Membership Inference Attacks and Defenses on Machine Learning Models Literature
A curated list of membership inference attacks and defenses papers on machine learning models.
Papers are sorted by their released dates in descending order.
This repository serves as a complement to the survey below.
Membership Inference Attacks on Machine Learning: A Survey (More than 100 papers reviewed).
@article{hu2022membership,
title={Membership inference attacks on machine learning: A survey},
author={Hu, Hongsheng and Salcic, Zoran and Sun, Lichao and Dobbie, Gillian and Yu, Philip S and Zhang, Xuyun},
journal={ACM Computing Surveys (CSUR)},
volume={54},
number={11s},
pages={1--37},
year={2022},
publisher={ACM New York, NY}
}
If you feel this repository is helpful, please cite the survey above.
How to Search?
Search keywords like conference name (e.g., CCS), adversarial knowledge (e.g., Black-box), or target model (e.g., Classification Model) over the webpage to quickly locate related papers.
Quick Links
Attack papers sorted by year: | 2024 |2023 |2022 |2021 | 2020 | 2019 | 2018 | 2017 |
Defense papers sorted by year: | 2023 |2022 | 2021 | 2020 | 2019 | 2018 |
Membership Inference Attack
Attack Papers 2024
| Year |
Title |
Adversarial Knowledge |
Target Model |
Venue |
Paper Link |
Code Link |
| 2024 |
Uncertainty, Calibration, and Membership Inference Attacks: An Information-Theoretic Perspective |
Black-box |
Classification Models |
Arxiv |
Link |
|
| 2024 |
Do Membership Inference Attacks Work on Large Language Models? |
Black-box |
LLM |
Arxiv |
Link |
Link |
| 2024 |
Learning-Based Difficulty Calibration for Enhanced Membership Inference Attacks |
Black-box |
Classification Models |
Arxiv |
Link |
Link |
| 2024 |
Scalable Membership Inference Attacks via Quantile Regression |
Black-box |
Classification Models |
NeurIPS |
Link |
Link |
Attack Papers 2023
| Year |
Title |
Adversarial Knowledge |
Target Model |
Venue |
Paper Link |
Code Link |
| 2023 |
Link Membership Inference Attacks against Unsupervised Graph Representation Learning |
White-box/Black-box |
Graph Embedding Models |
ACSAC |
Link |
Link |
| 2023 |
Low-Cost High-Power Membership Inference by Boosting Relativity |
Black-box |
Classification Models |
Arxiv |
Link |
Link |
| 2023 |
Practical Membership Inference Attacks against Fine-tuned Large Language Models via Self-prompt Calibration |
Black-box |
Language Models |
Arxiv |
Link |
|
| 2023 |
A Probabilistic Fluctuation based Membership Inference Attack for Diffusion Models |
Black-box |
Generative Models |
Arxiv |
Link |
|
| 2023 |
Practical Membership Inference Attacks Against Large-Scale Multi-Modal Models: A Pilot Study |
Black-box |
Classification Models |
ICCV |
Link |
Link |
| 2023 |
Privacy Side Channels in Machine Learning Systems |
Black-box |
Classification Models |
Arxiv |
Link |
|
| 2023 |
White-box Membership Inference Attacks against Diffusion Models |
White-box |
Generative Models |
Arxiv |
Link |
Link |
| 2023 |
Scalable Membership Inference Attacks via Quantile Regression |
Black-box |
Classification Models |
Arxiv |
Link |
|
| 2023 |
Synthetic is all you need: removing the auxiliary data assumption for membership inference attacks against synthetic data |
Black-box |
Classification Models |
Arxiv |
Link |
|
| 2023 |
Towards More Realistic Membership Inference Attacks on Large Diffusion Models |
Black-box |
Generative Models |
Arxiv |
Link |
|
| 2023 |
Fortifying Federated Learning against Membership Inference Attacks via Client-level Input Perturbation |
White-box |
Classification Models |
Arxiv |
Link |
|
| 2023 |
Gaussian Membership Inference Privacy |
White-box |
Classification Models |
NeurIPS |
Link |
Link |
| 2023 |
TMI! Finetuned Models Leak Private Information from their Pretraining Data |
Black-box |
Classification Models |
Arxiv |
Link |
|
| 2023 |
SoK: Membership Inference is Harder Than Previously Thought |
Black-box |
