trailofbits / PrivacyRavenLinks
Privacy Testing for Deep Learning
☆206Updated 2 years ago
Alternatives and similar repositories for PrivacyRaven
Users that are interested in PrivacyRaven are comparing it to the libraries listed below
Sorting:
- PhD/MSc course on Machine Learning Security (Univ. Cagliari)☆210Updated 2 months ago
- Privacy Meter: An open-source library to audit data privacy in statistical and machine learning algorithms.☆669Updated 3 months ago
- An awesome list of papers on privacy attacks against machine learning☆616Updated last year
- ARMORY Adversarial Robustness Evaluation Test Bed☆182Updated last year
- Implementation of membership inference and model inversion attacks, extracting training data information from an ML model. Benchmarking …☆103Updated 5 years ago
- ☆127Updated 3 years ago
- A Python library for Secure and Explainable Machine Learning☆184Updated last month
- ☆146Updated 9 months ago
- A library for running membership inference attacks against ML models☆148Updated 2 years ago
- Backdoors Framework for Deep Learning and Federated Learning. A light-weight tool to conduct your research on backdoors.☆369Updated 2 years ago
- autodp: A flexible and easy-to-use package for differential privacy☆274Updated last year
- ☆52Updated 4 years ago
- Security and Privacy Risk Simulator for Machine Learning (arXiv:2312.17667)☆399Updated last month
- Statistical Counterexample Detector for Differential Privacy☆28Updated last year
- A repository to quickly generate synthetic data and associated trojaned deep learning models☆78Updated 2 years ago
- Honest-but-Curious Nets: Sensitive Attributes of Private Inputs Can Be Secretly Coded into the Classifiers' Outputs (ACM CCS'21)☆17Updated 2 years ago
- This project's goal is to evaluate the privacy leakage of differentially private machine learning models.☆135Updated 2 years ago
- Federated Learning Utilities and Tools for Experimentation☆190Updated last year
- ☆38Updated 3 years ago
- Differentially Private Optimization for PyTorch 👁🙅♀️☆186Updated 5 years ago
- Copycat CNN☆27Updated last year
- Systematic Evaluation of Membership Inference Privacy Risks of Machine Learning Models☆127Updated last year
- CaPC is a method that enables collaborating parties to improve their own local heterogeneous machine learning models in a setting where b…☆26Updated 3 years ago
- ☆39Updated 2 years ago
- A toolbox for differentially private data generation☆132Updated 2 years ago
- a CLI that provides a generic automation layer for assessing the security of ML models☆874Updated 2 weeks ago
- UCLANesl - NIST Differential Privacy Challenge (Match 3)☆24Updated 6 years ago
- A Simulator for Privacy Preserving Federated Learning☆94Updated 4 years ago
- ☆23Updated last year
- Model extraction attacks on Machine-Learning-as-a-Service platforms.☆350Updated 4 years ago