stratosphereips / awesome-ml-privacy-attacks
An awesome list of papers on privacy attacks against machine learning
☆598Updated last year
Alternatives and similar repositories for awesome-ml-privacy-attacks:
Users that are interested in awesome-ml-privacy-attacks are comparing it to the libraries listed below
- Privacy Meter: An open-source library to audit data privacy in statistical and machine learning algorithms.☆646Updated last week
- ☆330Updated 2 months ago
- Code for Membership Inference Attack against Machine Learning Models (in Oakland 2017)☆193Updated 7 years ago
- A library for running membership inference attacks against ML models☆144Updated 2 years ago
- Systematic Evaluation of Membership Inference Privacy Risks of Machine Learning Models☆125Updated last year
- Backdoors Framework for Deep Learning and Federated Learning. A light-weight tool to conduct your research on backdoors.☆361Updated 2 years ago
- autodp: A flexible and easy-to-use package for differential privacy☆275Updated last year
- TrojanZoo provides a universal pytorch platform to conduct security researches (especially backdoor attacks/defenses) of image classifica…☆291Updated 8 months ago
- Privacy Testing for Deep Learning☆204Updated last year
- Breaching privacy in federated learning scenarios for vision and text☆288Updated last year
- [arXiv:2411.10023] "Model Inversion Attacks: A Survey of Approaches and Countermeasures"☆170Updated last month
- ☆314Updated 3 months ago
- A curated list of academic events on AI Security & Privacy☆150Updated 8 months ago
- Differential private machine learning☆191Updated 3 years ago
- This project's goal is to evaluate the privacy leakage of differentially private machine learning models.☆133Updated 2 years ago
- ☆186Updated last year
- ☆144Updated 6 months ago
- Security and Privacy Risk Simulator for Machine Learning (arXiv:2312.17667)☆388Updated 2 weeks ago
- Source code for paper "How to Backdoor Federated Learning" (https://arxiv.org/abs/1807.00459)☆295Updated 9 months ago
- Implementation of membership inference and model inversion attacks, extracting training data information from an ML model. Benchmarking …☆103Updated 5 years ago
- Differentially Private Optimization for PyTorch 👁🙅♀️☆186Updated 4 years ago
- Fast, memory-efficient, scalable optimization of deep learning with differential privacy☆120Updated 3 months ago
- Code for Data Poisoning Attacks Against Federated Learning Systems☆191Updated 3 years ago
- Algorithms to recover input data from their gradient signal through a neural network☆287Updated 2 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
- list of differential-privacy related resources☆308Updated 3 months ago
- A curated list of Meachine learning Security & Privacy papers published in security top-4 conferences (IEEE S&P, ACM CCS, USENIX Security…☆261Updated 5 months ago
- A codebase that makes differentially private training of transformers easy.☆170Updated 2 years ago
- Code implementation of the paper "Neural Cleanse: Identifying and Mitigating Backdoor Attacks in Neural Networks", at IEEE Security and P…☆285Updated 5 years ago
- Code for ML Doctor☆87Updated 8 months ago