Alternatives and similar repositories for Poisoning-Attacks-with-Back-gradient-Optimization:

Users that are interested in Poisoning-Attacks-with-Back-gradient-Optimization are comparing it to the libraries listed below

• shrezaei / MI-Attack
  ☆31Updated 5 months ago
• cleverhans-lab / entangled-watermark
  ☆44Updated 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
  ☆32Updated 4 years ago
• kangliucn / Fine-pruning-defense
  Fine-Pruning: Defending Against Backdooring Attacks on Deep Neural Networks (RAID 2018)
  ☆46Updated 6 years ago
• tribhuvanesh / prediction-poisoning
  Prediction Poisoning: Towards Defenses Against DNN Model Stealing Attacks (ICLR '20)
  ☆29Updated 4 years ago
• jinyuan-jia / MemGuard
  ☆45Updated 5 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
• cchoquette / membership-inference
  Code for the paper: Label-Only Membership Inference Attacks
  ☆64Updated 3 years ago
• AI-secure / Robustness-Against-Backdoor-Attacks
  RAB: Provable Robustness Against Backdoor Attacks
  ☆39Updated last year
• Machine-Learning-Security-Lab / mia_prune
  Membership Inference Attacks and Defenses in Neural Network Pruning
  ☆28Updated 2 years ago
• hyhmia / BlindMI
  ☆23Updated 2 years ago
• DingfanChen / RelaxLoss
  Official implementation of "RelaxLoss: Defending Membership Inference Attacks without Losing Utility" (ICLR 2022)
  ☆48Updated 2 years ago
• ganeshdg95 / Leveraging-Adversarial-Examples-to-Quantify-Membership-Information-Leakage
  ☆20Updated last year
• wronnyhuang / metapoison
  Craft poisoned data using MetaPoison
  ☆49Updated 3 years ago
• ksreenivasan / OOD_Federated_Learning
  ☆68Updated 2 years ago
• nthu-datalab / On.the.Trade-off.between.Adversarial.and.Backdoor.Robustness
  Code for "On the Trade-off between Adversarial and Backdoor Robustness" (NIPS 2020)
  ☆17Updated 4 years ago
• liuyugeng / ML-Doctor
  Code for ML Doctor
  ☆85Updated 6 months ago
• inspire-group / privacy-vs-robustness
  Privacy Risks of Securing Machine Learning Models against Adversarial Examples
  ☆44Updated 5 years ago
• naiyeleo / ABS
  ABS: Scanning Neural Networks for Back-doors by Artificial Brain Stimulation
  ☆49Updated 2 years ago
• cleverhans-lab / dataset-inference
  [ICLR'21] Dataset Inference for Ownership Resolution in Machine Learning
  ☆32Updated 2 years ago
• inspire-group / unlearning-verification
  verifying machine unlearning by backdooring
  ☆19Updated last year
• garrisongys / STRIP
  This is for releasing the source code of the ACSAC paper "STRIP: A Defence Against Trojan Attacks on Deep Neural Networks"
  ☆54Updated 3 months ago
• AI-secure / Meta-Nerual-Trojan-Detection
  ☆64Updated 4 years ago
• GeorgePisl / backdoor-attacks-based-on-deep-learning
  Implementation of Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning paper
  ☆20Updated 4 years ago
• ashafahi / inceptionv3-transferLearn-poison
  Attacking a dog vs fish classification that uses transfer learning inceptionV3
  ☆70Updated 6 years ago
• neeharperi / DeepKNNDefense
  KNN Defense Against Clean Label Poisoning Attacks
  ☆12Updated 3 years ago
• MadryLab / label-consistent-backdoor-code
  Code for "Label-Consistent Backdoor Attacks"
  ☆52Updated 4 years ago
• DennisLiu2022 / Membership-Inference-Attacks-by-Exploiting-Loss-Trajectory
  ☆24Updated 2 years ago
• csong27 / ml-model-remember
  Code for Machine Learning Models that Remember Too Much (in CCS 2017)
  ☆30Updated 7 years ago
• SPIN-UMass / ML-Privacy-Regulization
  ☆26Updated 6 years ago