Alternatives and similar repositories for MIA:

Users that are interested in MIA are comparing it to the libraries listed below

• AdrienBenamira / membership_inference_attack
  Implementation of the paper : "Membership Inference Attacks Against Machine Learning Models", Shokri et al.
  ☆58Updated 5 years ago
• cchoquette / membership-inference
  Code for the paper: Label-Only Membership Inference Attacks
  ☆64Updated 3 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
• ksreenivasan / OOD_Federated_Learning
  ☆69Updated 2 years ago
• inspire-group / membership-inference-evaluation
  Systematic Evaluation of Membership Inference Privacy Risks of Machine Learning Models
  ☆125Updated 11 months ago
• csong27 / property-inference-collaborative-ml
  Code for Exploiting Unintended Feature Leakage in Collaborative Learning (in Oakland 2019)
  ☆53Updated 5 years ago
• AI-secure / GMI-Attack
  ☆26Updated 3 years ago
• jinyuan-jia / MemGuard
  ☆45Updated 5 years ago
• shrebox / Privacy-Attacks-in-Machine-Learning
  Membership Inference, Attribute Inference and Model Inversion attacks implemented using PyTorch.
  ☆58Updated 5 months ago
• AhmedSalem2 / ML-Leaks
  Code for the paper "ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models"
  ☆82Updated 3 years ago
• tribhuvanesh / prediction-poisoning
  Prediction Poisoning: Towards Defenses Against DNN Model Stealing Attacks (ICLR '20)
  ☆29Updated 4 years ago
• hyhmia / BlindMI
  ☆23Updated 2 years ago
• BielStela / membership_inference
  Python package to create adversarial agents for membership inference attacks againts machine learning models
  ☆46Updated 6 years ago
• sam-yeom / ml-privacy-csf18
  Code for the CSF 2018 paper "Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting"
  ☆38Updated 6 years ago
• liuyugeng / ML-Doctor
  Code for ML Doctor
  ☆88Updated 7 months ago
• yashkant / model-inversion-attack
  Implementation of the Model Inversion Attack introduced with Model Inversion Attacks that Exploit Confidence Information and Basic Counte…
  ☆83Updated 2 years ago
• shrezaei / MI-Attack
  ☆31Updated 6 months ago
• AhmedSalem2 / Updates-Leak
  The code for our Updates-Leak paper
  ☆17Updated 4 years ago
• Machine-Learning-Security-Lab / mia_prune
  Membership Inference Attacks and Defenses in Neural Network Pruning
  ☆28Updated 2 years ago
• jeremy313 / Soteria
  Official implementation of "Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective"
  ☆55Updated last year
• pasquini-dario / SplitNN_FSHA
  Privacy attacks on Split Learning
  ☆38Updated 3 years ago
• zechenghe / Inverse_Collaborative_Inference
  ☆42Updated 3 years ago
• KaiyuanZh / FLIP
  [ICLR 2023, Best Paper Award at ECCV’22 AROW Workshop] FLIP: A Provable Defense Framework for Backdoor Mitigation in Federated Learning
  ☆53Updated 3 months ago
• zhenglisec / Label-Only-MIA
  ☆19Updated 6 months ago
• dayu11 / Differentially-Private-Deep-Learning
  This repo implements several algorithms for learning with differential privacy.
  ☆106Updated 2 years ago
• DingfanChen / RelaxLoss
  Official implementation of "RelaxLoss: Defending Membership Inference Attacks without Losing Utility" (ICLR 2022)
  ☆48Updated 2 years ago
• cake-lab / datafree-model-extraction
  CVPR 2021 Official repository for the Data-Free Model Extraction paper. https://arxiv.org/abs/2011.14779
  ☆71Updated 11 months ago
• kangliucn / Fine-pruning-defense
  Fine-Pruning: Defending Against Backdooring Attacks on Deep Neural Networks (RAID 2018)
  ☆47Updated 6 years ago
• ganeshdg95 / Leveraging-Adversarial-Examples-to-Quantify-Membership-Information-Leakage
  ☆20Updated 2 years ago
• SCccc21 / Knowledge-Enriched-DMI
  ☆42Updated last year