Classification Models |
Arxiv |
Link |
Link |
| 2023 |
Re-aligning Shadow Models can Improve White-box Membership Inference Attacks |
White-box |
Classification Models |
Arxiv |
Link |
|
| 2023 |
Membership inference attack with relative decision boundary distance |
Black-box |
Classification Models |
Arxiv |
Link |
|
| 2023 |
Membership Inference Attacks against Language Models via Neighbourhood Comparison |
Black-box |
Classification Models |
Arxiv |
Link |
|
| 2023 |
How to Combine Membership-Inference Attacks on Multiple Updated Machine Learning Models |
Black-box |
Classification Models |
PoPETs |
Link |
Link |
| 2023 |
AgrEvader: Poisoning Membership Inference against Byzantine-robust Federated Learning |
White-box |
Classification Models |
WWW |
Link |
Link |
| 2023 |
Membership Inference Attacks Against Sequential Recommender Systems |
Black-box |
Recommender System |
WWW |
Link |
|
| 2023 |
A Blessing of Dimensionality in Membership Inference through Regularization |
Black-box |
Classification Models |
AISTATS |
Link |
Link |
| 2023 |
Active Membership Inference Attack under Local Differential Privacy in Federated Learning |
White-box |
Classification Models |
AISTATS |
Link |
Link |
| 2023 |
Membership Inference Attacks against Synthetic Data through Overfitting Detection |
Black-box |
Generative models |
AISTATS |
Link |
Link |
| 2023 |
Students Parrot Their Teachers: Membership Inference on Model Distillation |
Black-box |
Classification Models |
Arxiv |
Link |
|
| 2023 |
Membership Inference Attacks against Diffusion Models |
White-box; Black-box |
Generative Models |
Arxiv |
Link |
|
| 2023 |
Interaction-level Membership Inference Attack Against Federated Recommender Systems |
White-box |
Recommender System |
WWW |
Link |
|
| 2023 |
Are Diffusion Models Vulnerable to Membership Inference Attacks? |
Black-box |
Generative Models |
Arxiv |
Link |
|
| 2023 |
Accuracy-Privacy Trade-off in Deep Ensemble: A Membership Inference Perspective |
Black-box |
Classification Models |
S&P |
Link |
Link |
| 2023 |
Membership Inference of Diffusion Models |
Black-box |
Generative Models |
Arxiv |
Link |
|
| 2023 |
MiDA: Membership inference attacks against domain adaptation |
Black-box |
Classification Models |
ISA Transactions |
Link |
|
Attack Papers 2022
| Year |
Title |
Adversarial Knowledge |
Target Model |
Venue |
Paper Link |
Code Link |
| 2022 |
On the Discredibility of Membership Inference Attacks |
Black-box |
Classification Models |
Arxiv |
Link |
|
| 2022 |
Membership Inference Attacks Against Semantic Segmentation Models |
Black-box |
Semantic Segmentation Models |
Arxiv |
Link |
Link |
| 2022 |
Similarity Distribution based Membership Inference Attack on Person Re-identification |
Black-box |
Person Re-identification |
AAAI |
Link |
|
| 2022 |
Amplifying Membership Exposure via Data Poisoning |
Black-box |
Classification Models |
NeurIPS |
Link |
Link |
| 2022 |
Canary in a Coalmine: Better Membership Inference with Ensembled Adversarial Queries |
Black-box |
Classification Models |
Arxiv |
Link |
Link |
| 2022 |
Membership Inference Attacks Against Text-to-image Generation Models |
Black-box |
Text-to-image Models |
Arxiv |
Link |
|
| 2022 |
Membership Inference Attacks Against Robust Graph Neural Network |
Black-box |
Classification Models |
CSS |
Link |
|
| 2022 |
No-Label User-Level Membership Inference for ASR Model Auditing |
Balck-box |
Automatic Speech Recognition Model |
ESORICS |
Link |
|
| 2022 |
Membership Inference Attacks and Generalization: A Causal Perspective |
Black-box; White-box |
Classification Models |
CCS |
Link |
|
| 2022 |
M^4I: Multi-modal Models Membership Inference |
Black-box |
Multi-modal Models |
NeurIPS |
Link |
Link |
| 2022 |
Membership Inference Attacks by Exploiting Loss Trajectory |
Black-box |
Classification Models |
CCS |
Link |
Link |
| 2022 |
Auditing Membership Leakages of Multi-Exit Networks |
