facebookresearch / label_dp_antipodesLinks
Code to reproduce experiments in "Antipodes of Label Differential Privacy PATE and ALIBI"
☆32Updated 3 years ago
Alternatives and similar repositories for label_dp_antipodes
Users that are interested in label_dp_antipodes are comparing it to the libraries listed below
Sorting:
- Code for Auditing DPSGD☆37Updated 3 years ago
- This repo implements several algorithms for learning with differential privacy.☆109Updated 2 years ago
- ☆80Updated 3 years ago
- This project's goal is to evaluate the privacy leakage of differentially private machine learning models.☆135Updated 2 years ago
- A fast algorithm to optimally compose privacy guarantees of differentially private (DP) mechanisms to arbitrary accuracy.☆73Updated last year
- Implementation of the paper : "Membership Inference Attacks Against Machine Learning Models", Shokri et al.☆58Updated 6 years ago
- Membership Inference, Attribute Inference and Model Inversion attacks implemented using PyTorch.☆63Updated 10 months ago
- ☆45Updated 5 years ago
- The code for "Improved Deep Leakage from Gradients" (iDLG).☆153Updated 4 years ago
- Code for Exploiting Unintended Feature Leakage in Collaborative Learning (in Oakland 2019)☆54Updated 6 years ago
- A library for running membership inference attacks against ML models☆149Updated 2 years ago
- Code for Membership Inference Attack against Machine Learning Models (in Oakland 2017)☆194Updated 7 years ago
- Algorithms to recover input data from their gradient signal through a neural network☆301Updated 2 years ago
- Code for the paper: Label-Only Membership Inference Attacks☆66Updated 3 years ago
- [CCS 2021] "DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation" by Boxin Wang*, Fan Wu*, Yunhui Long…☆38Updated 3 years ago
- Systematic Evaluation of Membership Inference Privacy Risks of Machine Learning Models☆127Updated last year
- Code for the paper "ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models"☆84Updated 3 years ago
- ☆15Updated last year
- ☆15Updated 2 years ago
- CRFL: Certifiably Robust Federated Learning against Backdoor Attacks (ICML 2021)☆73Updated 4 years ago
- Amortized version of the differentially private SGD algorithm published in "Deep Learning with Differential Privacy" by Abadi et al. Enfo…☆40Updated last year
- Privacy attacks on Split Learning☆42Updated 3 years ago
- simple Differential Privacy in PyTorch☆48Updated 5 years ago
- Code for "Analyzing Federated Learning through an Adversarial Lens" https://arxiv.org/abs/1811.12470☆151Updated 2 years ago
- ☆32Updated 11 months ago
- [NeurIPS 2021] "G-PATE: Scalable Differentially Private Data Generator via Private Aggregation of Teacher Discriminators" by Yunhui Long*…☆30Updated 3 years ago
- Official implementation of "When Machine Unlearning Jeopardizes Privacy" (ACM CCS 2021)☆48Updated 3 years ago
- DBA: Distributed Backdoor Attacks against Federated Learning (ICLR 2020)☆196Updated 4 years ago
- Official implementation of "Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective"☆57Updated 2 years ago
- The code of AAAI-21 paper titled "Defending against Backdoors in Federated Learning with Robust Learning Rate".☆34Updated 2 years ago