Alternatives and similar repositories for mia_prune

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

• cchoquette / membership-inference
  Code for the paper: Label-Only Membership Inference Attacks
  ☆66Updated 3 years ago
• DingfanChen / RelaxLoss
  Official implementation of "RelaxLoss: Defending Membership Inference Attacks without Losing Utility" (ICLR 2022)
  ☆50Updated 3 years ago
• shrezaei / MI-Attack
  ☆32Updated 11 months ago
• ganeshdg95 / Leveraging-Adversarial-Examples-to-Quantify-Membership-Information-Leakage
  ☆19Updated 2 years ago
• inspire-group / MIAdefenseSELENA
  [USENIX Security 2022] Mitigating Membership Inference Attacks by Self-Distillation Through a Novel Ensemble Architecture
  ☆16Updated 2 years ago
• MinChen00 / UnlearningLeaks
  Official implementation of "When Machine Unlearning Jeopardizes Privacy" (ACM CCS 2021)
  ☆48Updated 3 years ago
• AdrienBenamira / membership_inference_attack
  Implementation of the paper : "Membership Inference Attacks Against Machine Learning Models", Shokri et al.
  ☆58Updated 6 years ago
• DennisLiu2022 / Membership-Inference-Attacks-by-Exploiting-Loss-Trajectory
  ☆24Updated 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 last year
• DingfanChen / GAN-Leaks
  Official implementation of "GAN-Leaks: A Taxonomy of Membership Inference Attacks against Generative Models" (CCS 2020)
  ☆48Updated 3 years ago
• cleverhans-lab / dataset-inference
  [ICLR'21] Dataset Inference for Ownership Resolution in Machine Learning
  ☆32Updated 2 years ago
• liuyugeng / ML-Doctor
  Code for ML Doctor
  ☆91Updated last year
• SPIN-UMass / ML-Privacy-Regulization
  ☆26Updated 6 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.
  ☆63Updated 10 months ago
• ksreenivasan / OOD_Federated_Learning
  ☆70Updated 3 years ago
• zhenglisec / Label-Only-MIA
  ☆19Updated 11 months 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
• 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
• bboylyg / NAD
  This is an implementation demo of the ICLR 2021 paper [Neural Attention Distillation: Erasing Backdoor Triggers from Deep Neural Networks…
  ☆122Updated 3 years ago
• zhuohangli / GGL
  A pytorch implementation of the paper "Auditing Privacy Defenses in Federated Learning via Generative Gradient Leakage".
  ☆59Updated 2 years ago
• wronnyhuang / metapoison
  Craft poisoned data using MetaPoison
  ☆53Updated 4 years ago
• cleverhans-lab / entangled-watermark
  ☆48Updated 4 years ago
• vrt1shjwlkr / AAAI21-MIA-Defense
  Code for AAAI 2021 Paper "Membership Privacy for Machine Learning Models Through Knowledge Transfer"
  ☆11Updated 4 years ago
• hsouri / Sleeper-Agent
  ☆66Updated last year
• 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
• lhfowl / robbing_the_fed
  ☆25Updated 3 years ago
• superrrpotato / Defending-Neural-Backdoors-via-Generative-Distribution-Modeling
  The code is for our NeurIPS 2019 paper: https://arxiv.org/abs/1910.04749
  ☆34Updated 5 years ago
• tribhuvanesh / prediction-poisoning
  Prediction Poisoning: Towards Defenses Against DNN Model Stealing Attacks (ICLR '20)
  ☆32Updated 4 years ago
• PatrickZH / Improved-Deep-Leakage-from-Gradients
  The code for "Improved Deep Leakage from Gradients" (iDLG).
  ☆153Updated 4 years ago