White-box; Black-box |
Classification Models |
CCS |
Link |
Link |
| 2022 |
Label-Only Membership Inference Attack against Node-Level Graph Neural Networks |
Black-box |
Classification Models |
Arxiv |
Link |
|
| 2022 |
Membership-Doctor: Comprehensive Assessment of Membership Inference Against Machine Learning Models |
Black-box |
Classification Models |
Arxiv |
Link |
|
| 2022 |
On the Privacy Effect of Data Enhancement via the Lens of Memorization |
Black-box |
Classification Models |
Arxiv |
Link |
|
| 2022 |
Membership Inference Attacks via Adversarial Examples |
White-box |
Classification Models |
Arxiv |
Link |
|
| 2022 |
Label-Only Membership Inference Attack against Node-Level Graph Neural Networks |
Black-box |
Classification Models |
Arxiv |
Link |
|
| 2022 |
Semi-Leak: Membership Inference Attacks Against Semi-supervised Learning |
Black-box |
Semi-supervised Learning Models |
ECCV |
Link |
Link |
| 2022 |
Debiasing Learning for Membership Inference Attacks Against Recommender Systems |
Black-box |
Recommender System |
KDD |
Link |
|
| 2022 |
Membership Inference via Backdooring |
Black-box |
Classification Models |
IJCAI |
Link |
Link |
| 2022 |
Membership Inference Attacks Against Machine Learning Models via Prediction Sensitivity |
Black-box |
Classification Models |
IEEE Trans Dependable Secure Comput |
Link |
Link |
| 2022 |
Subject Membership Inference Attacks in Federated Learning |
White-box |
Classification Models |
Arxiv |
Link |
|
| 2022 |
Membership Feature Disentanglement Network |
White-box |
Classification Models |
ASIA CCS |
Link |
|
| 2022 |
Understanding Disparate Effects of Membership Inference Attacks and their Countermeasures |
Black-box |
Classification Models |
ASIA CCS |
Link |
|
| 2022 |
l-Leaks:Membership Inference Attacks with Logits |
Black-box |
Classification Models |
Arxiv |
Link |
|
| 2022 |
CS-MIA: Membership inference attack based on prediction confidence series in federated learning |
White-box |
Classification Models |
J. Inf. Secur. Appl |
Link |
|
| 2022 |
Evaluating Membership Inference Through Adversarial Robustnes |
White-box |
Classfication Models |
The Computer Journal |
Link |
Link |
| 2022 |
How to Combine Membership-Inference Attacks on Multiple Updated Models |
Black-box |
Classification Models |
Arxiv |
Link |
Link |
| 2022 |
An Efficient Subpopulation-based Membership Inference Attack |
Black-box |
Classification Models |
Arxiv |
Link |
|
| 2022 |
Assessing the Impact of Membership Inference Attacks on Classical Machine Learning Algorithms |
Black-box |
Classification Models |
DRCN |
Link |
Link |
| 2022 |
Optimal Membership Inference Bounds for Adaptive Composition of Sampled Gaussian Mechanisms |
White-box; Black-box |
Classification Models |
Arxiv |
Link |
|
| 2022 |
Perfectly Accurate Membership Inference by a Dishonest Central Server in Federated Learning |
White-box |
Classification Models |
Arxiv |
Link |
Link |
| 2022 |
Leveraging Adversarial Examples to Quantify Membership Information Leakage |
White-box; Black-box |
Classification Models |
CVPR |
Link |
Link |
| 2022 |
Quantifying Privacy Risks of Masked Language Models Using Membership Inference Attacks |
Black-box |
Masked Language Models |
Arxiv |
Link |
|
| 2022 |
User-Level Membership Inference Attack against Metric Embedding Learning |
Black-box |
Metric Embedding Models |
Arxiv |
Link |
|
| 2022 |
Label-Only Membership Inference Attacks and Defenses In Semantic Segmentation Models |
Black-box |
Segmentation Models |
IEEE Trans Dependable Secure Comput |
Link |
|
| 2022 |
Membership Inference Attacks and Defenses in Neural Network Pruning |
Black-box |
Classification Models |
USENIX Security |
Link |
Link |
| 2022 |
Parameters or Privacy: A Provable Tradeoff Between Overparameterization and Membership Inference |
Black-box |
Regression Models |
Arxiv |
Link |
|
| 2022 |
LTU Attacker for Membership Inference |
