columbia / pixeldp
☆64Updated 5 years ago
Alternatives and similar repositories for pixeldp:
Users that are interested in pixeldp are comparing it to the libraries listed below
- Privacy Risks of Securing Machine Learning Models against Adversarial Examples☆44Updated 5 years ago
- Code for the CSF 2018 paper "Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting"☆38Updated 6 years ago
- ☆45Updated 5 years ago
- Implementation of the Model Inversion Attack introduced with Model Inversion Attacks that Exploit Confidence Information and Basic Counte…☆83Updated 2 years ago
- Code for Auditing DPSGD☆37Updated 3 years ago
- Code for Machine Learning Models that Remember Too Much (in CCS 2017)☆30Updated 7 years ago
- Implementation of membership inference and model inversion attacks, extracting training data information from an ML model. Benchmarking …☆103Updated 5 years ago
- Attacking a dog vs fish classification that uses transfer learning inceptionV3☆70Updated 7 years ago
- Systematic Evaluation of Membership Inference Privacy Risks of Machine Learning Models☆125Updated last year
- Code for the IEEE S&P 2018 paper 'Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning'☆53Updated 4 years ago
- Code for the paper "ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models"☆83Updated 3 years ago
- Code for Exploiting Unintended Feature Leakage in Collaborative Learning (in Oakland 2019)☆53Updated 5 years ago
- This repo keeps track of popular provable training and verification approaches towards robust neural networks, including leaderboards on …☆99Updated 2 years ago
- This project's goal is to evaluate the privacy leakage of differentially private machine learning models.☆131Updated 2 years ago
- ☆26Updated 6 years ago
- A united toolbox for running major robustness verification approaches for DNNs. [S&P 2023]☆89Updated 2 years ago
- ☆23Updated 2 years ago
- ☆31Updated 7 months ago
- Fine-Pruning: Defending Against Backdooring Attacks on Deep Neural Networks (RAID 2018)☆48Updated 6 years ago
- A library for running membership inference attacks against ML models☆143Updated 2 years ago
- A unified benchmark problem for data poisoning attacks☆155Updated last year
- Prediction Poisoning: Towards Defenses Against DNN Model Stealing Attacks (ICLR '20)☆30Updated 4 years ago
- code for model-targeted poisoning☆12Updated last year
- Code for "Neural Network Inversion in Adversarial Setting via Background Knowledge Alignment" (CCS 2019)☆46Updated 5 years ago
- ABS: Scanning Neural Networks for Back-doors by Artificial Brain Stimulation☆50Updated 2 years ago
- Code for "On the Trade-off between Adversarial and Backdoor Robustness" (NIPS 2020)☆17Updated 4 years ago
- Code for the paper: Label-Only Membership Inference Attacks☆65Updated 3 years ago
- Public implementation of ICML'19 paper "White-box vs Black-box: Bayes Optimal Strategies for Membership Inference"☆16Updated 4 years ago
- Code for Membership Inference Attack against Machine Learning Models (in Oakland 2017)☆193Updated 7 years ago
- Code to reproduce experiments in "Antipodes of Label Differential Privacy PATE and ALIBI"☆31Updated 2 years ago