Awesome Ml Privacy Attacks

An awesome list of papers on privacy attacks against machine learning
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Project NameStarsDownloadsRepos Using ThisPackages Using ThisMost Recent CommitTotal ReleasesLatest ReleaseOpen IssuesLicenseLanguage
Adversarial Robustness Toolbox3,733717 hours ago45July 01, 2022125mitPython
Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams
Pfl Non Iid555
4 days ago4gpl-2.0Python
Personalized federated learning simulation platform with non-IID and unbalanced dataset
Awesome Ml Privacy Attacks396
2 months ago
An awesome list of papers on privacy attacks against machine learning
4 months ago1May 13, 20224mitJupyter Notebook
Privacy Meter: An open-source library to audit data privacy in statistical and machine learning algorithms.
Deep Spying173
6 years agoapache-2.0Python
Spying using Smartwatch and Deep Learning
2 months ago36apache-2.0Python
Privacy Testing for Deep Learning
16 days ago11mitPython
Toolkit for building machine learning models that generalize to unseen domains and are robust to privacy and other attacks.
6 months ago1mitPython
This project's goal is to evaluate the privacy leakage of differentially private machine learning models.
4 months ago26mitPython
Privacy Preserving Collaborative Encrypted Network Traffic Classification (Differential Privacy, Federated Learning, Membership Inference Attack, Encrypted Traffic Classification)
2 years ago4September 27, 201815mitPython
A library for running membership inference attacks against ML models
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Awesome Attacks on Machine Learning Privacy Awesome

This repository contains a curated list of papers related to privacy attacks against machine learning. A code repository is provided when available by the authors. For corrections, suggestions, or missing papers, please either open an issue or submit a pull request.


Surveys and Overviews

Privacy Testing Tools

Papers and Code

Membership inference

A curated list of membership inference papers (more than 100 papers) on machine learning models is available at this repository.


Reconstruction attacks cover also attacks known as model inversion and attribute inference.

Property inference

Model extraction


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