White-box; Black-box |
Classification Models |
AAAI Workshop |
Link |
Link |
Attack Papers 2021
| Year |
Title |
Adversarial Knowledge |
Target Model |
Venue |
Paper Link |
Code Link |
| 2021 |
Membership Inference Attacks From First Principles |
White-box; Black-box |
Classification Models |
Arxiv |
Link |
|
| 2021 |
SHAPr: An Efficient and Versatile Membership Privacy Risk Metric for Machine Learning |
Black-box |
Classification Models |
Arxiv |
Link |
|
| 2021 |
Enhanced Membership Inference Attacks against Machine Learning Models |
Black-box |
Classification Models |
Arxiv |
Link |
Link |
| 2021 |
Do Not Trust Prediction Scores for Membership Inference Attacks |
Black-box |
Classification Models |
IJCAI |
Link |
Link |
| 2021 |
On the Importance of Difficulty Calibration in Membership Inference Attacks |
White-box |
Classification Models |
Arxiv |
Link |
|
| 2021 |
Membership Inference Attacks against GANs by Leveraging Over-representation Regions |
White-box |
Generative Models |
CCS |
Link |
|
| 2021 |
Membership Inference Attacks Against Recommender Systems |
Black-box |
Recommender Systems |
CCS |
Link |
Link |
| 2021 |
Source Inference Attacks in Federated Learning |
Black-box |
Classifcation Models |
ICDM |
Link |
Link |
| 2021 |
Adapting Membership Inference Attacks to GNN for Graph Classification: Approaches and Implications |
Black-box |
Classification Models |
ICDM |
Link |
Link |
| 2021 |
On The Vulnerability of Recurrent Neural Networks to Membership Inference Attacks |
Black-box |
Text Generation Models |
Arxiv |
Link |
Link |
| 2021 |
On the Difficulty of Membership Inference Attacks |
White-box |
Classification Models |
CVPR |
Link |
Link |
| 2021 |
Quantifying Privacy Leakage in Graph Embedding |
White-box; Black-box |
Graph Embedding Models |
NeurIPS Workshop |
Link |
Link |
| 2021 |
Label-only membership inference attacks |
Black-box |
Classification Models |
ICML |
Link |
Link |
| 2021 |
On the Privacy Risks of Model Explanations |
Black-box |
Classification Models |
AIES |
Link |
|
| 2021 |
Systematic evaluation of privacy risks of machine learning models |
White-box; Black-box |
Classification Models |
USENIX Security |
Link |
Link |
| 2021 |
Practical blind membership inference attack via differential comparisons |
Black-box |
Classification Models |
NDSS |
Link |
Link |
| 2021 |
On the (In) Feasibility of Attribute Inference Attacks on Machine Learning Models |
White-box; Black-box |
Classification Models |
EuroS&P |
Link |
|
| 2021 |
Bounding Information Leakage in Machine Learning |
White-box |
Classification Models |
Arxiv |
Link |
|
| 2021 |
How Does Data Augmentation Affect Privacy in Machine Learning? |
Black-box |
Classification Models |
AAAI |
Link |
Link |
| 2021 |
Node-Level Membership Inference Attacks Against Graph Neural Networks |
Black-box |
Classification Models |
Arxiv |
Link |
|
| 2021 |
The Audio Auditor: User-Level Membership Inference in Internet of Things Voice Services |
Black-box |
Automatic Speech Recognition Model |
PoPETs |
Link |
|
| 2021 |
Reconstruction-Based Membership Inference Attacks are Easier on Difficult Problems |
Black-box |
Image Translation Models; Image Segmentation Models |
ICCV |
Link |
Link |
| 2021 |
This Person (Probably) Exists. Identity Membership Attacks Against GAN Generated Faces |
Black-box |
Generative Models |
Arxiv |
link |
|
| 2021 |
Membership Inference Attack Susceptibility of Clinical Language Models |
White-box; Black-box |
Clinical Language Models |
Arxiv |
Link |
|
| 2021 |
Killing four birds with one Gaussian process: the relation between different test-time attacks |
Black-box |
Classification Models |
ICPR |
Link |
|
| 2021 |
Evaluating the Vulnerability of End-to-End Automatic Speech Recognition Models To Membership Inference Attacks |
Black-box |
Speech Recognition Models |
Interspeech |
Link |
|
| 2021 |
Membership Inference Attacks on Knowledge Graphs |
Black-box |
