Alternatives and similar repositories for ML-Leaks:

Users that are interested in ML-Leaks 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
• inspire-group / membership-inference-evaluation
  Systematic Evaluation of Membership Inference Privacy Risks of Machine Learning Models
  ☆125Updated 11 months ago
• csong27 / membership-inference
  Code for Membership Inference Attack against Machine Learning Models (in Oakland 2017)
  ☆194Updated 7 years ago
• jinyuan-jia / MemGuard
  ☆45Updated 5 years ago
• liuyugeng / ML-Doctor
  Code for ML Doctor
  ☆88Updated 6 months ago
• hyhmia / BlindMI
  ☆23Updated 2 years ago
• csong27 / property-inference-collaborative-ml
  Code for Exploiting Unintended Feature Leakage in Collaborative Learning (in Oakland 2019)
  ☆53Updated 5 years 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
• yziqi / adversarial-model-inversion
  Code for "Neural Network Inversion in Adversarial Setting via Background Knowledge Alignment" (CCS 2019)
  ☆46Updated 5 years ago
• spring-epfl / mia
  A library for running membership inference attacks against ML models
  ☆142Updated 2 years ago
• shrebox / Privacy-Attacks-in-Machine-Learning
  Membership Inference, Attribute Inference and Model Inversion attacks implemented using PyTorch.
  ☆58Updated 5 months ago
• DingfanChen / GAN-Leaks
  Official implementation of "GAN-Leaks: A Taxonomy of Membership Inference Attacks against Generative Models" (CCS 2020)
  ☆47Updated 2 years ago
• pasquini-dario / SplitNN_FSHA
  Privacy attacks on Split Learning
  ☆38Updated 3 years ago
• FuChong-cyber / label-inference-attacks
  Code & supplementary material of the paper Label Inference Attacks Against Federated Learning on Usenix Security 2022.
  ☆83Updated last year
• jhcknzzm / Federated-Learning-Backdoor
  ICML 2022 code for "Neurotoxin: Durable Backdoors in Federated Learning" https://arxiv.org/abs/2206.10341
  ☆70Updated last year
• ashafahi / inceptionv3-transferLearn-poison
  Attacking a dog vs fish classification that uses transfer learning inceptionV3
  ☆70Updated 6 years ago
• ksreenivasan / OOD_Federated_Learning
  ☆69Updated 2 years ago
• bargavj / EvaluatingDPML
  This project's goal is to evaluate the privacy leakage of differentially private machine learning models.
  ☆131Updated 2 years ago
• naiyeleo / ABS
  ABS: Scanning Neural Networks for Back-doors by Artificial Brain Stimulation
  ☆50Updated 2 years ago
• BielStela / membership_inference
  Python package to create adversarial agents for membership inference attacks againts machine learning models
  ☆46Updated 6 years ago
• kangliucn / Fine-pruning-defense
  Fine-Pruning: Defending Against Backdooring Attacks on Deep Neural Networks (RAID 2018)
  ☆47Updated 6 years ago
• facebookresearch / label_dp_antipodes
  Code to reproduce experiments in "Antipodes of Label Differential Privacy PATE and ALIBI"
  ☆30Updated 2 years ago
• DingfanChen / RelaxLoss
  Official implementation of "RelaxLoss: Defending Membership Inference Attacks without Losing Utility" (ICLR 2022)
  ☆48Updated 2 years ago
• Unispac / Subnet-Replacement-Attack
  Official implementation of (CVPR 2022 Oral) Towards Practical Deployment-Stage Backdoor Attack on Deep Neural Networks.
  ☆26Updated 2 years ago
• csong27 / ml-model-remember
  Code for Machine Learning Models that Remember Too Much (in CCS 2017)
  ☆30Updated 7 years ago
• AI-secure / GMI-Attack
  ☆26Updated 3 years ago
• MinChen00 / UnlearningLeaks
  Official implementation of "When Machine Unlearning Jeopardizes Privacy" (ACM CCS 2021)
  ☆46Updated 2 years ago
• PatrickZH / Improved-Deep-Leakage-from-Gradients
  The code for "Improved Deep Leakage from Gradients" (iDLG).
  ☆148Updated 4 years ago
• jinghuichen / Focused-Flip-Federated-Backdoor-Attack
  Github Repo for AAAI 2023 paper: On the Vulnerability of Backdoor Defenses for Federated Learning
  ☆37Updated last year