Alternatives and similar repositories for Secure-and-Private-AI:

Users that are interested in Secure-and-Private-AI are comparing it to the libraries listed below

• lingjuanlv / FPPDL
  code for TPDS paper "Towards Fair and Privacy-Preserving Federated Deep Models"
  ☆31Updated 2 years ago
• DPBayes / ADADP
  Learning rate adaptation for differentially private stochastic gradient descent
  ☆16Updated 3 years ago
• sam-yeom / ml-privacy-csf18
  Code for the CSF 2018 paper "Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting"
  ☆38Updated 5 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 5 years ago
• Lory94 / dp-GAN
  Differentially Private Generative Adversarial Networks for Time Series, Continuous, and Discrete Open Data
  ☆33Updated 6 years ago
• Machine-Learning-Security-Lab / mia_prune
  Membership Inference Attacks and Defenses in Neural Network Pruning
  ☆28Updated 2 years ago
• SPIN-UMass / ML-Privacy-Regulization
  ☆26Updated 6 years ago
• desternylin / perfed
  ☆15Updated 10 months ago
• woodyx218 / Deep-Learning-with-GDP-Pytorch
  Code to accompany the paper "Deep Learning with Gaussian Differential Privacy"
  ☆31Updated 3 years ago
• jeremy313 / Soteria
  Official implementation of "Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective"
  ☆55Updated last year
• BielStela / membership_inference
  Python package to create adversarial agents for membership inference attacks againts machine learning models
  ☆46Updated 5 years ago
• hwang595 / DETOX
  DETOX: A Redundancy-based Framework for Faster and More Robust Gradient Aggregation
  ☆16Updated 4 years ago
• shrezaei / MI-Attack
  ☆32Updated 4 months ago
• git-disl / Fed-CDP
  Gradient-Leakage Resilient Federated Learning
  ☆13Updated 2 years ago
• DingfanChen / RelaxLoss
  Official implementation of "RelaxLoss: Defending Membership Inference Attacks without Losing Utility" (ICLR 2022)
  ☆48Updated 2 years ago
• ebagdasa / differential-privacy-vs-fairness
  Code for "Differential Privacy Has Disparate Impact on Model Accuracy" NeurIPS'19
  ☆35Updated 3 years ago
• ebagdasa / pytorch-privacy
  simple Differential Privacy in PyTorch
  ☆48Updated 4 years ago
• AI-secure / DataLens
  [CCS 2021] "DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation" by Boxin Wang*, Fan Wu*, Yunhui Long…
  ☆37Updated 3 years ago
• DeRafael / CAFE
  ☆21Updated 3 years ago
• yiyiyi4321 / Vertical-Federated-Learning
  ☆12Updated 5 years ago
• AdrienBenamira / membership_inference_attack
  Implementation of the paper : "Membership Inference Attacks Against Machine Learning Models", Shokri et al.
  ☆57Updated 5 years ago
• gitgik / differential-privacy-federated-learning
  Curated notebooks on how to train neural networks using differential privacy and federated learning.
  ☆66Updated 4 years ago
• alevine0 / DPA
  Code for the paper "Deep Partition Aggregation: Provable Defenses against General Poisoning Attacks"
  ☆12Updated 2 years ago
• shrebox / Privacy-Attacks-in-Machine-Learning
  Membership Inference, Attribute Inference and Model Inversion attacks implemented using PyTorch.
  ☆58Updated 3 months ago
• ganeshdg95 / Leveraging-Adversarial-Examples-to-Quantify-Membership-Information-Leakage
  ☆20Updated last year
• AI-secure / CRFL
  CRFL: Certifiably Robust Federated Learning against Backdoor Attacks (ICML 2021)
  ☆72Updated 3 years ago
• mattbev / 6.867-final-project
  Adversarial attacks and defenses against federated learning.
  ☆15Updated last year
• google-deepmind / informed_adversary_mnist_reconstruction
  ☆17Updated 2 years ago
• lee-man / federated-learning
  Related material on Federated Learning
  ☆26Updated 4 years ago