Alternatives and similar repositories for DP-MIA:

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

• shrebox / Privacy-Attacks-in-Machine-Learning
  Membership Inference, Attribute Inference and Model Inversion attacks implemented using PyTorch.
  ☆58Updated 3 months ago
• dayu11 / Differentially-Private-Deep-Learning
  This repo implements several algorithms for learning with differential privacy.
  ☆104Updated 2 years ago
• srxzr / DPSGD
  ☆20Updated 5 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
• epfml / byzantine-robust-noniid-optimizer
  ☆15Updated 2 years ago
• AdrienBenamira / membership_inference_attack
  Implementation of the paper : "Membership Inference Attacks Against Machine Learning Models", Shokri et al.
  ☆57Updated 5 years ago
• thecml / dpsgd-optimizer
  Amortized version of the differentially private SGD algorithm published in "Deep Learning with Differential Privacy" by Abadi et al. Enfo…
  ☆40Updated 9 months ago
• ebagdasa / pytorch-privacy
  simple Differential Privacy in PyTorch
  ☆48Updated 4 years ago
• PatrickZH / Improved-Deep-Leakage-from-Gradients
  The code for "Improved Deep Leakage from Gradients" (iDLG).
  ☆146Updated 3 years ago
• ftramer / Handcrafted-DP
  ☆80Updated 2 years ago
• cchoquette / membership-inference
  Code for the paper: Label-Only Membership Inference Attacks
  ☆64Updated 3 years ago
• epfml / byzantine-robust-optimizer
  Learning from history for Byzantine Robustness
  ☆22Updated 3 years ago
• jinyuan-jia / MemGuard
  ☆45Updated 5 years ago
• jeremy313 / Soteria
  Official implementation of "Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective"
  ☆55Updated last year
• DingfanChen / GS-WGAN
  Official implementation of "GS-WGAN: A Gradient-Sanitized Approach for Learning Differentially Private Generators" (NeurIPS 2020)
  ☆68Updated 2 years ago
• DingfanChen / RelaxLoss
  Official implementation of "RelaxLoss: Defending Membership Inference Attacks without Losing Utility" (ICLR 2022)
  ☆48Updated 2 years ago
• AI-secure / CRFL
  CRFL: Certifiably Robust Federated Learning against Backdoor Attacks (ICML 2021)
  ☆72Updated 3 years ago
• ksreenivasan / OOD_Federated_Learning
  ☆67Updated 2 years ago
• inspire-group / ModelPoisoning
  Code for "Analyzing Federated Learning through an Adversarial Lens" https://arxiv.org/abs/1811.12470
  ☆147Updated 2 years ago
• woodyx218 / opacus_global_clipping
  ☆13Updated last year
• gdisag / gradient_disaggregation
  ☆14Updated last year
• jgshu / Attacks-and-Defenses-in-Federated-Learning
  ☆38Updated 3 years ago
• ppmlguy / DP-AGD
  Concentrated Differentially Private Gradient Descent with Adaptive per-iteration Privacy Budget
  ☆49Updated 6 years ago
• LPD-EPFL / ByzantineMomentum
  Distributed Momentum for Byzantine-resilient Stochastic Gradient Descent (ICLR 2021)
  ☆20Updated 3 years ago
• facebookresearch / label_dp_antipodes
  Code to reproduce experiments in "Antipodes of Label Differential Privacy PATE and ALIBI"
  ☆30Updated 2 years ago
• Machine-Learning-Security-Lab / mia_prune
  Membership Inference Attacks and Defenses in Neural Network Pruning
  ☆28Updated 2 years ago
• inspire-group / membership-inference-evaluation
  Systematic Evaluation of Membership Inference Privacy Risks of Machine Learning Models
  ☆125Updated 9 months ago
• jagielski / auditing-dpsgd
  Code for Auditing DPSGD
  ☆38Updated 2 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
• csong27 / membership-inference
  Code for Membership Inference Attack against Machine Learning Models (in Oakland 2017)
  ☆192Updated 7 years ago