microsoft / privGANLinks
PrivGAN: Protecting GANs from membership inference attacks at low cost
☆33Updated last year
Alternatives and similar repositories for privGAN
Users that are interested in privGAN are comparing it to the libraries listed below
Sorting:
- A library for running membership inference attacks against ML models☆149Updated 2 years ago
- Python package to create adversarial agents for membership inference attacks againts machine learning models☆47Updated 6 years ago
- Code for Membership Inference Attack against Machine Learning Models (in Oakland 2017)☆194Updated 7 years ago
- Differentially Private (tabular) Generative Models Papers with Code☆52Updated last year
- Source code of paper "Differentially Private Generative Adversarial Network"☆70Updated 6 years ago
- Systematic Evaluation of Membership Inference Privacy Risks of Machine Learning Models☆128Updated last year
- [NeurIPS 2021] "G-PATE: Scalable Differentially Private Data Generator via Private Aggregation of Teacher Discriminators" by Yunhui Long*…☆30Updated 3 years ago
- Membership Inference, Attribute Inference and Model Inversion attacks implemented using PyTorch.☆63Updated 10 months ago
- Official implementation of "GAN-Leaks: A Taxonomy of Membership Inference Attacks against Generative Models" (CCS 2020)☆48Updated 3 years ago
- This project's goal is to evaluate the privacy leakage of differentially private machine learning models.☆135Updated 2 years ago
- Membership Inference of Generative Models☆14Updated 5 years ago
- Implementation of the paper : "Membership Inference Attacks Against Machine Learning Models", Shokri et al.☆58Updated 6 years ago
- ☆40Updated 2 years ago
- Differentially Private Conditional Generative Adversarial Network☆31Updated 3 years ago
- Analytic calibration for differential privacy with Gaussian perturbations☆48Updated 6 years ago
- Code to reproduce experiments in "Antipodes of Label Differential Privacy PATE and ALIBI"☆32Updated 3 years ago
- A toolbox for differentially private data generation☆132Updated 2 years ago
- Amortized version of the differentially private SGD algorithm published in "Deep Learning with Differential Privacy" by Abadi et al. Enfo…☆41Updated last year
- Fast, memory-efficient, scalable optimization of deep learning with differential privacy☆127Updated 2 weeks ago
- ☆36Updated last year
- A library providing general-purpose tools for estimating discrete distributions from noisy observations of their marginals.☆105Updated this week
- ☆32Updated 11 months ago
- SAP Security Research sample code to reproduce the research done in our paper "Comparing local and central differential privacy using mem…☆18Updated last year
- A Simulator for Privacy Preserving Federated Learning☆94Updated 4 years ago
- Differentially Private Optimization for PyTorch 👁🙅♀️☆187Updated 5 years ago
- autodp: A flexible and easy-to-use package for differential privacy☆274Updated last year
- A fast algorithm to optimally compose privacy guarantees of differentially private (DP) mechanisms to arbitrary accuracy.☆73Updated last year
- Implementation of the Model Inversion Attack introduced with Model Inversion Attacks that Exploit Confidence Information and Basic Counte…☆85Updated 2 years ago
- ☆70Updated 3 years ago
- Code for the paper "ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models"☆84Updated 3 years ago