Merge branch 'master' into master

README.md

@@ -85,6 +85,8 @@ This repository contains a curated list of papers related to privacy attacks aga
 - [**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)
 - [**The Influence of Dropout on Membership Inference in Differentially Private Models**](https://arxiv.org/abs/2103.09008) (Galinkin, 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
@@ -130,6 +132,7 @@ Reconstruction attacks cover also attacks known as *model inversion* and *attrib
 - [**MixCon: Adjusting the Separability of Data Representations for Harder Data Recovery**](https://arxiv.org/abs/2010.11463) (Li et al., 2020)
 - [**Evaluation of Inference Attack Models for Deep Learning on Medical Data**](https://arxiv.org/abs/2011.00177) (Wu et al., 2020)
 - [**FaceLeaks: Inference Attacks against Transfer Learning Models via Black-box Queries**](https://arxiv.org/abs/2010.14023) (Liew and Takahashi, 2020)
+- [**Extracting Training Data from Large Language Models**](https://arxiv.org/abs/2012.07805) (Carlini et al., 2020)
 - [**MIDAS: Model Inversion Defenses Using an Approximate Memory System**](https://ieeexplore.ieee.org/abstract/document/9358254) (Xu et al., 2021)
 - [**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)
@@ -181,11 +184,10 @@ Reconstruction attacks cover also attacks known as *model inversion* and *attrib
 - [**ES Attack: Model Stealing against Deep Neural Networks without Data Hurdles**](https://arxiv.org/abs/2009.09560) (Yuan et al., 2020)
 - [**Black-Box Ripper: Copying black-box models using generative evolutionary algorithms**](https://arxiv.org/abs/2010.11158) (Barbalau et al., 2020) ([code](https://github.com/antoniobarbalau/black-box-ripper))
 - [**Model Extraction Attacks on Graph Neural Networks: Taxonomy and Realization**](https://arxiv.org/abs/2010.12751) (Wu et al., 2020) 
-- [**Extracting Training Data from Large Language Models**](https://arxiv.org/abs/2012.07805) (Carlini et al., 2020)
 - [**Model Extraction Attacks and Defenses on Cloud-Based Machine Learning Models**](https://ieeexplore.ieee.org/abstract/document/9311938?casa_token=f_8Lg24vAQkAAAAA:A7P5ym7bTLFIJZtL2yGorscyQC2R1WGJUKzcO-pn8wADHus0w8NArN-nv0JFcKYhwwQFeCaptQ) (Gong et al., 2020)
 - [**Leveraging Extracted Model Adversaries for Improved Black Box Attacks**](https://arxiv.org/abs/2010.16336) (Nizar and Kobren, 2020)
 - [**Differentially Private Machine Learning Model against Model Extraction Attack**](https://ieeexplore.ieee.org/abstract/document/9291542) (Cheng et al., 2020)
-- - [**Model Extraction Attacks and Defenses on Cloud-Based Machine Learning Models**](https://ieeexplore.ieee.org/abstract/document/9311938?casa_token=YP1PeB4XPqEAAAAA:q1Ni88642UTpBQ8r7jUe9tbWjMWG9lw3v8CK4g1q7V-ZShK0KonYuMiapY4rXDfKVNST6xLtSw) (Gong et al., 2020)
+- [**Model Extraction Attacks and Defenses on Cloud-Based Machine Learning Models**](https://ieeexplore.ieee.org/abstract/document/9311938?casa_token=YP1PeB4XPqEAAAAA:q1Ni88642UTpBQ8r7jUe9tbWjMWG9lw3v8CK4g1q7V-ZShK0KonYuMiapY4rXDfKVNST6xLtSw) (Gong et al., 2020)
 - [**Stealing Neural Network Models through the Scan Chain: A New Threat for ML Hardware**](https://eprint.iacr.org/2021/167) (Potluri and Aysu, 2021)
 - [**Model Extraction and Defenses on Generative Adversarial Networks**](https://arxiv.org/abs/2101.02069) (Hu and Pang, 2021)
 - [**Protecting Decision Boundary of Machine Learning Model With Differentially Private Perturbation**](https://ieeexplore.ieee.org/abstract/document/9286504) (Zheng et al., 2021)
@@ -198,6 +200,7 @@ Reconstruction attacks cover also attacks known as *model inversion* and *attrib
 - [**Deep Neural Network Fingerprinting by Conferrable Adversarial Examples**](https://arxiv.org/abs/1912.00888) (Lukas et al., 2021)
 - [**BODAME: Bilevel Optimization for Defense Against Model Extraction**](https://arxiv.org/abs/2103.06797) (Mori et al., 2021)
 - [**Dataset Inference: Ownership Resolution in Machine Learning**](https://openreview.net/forum?id=hvdKKV2yt7T) (Maini et al., 2021)
+- [**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