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A curated list of resources for model inversion attack (MIA).
If some related papers are missing, please contact us via pull requests.
### What is the model inversion attack?
**Outlines:**
[TOC]
## What is the model inversion attack?
A model inversion attack is a privacy attack where the attacker is able to reconstruct the original samples that were used to train the synthetic model from the generated synthetic data set. (Mostly.ai)
@@ -16,7 +20,7 @@ The goal of model inversion attacks is to recreate training data or sensitive at
In model inversion attacks, a malicious user attempts to recover the private dataset used to train a supervised neural network. A successful model inversion attack should generate realistic and diverse samples that accurately describe each of the classes in the private dataset. (Wang et al, 2021.)
### Survey
## Survey
Arxiv 2021 - A Survey of Privacy Attacks in Machine Learning.
[[paper]](https://arxiv.org/pdf/2007.07646.pdf)
@@ -34,7 +38,7 @@ Philosophical Transactions of the Royal Society A 2018. Algorithms that remember
[[paper]](https://royalsocietypublishing.org/doi/pdf/10.1098/rsta.2018.0083)
### Computer vision domain
## Computer vision domain
USENIX Security 2014 - Privacy in Pharmacogenetics: An End-to-End Case Study of Personalized Warfarin Dosing.
[[paper]](https://www.usenix.org/system/files/conference/usenixsecurity14/sec14-paper-fredrikson-privacy.pdf)
@@ -46,6 +50,10 @@ CCS 2015 - Model Inversion Attacks that Exploit Confidence Information and Basic
[[code3]](https://github.com/zhangzp9970/MIA)
[[code4]](https://github.com/sarahsimionescu/simple-model-inversion)
IJCAI 2015 - Regression model fitting under differential privacy and model inversion attack.
[[paper]](http://www.csce.uark.edu/~xintaowu/publ/ijcai15.pdf)
[[code]](https://github.com/cxs040/Regression-Model-Fitting-under-Differential-Privacy-and-Model-Inversion-Attack-Source-Code)
CSF 2016 - A Methodology for Formalizing Model-Inversion Attacks.
[[paper]](https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7536387&casa_token=ClIVAMYo6dcAAAAA:u75HHyFHj5lBRec9h5SqOZyAsL2dICcWIuQPCj6ltk8McREFCaM4ex42mv3S-oNPiGJLDfUqg0qL)
@@ -59,6 +67,13 @@ PST 2017 - Model inversion attacks for prediction systems: Without knowledge of
CSF 2018 - Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting.
[[paper]](https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=8429311)
GLSVLSI 2019 - MLPrivacyGuard: Defeating Confidence Information based Model Inversion Attacks on Machine Learning Systems.
[[paper]](https://www.researchgate.net/profile/Tiago-Alves-13/publication/333136362_MLPrivacyGuard_Defeating_Confidence_Information_based_Model_Inversion_Attacks_on_Machine_Learning_Systems/links/5cddb94d92851c4eaba682d7/MLPrivacyGuard-Defeating-Confidence-Information-based-Model-Inversion-Attacks-on-Machine-Learning-Systems.pdf)
ACSAC 2019 - Model inversion attacks against collaborative inference.
[[paper]](https://par.nsf.gov/servlets/purl/10208164)
[[code]](https://github.com/zechenghe/Inverse_Collaborative_Inference)
CCS 2019 - Neural Network Inversion in Adversarial Setting via Background Knowledge Alignment.
[[paper]](https://dl.acm.org/doi/pdf/10.1145/3319535.3354261?casa_token=J81Ps-ZWXHkAAAAA:FYnXo7DQoHpdhqns8x2TclKFeHpAQlXVxMBW2hTrhJ5c20XKdsounqdT1Viw1g6Xsu9FtKj85elxQaA)
[[code]](https://github.com/zhangzp9970/TB-MIA)
@@ -87,9 +102,16 @@ APSIPA ASC 2020 - Deep Face Recognizer Privacy Attack: Model Inversion Initializ
USENIX Security 2020 - Updates-Leak: Data Set Inference and Reconstruction Attacks in Online Learning.
