ftramer / Handcrafted-DP
☆80Updated 2 years ago
Alternatives and similar repositories for Handcrafted-DP:
Users that are interested in Handcrafted-DP are comparing it to the libraries listed below
- Code for Auditing DPSGD☆37Updated 3 years ago
- Code to reproduce experiments in "Antipodes of Label Differential Privacy PATE and ALIBI"☆31Updated 3 years ago
- Algorithms for Privacy-Preserving Machine Learning in JAX☆94Updated 2 weeks ago
- A fast algorithm to optimally compose privacy guarantees of differentially private (DP) mechanisms to arbitrary accuracy.☆73Updated last year
- ☆15Updated last year
- This project's goal is to evaluate the privacy leakage of differentially private machine learning models.☆133Updated 2 years ago
- [CCS 2021] "DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation" by Boxin Wang*, Fan Wu*, Yunhui Long…☆37Updated 3 years ago
- This repo implements several algorithms for learning with differential privacy.☆108Updated 2 years ago
- simple Differential Privacy in PyTorch☆48Updated 4 years ago
- Code for Exploiting Unintended Feature Leakage in Collaborative Learning (in Oakland 2019)☆53Updated 5 years ago
- Code for "Differential Privacy Has Disparate Impact on Model Accuracy" NeurIPS'19☆34Updated 3 years ago
- ☆45Updated 5 years ago
- Implementation of the paper : "Membership Inference Attacks Against Machine Learning Models", Shokri et al.☆60Updated 5 years ago
- Code for the CSF 2018 paper "Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting"☆37Updated 6 years ago
- ☆31Updated 8 months ago
- A library for running membership inference attacks against ML models☆144Updated 2 years ago
- ☆24Updated 3 years ago
- Analytic calibration for differential privacy with Gaussian perturbations☆47Updated 6 years ago
- Fast, memory-efficient, scalable optimization of deep learning with differential privacy☆120Updated 3 months ago
- Code to accompany the paper "Deep Learning with Gaussian Differential Privacy"☆33Updated 4 years ago
- Code for the paper: Label-Only Membership Inference Attacks☆65Updated 3 years ago
- Systematic Evaluation of Membership Inference Privacy Risks of Machine Learning Models☆125Updated last year
- ☆65Updated 5 years ago
- R-GAP: Recursive Gradient Attack on Privacy [Accepted at ICLR 2021]☆36Updated 2 years ago
- autodp: A flexible and easy-to-use package for differential privacy☆275Updated last year
- Membership Inference Attacks and Defenses in Neural Network Pruning☆28Updated 2 years ago
- CRFL: Certifiably Robust Federated Learning against Backdoor Attacks (ICML 2021)☆73Updated 3 years ago
- Robust aggregation for federated learning with the RFA algorithm.☆48Updated 2 years ago
- A codebase that makes differentially private training of transformers easy.☆170Updated 2 years ago
- Official implementation of "RelaxLoss: Defending Membership Inference Attacks without Losing Utility" (ICLR 2022)☆49Updated 2 years ago