Alternatives and similar repositories for PPGANs-Privacy-preserving-GANs

Users that are interested in PPGANs-Privacy-preserving-GANs are comparing it to the libraries listed below

• illidanlab / dpgan
  Source code of paper "Differentially Private Generative Adversarial Network"
  ☆70Updated 7 years ago
• DingfanChen / GS-WGAN
  Official implementation of "GS-WGAN: A Gradient-Sanitized Approach for Learning Differentially Private Generators" (NeurIPS 2020)
  ☆70Updated 3 years ago
• miranthajayatilake / dpgan
  Implementation of a differentially private generative adversarial network.
  ☆11Updated 7 years ago
• DingfanChen / GAN-Leaks
  Official implementation of "GAN-Leaks: A Taxonomy of Membership Inference Attacks against Generative Models" (CCS 2020)
  ☆47Updated 3 years ago
• AI-secure / G-PATE
  [NeurIPS 2021] "G-PATE: Scalable Differentially Private Data Generator via Private Aggregation of Teacher Discriminators" by Yunhui Long*…
  ☆30Updated 4 years ago
• jhayes14 / gen_mem_inf
  Membership Inference of Generative Models
  ☆15Updated 6 years ago
• csong27 / membership-inference
  Code for Membership Inference Attack against Machine Learning Models (in Oakland 2017)
  ☆200Updated 8 years ago
• kamathhrishi / PATE
  Pytorch implementation of paper Semi-supervised Knowledge Transfer for Deep Learning from Private Training Data (https://arxiv.org/abs/16…
  ☆45Updated 4 years ago
• sam-yeom / ml-privacy-csf18
  Code for the CSF 2018 paper "Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting"
  ☆39Updated 7 years ago
• spring-epfl / mia
  A library for running membership inference attacks against ML models
  ☆152Updated 3 years ago
• reihaneh-torkzadehmahani / DP-CGAN
  Differentially Private Conditional Generative Adversarial Network
  ☆31Updated 4 years ago
• microsoft / privGAN
  PrivGAN: Protecting GANs from membership inference attacks at low cost
  ☆36Updated last year
• BielStela / membership_inference
  Python package to create adversarial agents for membership inference attacks againts machine learning models
  ☆47Updated 6 years ago
• lingjuanlv / FPPDL
  code for TPDS paper "Towards Fair and Privacy-Preserving Federated Deep Models"
  ☆31Updated 3 years ago
• mattbev / 6.867-final-project
  Adversarial attacks and defenses against federated learning.
  ☆20Updated 2 years ago
• ebagdasa / pytorch-privacy
  simple Differential Privacy in PyTorch
  ☆49Updated 5 years ago
• woodyx218 / Deep-Learning-with-GDP-Tensorflow
  Code to accompany the paper "Deep Learning with Gaussian Differential Privacy"
  ☆49Updated 4 years ago
• SPIN-UMass / ML-Privacy-Regulization
  ☆25Updated 7 years ago
• civisanalytics / dpwgan
  Differentially-private Wasserstein GAN implementation in PyTorch
  ☆28Updated 6 years ago
• gitgik / differential-privacy-federated-learning
  Curated notebooks on how to train neural networks using differential privacy and federated learning.
  ☆67Updated 5 years ago
• inspire-group / ModelPoisoning
  Code for "Analyzing Federated Learning through an Adversarial Lens" https://arxiv.org/abs/1811.12470
  ☆152Updated 3 years ago
• layer6ai-labs / fair-dp
  Code accompanying the paper "Disparate Impact in Differential Privacy from Gradient Misalignment".
  ☆11Updated 2 years ago
• Hydrino / ACGAN_cifar10
  A PyTorch implementation of Auxiliary Classifier GAN to generate CIFAR10 images.
  ☆47Updated 7 years ago
• ParkLabML / DP-MERF
  ☆17Updated 2 years ago
• ipc-lab / private-ml-for-health
  Dopamine: Differentially Private Federated Learning on Medical Data (AAAI - PPAI)
  ☆76Updated 11 months ago
• yashkant / model-inversion-attack
  Implementation of the Model Inversion Attack introduced with Model Inversion Attacks that Exploit Confidence Information and Basic Counte…
  ☆85Updated 2 years ago
• inspire-group / privacy-vs-robustness
  Privacy Risks of Securing Machine Learning Models against Adversarial Examples
  ☆46Updated 6 years ago
• lmunoz-gonzalez / Poisoning-Attacks-with-Back-gradient-Optimization
  Example of the attack described in the paper "Towards Poisoning of Deep Learning Algorithms with Back-gradient Optimization"
  ☆21Updated 6 years ago
• jinyuan-jia / MemGuard
  ☆46Updated 6 years ago
• AdrienBenamira / membership_inference_attack
  Implementation of the paper : "Membership Inference Attacks Against Machine Learning Models", Shokri et al.
  ☆60Updated 6 years ago