Alternatives and similar repositories for black-box-ripper:

Users that are interested in black-box-ripper are comparing it to the libraries listed below

• cleverhans-lab / dataset-inference
  [ICLR'21] Dataset Inference for Ownership Resolution in Machine Learning
  ☆32Updated 2 years ago
• shrezaei / MI-Attack
  ☆31Updated 6 months ago
• uclaml / RayS
  RayS: A Ray Searching Method for Hard-label Adversarial Attack (KDD2020)
  ☆56Updated 4 years ago
• tribhuvanesh / prediction-poisoning
  Prediction Poisoning: Towards Defenses Against DNN Model Stealing Attacks (ICLR '20)
  ☆28Updated 4 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
• 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
• MadryLab / backdoor_data_poisoning
  ☆25Updated 6 years ago
• DingfanChen / RelaxLoss
  Official implementation of "RelaxLoss: Defending Membership Inference Attacks without Losing Utility" (ICLR 2022)
  ☆48Updated 2 years ago
• snu-mllab / parsimonious-blackbox-attack
  Official TensorFlow implementation of "Parsimonious Black-Box Adversarial Attacks via Efficient Combinatorial Optimization" (ICML 2019)
  ☆40Updated 4 years ago
• wielandbrendel / adaptive_attacks_paper
  Code for "On Adaptive Attacks to Adversarial Example Defenses"
  ☆86Updated 4 years ago
• vtddggg / CAA
  The implementation of our paper: Composite Adversarial Attacks (AAAI2021)
  ☆30Updated 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
  ☆33Updated 5 years ago
• eth-sri / adaptive-auto-attack
  ☆23Updated 3 years ago
• Machine-Learning-Security-Lab / mia_prune
  Membership Inference Attacks and Defenses in Neural Network Pruning
  ☆28Updated 2 years ago
• hsouri / Sleeper-Agent
  ☆65Updated last year
• ganeshdg95 / Leveraging-Adversarial-Examples-to-Quantify-Membership-Information-Leakage
  ☆19Updated 2 years ago
• inspire-group / privacy-vs-robustness
  Privacy Risks of Securing Machine Learning Models against Adversarial Examples
  ☆44Updated 5 years ago
• wronnyhuang / metapoison
  Craft poisoned data using MetaPoison
  ☆50Updated 3 years ago
• tml-epfl / adv-training-corruptions
  On the effectiveness of adversarial training against common corruptions [UAI 2022]
  ☆30Updated 2 years ago
• YiZeng623 / I-BAU
  Official Implementation of ICLR 2022 paper, ``Adversarial Unlearning of Backdoors via Implicit Hypergradient''
  ☆54Updated 2 years ago
• Haichao-Zhang / FeatureScatter
  Feature Scattering Adversarial Training (NeurIPS19)
  ☆72Updated 9 months ago
• Bai-Li / STN-Code
  Code for Stability Training with Noise (STN)
  ☆21Updated 4 years ago
• AI-secure / Meta-Nerual-Trojan-Detection
  ☆64Updated 4 years ago
• zhuchen03 / ConvexPolytopePosioning
  ConvexPolytopePosioning
  ☆35Updated 5 years ago
• yunyuntsai / DNN-Model-Stealing
  Code for "CloudLeak: Large-Scale Deep Learning Models Stealing Through Adversarial Examples" (NDSS 2020)
  ☆20Updated 4 years ago
• cassidylaidlaw / perceptual-advex
  Code and data for the ICLR 2021 paper "Perceptual Adversarial Robustness: Defense Against Unseen Threat Models".
  ☆55Updated 3 years ago
• DequanWang / dent
  Fighting Gradients with Gradients: Dynamic Defenses against Adversarial Attacks
  ☆38Updated 3 years ago
• aks2203 / poisoning-benchmark
  A unified benchmark problem for data poisoning attacks
  ☆153Updated last year
• ftramer / MultiRobustness
  Code for the paper "Adversarial Training and Robustness for Multiple Perturbations", NeurIPS 2019
  ☆47Updated 2 years ago
• Ping-C / certifiedpatchdefense
  Repository for Certified Defenses for Adversarial Patch ICLR-2020
  ☆32Updated 4 years ago