[[paper]](https://www.usenix.org/system/files/sec20-salem.pdf)
IoTJ 2020 - Attacking and Protecting Data Privacy in Edge-Cloud Collaborative Inference Systems.
[[paper]](https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9187880)
[[code]](https://github.com/zechenghe/Inverse_Collaborative_Inference)
ECCV 2020 Workshop - Black-Box Face Recovery from Identity Features.
[[paper]](https://arxiv.org/pdf/2007.13635.pdf)
Arxiv 2020 - Defending model inversion and membership inference attacks via prediction purification.
[[paper]](https://arxiv.org/pdf/2005.03915.pdf)
IJCAI 2021 - Contrastive Model Inversion for Data-Free Knowledge Distillation.
[[paper]](https://www.ijcai.org/proceedings/2021/0327.pdf)
[[code]](https://github.com/zju-vipa/CMI)
@@ -187,7 +209,7 @@ Arxiv 2022 - Defending against Reconstruction Attacks through Differentially Pri
IEEE 2021 - Defending Against Model Inversion Attack by Adversarial Examples.
[[paper]](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9527945&tag=1)
### Graph learning domain
## Graph learning domain
USENIX Security 2020 - Stealing Links from Graph Neural Networks.
[[paper]](https://www.usenix.org/system/files/sec21-he-xinlei.pdf)
@@ -250,7 +272,7 @@ ICML 2023 - On Strengthening and Defending Graph Reconstruction Attack with Mark
[[paper]](https://openreview.net/pdf?id=Vcl3qckVyh)
[[code]](https://github.com/tmlr-group/MC-GRA)
### Natural language processing domain
## Natural language processing domain
CCS 2020 - Information Leakage in Embedding Models.
[[paper]](https://dl.acm.org/doi/pdf/10.1145/3372297.3417270?casa_token=0ltuTKcG5cIAAAAA:YcpnOm4WlV0UnSS2dOWdtcnFh6DqSygG9MuS31gGQEgMxOBHQKeXsoNGkFhEw8gvlqY78gTkaRn9gUo)
@@ -262,7 +284,7 @@ Arxiv 2022 - Text Revealer: Private Text Reconstruction via Model Inversion Atta
[[paper]](https://arxiv.org/pdf/2209.10505.pdf)
### Tools
## Tools
[AIJack](https://github.com/Koukyosyumei/AIJack): Implementation of algorithms for AI security.
[Privacy-Attacks-in-Machine-Learning](https://github.com/shrebox/Privacy-Attacks-in-Machine-Learning): Membership Inference, Attribute Inference and Model Inversion attacks implemented using PyTorch.
@@ -270,7 +292,7 @@ Arxiv 2022 - Text Revealer: Private Text Reconstruction via Model Inversion Atta
[ml-attack-framework](https://github.com/Pilladian/ml-attack-framework): Universität des Saarlandes - Privacy Enhancing Technologies 2021 - Semester Project.
### Others
## Others
2019 - Uncovering a model’s secrets.
[[blog1]](https://gab41.lab41.org/uncovering-a-models-secrets-model-inversion-part-i-ce460eab93d6)
[[blog2]](https://gab41.lab41.org/robust-or-private-model-inversion-part-ii-94d54fd8d4a5)
@@ -285,7 +307,7 @@ Arxiv 2022 - Text Revealer: Private Text Reconstruction via Model Inversion Atta
[[slides]](https://www.cs.toronto.edu/~toni/Courses/Fairness/Lectures/ML-and-DP-v2.pdf)
### Related repositories
## Related repositories
awesome-ml-privacy-attacks
[[repo]](https://github.com/stratosphereips/awesome-ml-privacy-attacks#reconstruction)