Knowledge Graph Embedding Models |
Arxiv |
Link |
|
| 2021 |
Membership Leakage in Label-Only Exposures |
Black-box |
Classification Models |
CCS |
Link |
|
| 2021 |
Membership inference attack on graph neural networks |
Black-box |
Classification Models |
Arxiv |
Link |
|
| 2021 |
Membership Inference Attacks on Deep Regression Models for Neuroimaging |
Black-box |
Regression Models |
MIDL |
Link |
|
| 2021 |
Membership Inference Attacks on Lottery Ticket Networks |
Black-box |
Classification Models |
ICML Workshop |
Link |
|
| 2021 |
Membership Inference on Word Embedding and Beyond |
Black-box |
Word Embedding Models |
Arxiv |
Link |
|
| 2021 |
EncoderMI: Membership Inference against Pre-trained Encoders in Contrastive Learning |
Black-box |
Image Encoder Models |
CCS |
Link |
|
Attack Papers 2020 [Back to Top]
| Year |
Title |
Adversarial Knowledge |
Target Model |
Venue |
Paper Link |
Code Link |
| 2020 |
GECKO: Reconciling Privacy, Accuracy and Efficiency in Embedded Deep Learning |
Black-box |
Classification Models |
NeurIPS Workshop |
Link |
|
| 2020 |
Gan-leaks: A taxonomy of membership inference attacks against generative models |
White-box; Black-box |
Generative Models |
CCS |
Link |
Link |
| 2020 |
Stolen Memories: Leveraging Model Memorization for Calibrated White-Box Membership Inference |
White-box |
Classification Models |
USENIX Security |
Link |
|
| 2020 |
Information leakage in embedding models |
Black-box |
Text Embedding Models |
CCS |
Link |
|
| 2020 |
When machine unlearning jeopardizes privacy |
Black-box |
Classification Models |
Arxiv |
Link |
|
| 2020 |
Revisiting membership inference under realistic assumptions |
Black-box |
Classification Models |
PoPETs |
Link |
Link |
| 2020 |
Membership inference attacks on sequence-to-sequence models: Is my data in your machine translation system? |
Black-box |
Text Generation Models |
TACL |
Link |
Link |
| 2020 |
Segmentations-leak: Membership inference attacks and defenses in semantic image segmentation |
Black-box |
Image Segmentation Models |
ECCV |
Link |
Link |
| 2020 |
Performing co-membership attacks against deep generative models |
White-box |
Generative Models |
ICDM |
Link |
|
| 2020 |
On the privacy risks of algorithmic fairness |
Black-box |
Classification Models |
EuroS&P |
Link |
|
| 2020 |
A Comprehensive Analysis of Information Leakage in Deep Transfer Learning |
Black-box |
Classification Models |
Arxiv |
Link |
|
| 2020 |
Gan enhanced membership inference: A passive local attack in federated learning |
White-box |
Classification Models |
ICC |
Link |
|
| 2020 |
Privacy analysis of deep learning in the wild: Membership inference attacks against transfer learning |
Black-box |
Classification Models |
Arxiv |
Link |
|
| 2020 |
Data and model dependencies of membership inference attack |
Black-box |
Classification Models |
Arxiv |
Link |
|
| 2020 |
A Pragmatic Approach to Membership Inferences on Machine Learning Models |
Black-box |
Classification Models |
EuroS&P |
Link |
|
| 2020 |
Quantifying Membership Inference Vulnerability via Generalization Gap and Other Model Metrics |
Black-box |
Classification Models |
Arxiv |
Link |
|
| 2020 |
Investigating the Impact of Pre-trained Word Embeddings on Memorization in Neural Networks |
Black-box |
Word Embedding Models |
TSD |
Link |
|
| 2020 |
Beyond Model-Level Membership Privacy Leakage: an Adversarial Approach in Federated Learning |
White-box |
Classification Models |
ICCCN |
Link |
|
| 2020 |
Practical Membership Inference Attack Against Collaborative Inference in Industrial IoT |
White-box |
Classification Models |
IEEE Trans. Industr. Inform. |
Link |
|
Attack Papers 2019 [Back to Top]
| Year |
Title |
Adversarial Knowledge |
Target Model |
Venue |
Paper Link |
Code Link |
| 2019 |
Exploiting unintended feature leakage in collaborative learning |
White-box |
Classification Models |
S&P |
Link |
Link |
| 2019 |
Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference Attacks against Centralized and Federated Learning |
Black-box; White-box |
Classification Models |
S&P |
link |
Link |
| 2019 |
ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models |
Black-box |
Classification Models |
NDSS |
Link |
Link |
| 2019 |
LOGAN: Membership Inference Attacks Against Generative Models |
Black-box; White-box |
Generative Models |
PoPETs |
Link |
Link |
| 2019 |
White-box vs Black-box: Bayes Optimal Strategies for Membership Inference |
Black-box |
Classification Models |
ICML |
Link |
|
| 2019 |
Auditing data provenance in text-generation models |
Black-box |
Text Generation Models |
KDD |
Link |
Link |
| 2019 |
Socinf: Membership inference attacks on social media health data with machine learning |
Black-box |
Classification Models |
IEEE Trans. Comput. Soc. Syst. |
Link |
|
| 2019 |
Monte Carlo and Reconstruction Membership Inference Attacks against Generative Models. |
White-box; Black-box |
Generative Models |
PoPETs |
Link |
Link |
| 2019 |
Disparate Vulnerability: on the Unfairness of Privacy Attacks Against Machine Learning |
Black-box |
Classification Models |
Arxiv |
Link |
|
| 2019 |
Demystifying the membership inference attack |
Black-box |
Classification Models |
CMI |
Link |
|
| 2019 |
Differential Privacy Defenses and Sampling Attacks for Membership Inference |
Black-box |
Classification Models |
NeurIPS Workshop |
Link |
|
| 2019 |
Privacy Risks of Securing Machine Learning Models against Adversarial Examples |
Black-box |
Classification Models |
CCS |
Link |
Link |
| 2019 |
Membership Inference Attacks against Adversarially Robust Deep Learning Models |
Black-box |
Classification Models |
S&P Workshop |
Link |
|
| 2019 |
Demystifying Membership Inference Attacks in Machine Learning as a Service |
Black-box |
Classification Models |
IEEE Trans. Serv. Comput. |
Link |
|
Attack Papers 2018 [Back to Top]
| Year |
Title |
Adversarial Knowledge |
Target Model |
Venue |
Paper Link |
Code Link |
| 2018 |
Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting |
Black-box |
Classification Models |
CSF |
Link |
Link |
| 2018 |
Understanding membership inferences on well-generalized learning models |
Black-box |
Classification Models |
Arxiv |
link |
|
Attack Papers 2017 [Back to Top]
| Year |
Title |
Adversarial Knowledge |
Target Model |
Venue |
Paper Link |
Code Link |
| 2017 |
Membership inference attacks against machine learning models |
Black-box |
Classification Models |
S&P |
link |
Link |
Membership Inference Defense
Defense Papers 2023 [Back to Top]
| Year |
Title |
Adversarial Knowledge |
Target Model |
Venue |
Paper Link |
Code Link |
| 2023 |
Mitigating Membership Inference Attacks via Weighted Smoothing |
Black-box |
Classification Models |
ACSAC |
Link |
Link |
| 2023 |
MIST: Defending Against Membership Inference Attacks Through Membership-Invariant Subspace Training |
Black-box |
Classification Models |
Arxiv |
Link |
|
| 2023 |
Overconfidence is a Dangerous Thing: Mitigating Membership Inference Attacks by Enforcing Less Confident Prediction |
Black-box |
Classification Models |
NDSS |
Link |
Link |
| 2023 |
LoDen: Making Every Client in Federated Learning a Defender Against the Poisoning Membership Inference Attacks |
White-box; Black-box |
Classification Models |
Asia CCS |
Link |
Link |
Defense Papers 2022 [Back to Top]
| Year |
Title |
Adversarial Knowledge |
Target Model |
Venue |
Paper Link |
Code Link |
| 2022 |
Defense against membership inference attack in graph neural networks through graph perturbation |
White-box |
Graph Embedding Models |
Int. J. Inf. Secur. |
Link |
|
| 2022 |
Provable Membership Inference Privacy |
White-box; Black-box |
Classification Models |
Arxiv |
Link |
|
| 2022 |
Repeated Knowledge Distillation with Confidence Masking to Mitigate Membership Inference Attacks |
White-box; Black-box |
Classification Models |
