yashkant / model-inversion-attack
Implementation of the Model Inversion Attack introduced with Model Inversion Attacks that Exploit Confidence Information and Basic Countermeasures (Fredrikson Et al.)
☆85Updated 2 years ago
Alternatives and similar repositories for model-inversion-attack
Users that are interested in model-inversion-attack are comparing it to the libraries listed below
Sorting:
- 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"☆37Updated 6 years ago
- Code for the paper "ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models"☆84Updated 3 years ago
- Code for Exploiting Unintended Feature Leakage in Collaborative Learning (in Oakland 2019)☆53Updated 5 years ago
- Implementation of the paper : "Membership Inference Attacks Against Machine Learning Models", Shokri et al.☆60Updated 6 years ago
- Code for Membership Inference Attack against Machine Learning Models (in Oakland 2017)☆193Updated 7 years ago
- Systematic Evaluation of Membership Inference Privacy Risks of Machine Learning Models☆126Updated last year
- Implementation of membership inference and model inversion attacks, extracting training data information from an ML model. Benchmarking …☆103Updated 5 years ago
- ☆45Updated 5 years ago
- Code for "Neural Network Inversion in Adversarial Setting via Background Knowledge Alignment" (CCS 2019)☆46Updated 5 years ago
- Code for the paper: Label-Only Membership Inference Attacks☆65Updated 3 years ago
- Code for Machine Learning Models that Remember Too Much (in CCS 2017)☆30Updated 7 years ago
- A library for running membership inference attacks against ML models☆147Updated 2 years ago
- Example of the attack described in the paper "Towards Poisoning of Deep Learning Algorithms with Back-gradient Optimization"☆21Updated 5 years ago
- ABS: Scanning Neural Networks for Back-doors by Artificial Brain Stimulation☆51Updated 2 years ago
- Fine-Pruning: Defending Against Backdooring Attacks on Deep Neural Networks (RAID 2018)☆47Updated 6 years ago
- Code for ML Doctor☆87Updated 9 months ago
- Membership Inference, Attribute Inference and Model Inversion attacks implemented using PyTorch.☆61Updated 7 months ago
- Attacking a dog vs fish classification that uses transfer learning inceptionV3☆70Updated 7 years ago
- This project's goal is to evaluate the privacy leakage of differentially private machine learning models.☆134Updated 2 years ago
- Prediction Poisoning: Towards Defenses Against DNN Model Stealing Attacks (ICLR '20)☆30Updated 4 years ago
- simple Differential Privacy in PyTorch☆48Updated 4 years ago
- ☆23Updated 2 years ago
- Input Purification Defense Against Trojan Attacks on Deep Neural Network Systems☆27Updated 4 years ago
- ☆66Updated 5 years ago
- This is for releasing the source code of the ACSAC paper "STRIP: A Defence Against Trojan Attacks on Deep Neural Networks"☆57Updated 6 months ago
- Official implementation of "When Machine Unlearning Jeopardizes Privacy" (ACM CCS 2021)☆47Updated 2 years ago
- Implementation of Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning paper☆20Updated 4 years ago
- ☆31Updated 4 years ago
- privacy preserving deep learning☆15Updated 7 years ago