Alternatives and similar repositories for property-inference-attacks

Users that are interested in property-inference-attacks are comparing it to the libraries listed below

• google-research / DP-FTRL
  DP-FTRL from "Practical and Private (Deep) Learning without Sampling or Shuffling" for centralized training.
  ☆29Updated last week
• ganeshdg95 / Leveraging-Adversarial-Examples-to-Quantify-Membership-Information-Leakage
  ☆19Updated 2 years ago
• pasquini-dario / SplitNN_FSHA
  Privacy attacks on Split Learning
  ☆42Updated 3 years ago
• microsoft / prv_accountant
  A fast algorithm to optimally compose privacy guarantees of differentially private (DP) mechanisms to arbitrary accuracy.
  ☆73Updated last year
• woodyx218 / opacus_global_clipping
  ☆15Updated 2 years ago
• MinChen00 / UnlearningLeaks
  Official implementation of "When Machine Unlearning Jeopardizes Privacy" (ACM CCS 2021)
  ☆48Updated 3 years ago
• pps-lab / rofl-project-code
  ☆32Updated 2 years ago
• jagielski / auditing-dpsgd
  Code for Auditing DPSGD
  ☆37Updated 3 years ago
• sarus-tech / dp-xgboost
  ☆23Updated last year
• liuyugeng / ML-Doctor
  Code for ML Doctor
  ☆89Updated 9 months ago
• facebookresearch / dp_compression
  Code repo for the paper "Privacy-aware Compression for Federated Data Analysis".
  ☆19Updated 2 years ago
• DingfanChen / RelaxLoss
  Official implementation of "RelaxLoss: Defending Membership Inference Attacks without Losing Utility" (ICLR 2022)
  ☆50Updated 2 years ago
• csong27 / property-inference-collaborative-ml
  Code for Exploiting Unintended Feature Leakage in Collaborative Learning (in Oakland 2019)
  ☆53Updated 6 years ago
• ebagdasa / differential-privacy-vs-fairness
  Code for "Differential Privacy Has Disparate Impact on Model Accuracy" NeurIPS'19
  ☆34Updated 4 years ago
• google-deepmind / jax_privacy
  Algorithms for Privacy-Preserving Machine Learning in JAX
  ☆94Updated last month
• Princeton-SysML / FILM
  Official repo for the paper: Recovering Private Text in Federated Learning of Language Models (in NeurIPS 2022)
  ☆56Updated 2 years ago
• google-research / public-data-in-dpfl
  ☆22Updated 2 years ago
• google-deepmind / informed_adversary_mnist_reconstruction
  ☆18Updated 3 years ago
• facebookresearch / label_dp_antipodes
  Code to reproduce experiments in "Antipodes of Label Differential Privacy PATE and ALIBI"
  ☆32Updated 3 years ago
• Machine-Learning-Security-Lab / mia_prune
  Membership Inference Attacks and Defenses in Neural Network Pruning
  ☆28Updated 2 years ago
• dayu11 / Gradient-Embedding-Perturbation
  ☆27Updated 2 years ago
• inspire-group / membership-inference-evaluation
  Systematic Evaluation of Membership Inference Privacy Risks of Machine Learning Models
  ☆126Updated last year
• bargavj / EvaluatingDPML
  This project's goal is to evaluate the privacy leakage of differentially private machine learning models.
  ☆135Updated 2 years ago
• zechenghe / Inverse_Collaborative_Inference
  ☆45Updated 3 years ago
• AI-secure / FLBenchmark-toolkit
  Federated Learning Framework Benchmark (UniFed)
  ☆49Updated last year
• litian96 / AdaDPS
  Private Adaptive Optimization with Side Information (ICML '22)
  ☆16Updated 2 years ago
• AI-secure / DataLens
  [CCS 2021] "DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation" by Boxin Wang*, Fan Wu*, Yunhui Long…
  ☆38Updated 3 years ago
• DennisLiu2022 / Membership-Inference-Attacks-by-Exploiting-Loss-Trajectory
  ☆25Updated 2 years ago
• sam-yeom / ml-privacy-csf18
  Code for the CSF 2018 paper "Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting"
  ☆37Updated 6 years ago
• krishnap25 / RFA
  Robust aggregation for federated learning with the RFA algorithm.
  ☆48Updated 2 years ago