AISec |
Link |
|
| 2022 |
NeuGuard: Lightweight Neuron-Guided Defense against Membership Inference Attacks |
Black-box |
Classification Models |
Arxiv |
Link |
|
| 2022 |
Defending against Membership Inference Attacks with High Utility by GAN |
White-box; Black-box |
Classification Models |
TDSC |
Link |
|
| 2022 |
RelaxLoss: Defending Membership Inference Attacks without Losing Utility |
White-box; Black-box |
Classification Models |
ICLR |
Link |
Link |
| 2022 |
Assessing Differentially Private Variational Autoencoders under Membership Inference |
Black-box |
Generative Models |
Arxiv |
Link |
Link |
| 2022 |
Membership Privacy Protection for Image Translation Models via Adversarial Knowledge Distillation |
Black-box |
Image Translation Models |
Arxiv |
Link |
|
| 2022 |
MIAShield: Defending Membership Inference Attacks via Preemptive Exclusion of Members |
Black-box |
Classification Models |
Arxiv |
Link |
|
| 2022 |
Privacy-preserving Generative Framework Against Membership Inference Attacks |
White-box; Black-box |
Classification Models |
Arxiv |
Link |
|
Defense Papers 2021 [Back to Top]
| Year |
Title |
Adversarial Knowledge |
Target Model |
Venue |
Paper Link |
Code Link |
| 2021 |
Enhanced Mixup Training: a Defense Method Against Membership Inference Attack |
Black-box |
Classification Models |
ISPEC |
Link |
|
| 2021 |
Mitigating Membership Inference Attacks by Self-Distillation Through a Novel Ensemble Architecture |
White-box; Black-box |
Classification Models |
Arxiv |
Link |
|
| 2021 |
On the privacy-utility trade-off in differentially private hierarchical text classification |
White-box |
Classification Models |
Arxiv |
Link |
|
| 2021 |
MLCapsule: Guarded Offline Deployment of Machine Learning as a Service |
Black-box |
Classification Models |
CVPR |
Link |
|
| 2021 |
Comparing Local and Central Differential Privacy Using Membership Inference Attacks |
White-box |
Classification Models |
DBSec |
Link |
Link |
| 2021 |
Adversary Instantiation: Lower Bounds for Differentially Private Machine Learning |
White-box |
Classification Models |
S&P |
Link |
|
| 2021 |
When Does Data Augmentation Help With Membership Inference Attacks? |
Black-box |
Classification Models |
ICML |
Link |
Link |
| 2021 |
Against Membership Inference Attack: Pruning is All You Need |
Black-box |
Classification Models |
IJCAI |
Link |
|
| 2021 |
Membership Privacy for Machine Learning Models Through Knowledge Transfer |
White-box; Black-box |
Classification Models |
AAAI |
Link |
|
| 2021 |
Quantifying Membership Privacy via Information Leakage |
Black-box |
Classification Models |
IEEE Trans. Inf. Forensics Secur. |
Link |
|
| 2021 |
Membership Inference Attacks and Defenses in Classification Models |
Black-box |
Classification Models |
CODASPY |
Link |
|
| 2021 |
Digestive Neural Networks: A Novel Defense Strategy Against Inference Attacks in Federated Learning |
White-box |
Classification Models |
Computers & Security |
Link |
|
| 2021 |
Resisting Membership Inference Attacks through Knowledge Distillation |
Black-box |
Classification Models |
Neurocomputing |
Link |
|
| 2021 |
privGAN: Protecting GANs from membership inference attacks at low cost to utility |
White-box |
Generative Models |
PoPETs |
Link |
|
| 2021 |
Generating Private Data Surrogates for Vision Related Tasks |
White-box |
Generative Models |
ICPR |
Link |
|
| 2021 |
Membership Inference Attack with Multi-Grade Service Models in Edge Intelligence |
Black-box |
Classification Models |
IEEE Network |
Link |
|
| 2021 |
PAR-GAN: Improving the Generalization of Generative Adversarial Networks Against Membership Inference Attacks |
White-box |
Generative Models |
KDD |
Link |
Link |
| 2021 |
Defending Medical Image Diagnostics against Privacy Attacks using Generative Methods: Application to Retinal Diagnostics |
Black-box |
Classification Models |
MICCAI Workshop |
Link |
|
| 2021 |
