSfP1vxXfecw0kobBQ) (Okada et al., 2021)
 - [**Model Extraction and Adversarial Transferability, Your BERT is Vulnerable!**](https://arxiv.org/abs/2103.10013) (He et al., 2021) ([code](https://github.com/xlhex/extract_and_transfer))
+- [**Good Artists Copy, Great Artists Steal: Model Extraction Attacks Against Image Translation Generative Adversarial Networks**](https://arxiv.org/abs/2104.12623) (Szyller et al., 2021)
 
 
 # Other