Defending Privacy Against More Knowledgeable Membership Inference Attackers |
White-box; Black-box |
Classification Models |
KDD |
Link |
Link |
Defense Papers 2020 [Back to Top]
| Year |
Title |
Adversarial Knowledge |
Target Model |
Venue |
Paper Link |
Code Link |
| 2020 |
Privacy for All: Demystify Vulnerability Disparity of Differential Privacy against Membership Inference Attack |
Black-box |
Classification Models |
Arxiv |
Link |
|
| 2020 |
Privacy for All: Demystify Vulnerability Disparity of Differential Privacy against Membership Inference Attack |
Black-box |
Classification Models |
Arxiv |
Link |
|
| 2020 |
Differential Privacy Protection Against Membership Inference Attack on Machine Learning for Genomic Data |
Black-box |
Classification Models |
Biocomputing |
Link |
|
| 2020 |
A Secure Federated Learning Framework for 5G Networks |
White-box |
Classification Models |
IEEE Wireless Communications |
Link |
|
| 2020 |
Auditing Differentially Private Machine Learning: How Private is Private SGD? |
Black-box |
Classification Models |
NeurIPS |
Link |
Link |
| 2020 |
Toward Robustness and Privacy in Federated Learning: Experimenting with Local and Central Differential Privacy |
White-box |
Classification Models |
Arxiv |
Link |
|
| 2020 |
Defending Model Inversion and Membership Inference Attacks via Prediction Purification |
Black-box |
Classification |
Arxiv |
Link |
|
| 2020 |
Alleviating Privacy Attacks via Causal Learning |
Black-box |
Classification Models |
ICML |
Link |
Link |
| 2020 |
On the Effectiveness of Regularization Against Membership Inference Attacks |
Black-box |
Classification Models |
Arxiv |
Link |
|
| 2020 |
Characterizing Membership Privacy in Stochastic Gradient Langevin Dynamics |
Black-box |
Classification Models |
AAAI |
Link |
|
| 2020 |
Differentially Private Learning Does Not Bound Membership Inference |
Black-box |
Classification Models |
Arxiv |
Link |
|
| 2020 |
Privacy-Preserving in Defending against Membership Inference Attacks |
Black-box |
Classification Models |
PPMLP |
Link |
|
Defense Papers 2019 [Back to Top]
| Year |
Title |
Adversarial Knowledge |
Target Model |
Venue |
Paper Link |
Code Link |
| 2019 |
Evaluating Differentially Private Machine Learning in Practice |
Black-box |
Classification Models |
USENIX Security |
Link |
Link |
| 2019 |
MemGuard: Defending against Black-Box Membership Inference Attacks via Adversarial Examples |
Black-box |
Classification Models |
CCS |
Link |
Link |
| 2019 |
Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection |
White-box; Black-box |
Generative Models |
NeurIPS |
Link |
|
| 2019 |
Cronus: Robust and Heterogeneous Collaborative Learning with Black-Box Knowledge Transfer |
Black-box |
Classification Models |
Arxiv |
Link |
|
| 2019 |
ML Defense: Against Prediction API Threats in Cloud-Based Machine Learning Service |
Black-box |
Classification Models |
IWQoS |
Link |
|
| 2019 |
Effects of Differential Privacy and Data Skewness on Membership Inference Vulnerability |
Black-box |
Classification Models |
TPS-ISA |
Link |
|
| 2019 |
Generating Artificial Data for Private Deep Learning |
Black-box |
Generative Models |
PAL |
Link |
|
Defense Papers 2018 [Back to Top]
| Year |
Title |
Adversarial Knowledge |
Target Model |
Venue |
Paper Link |
Code Link |
| 2018 |
Machine Learning with Membership Privacy using Adversarial Regularization |
Black-box |
Classification Models |
CCS |
Link |
Link |
| 2018 |
Privacy-preserving Machine Learning through Data Obfuscation |
Black-box |
Classification Models |
Arxiv |
Link |
|
| 2018 |
Differentially Private Data Generative Models |
Black-box |
Classification Models |
Arxiv |
Link |
|
| 2018 |
Membership Inference Attack against Differentially Private Deep Learning Model |
Black-box |
Classification Models |
Transactions on Data Privacy |
Link |
|
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HongshengHu
HongshengHu