cleverhans-lab / verifiable-unlearningLinks
☆21Updated 2 years ago
Alternatives and similar repositories for verifiable-unlearning
Users that are interested in verifiable-unlearning are comparing it to the libraries listed below
Sorting:
- ☆28Updated 2 years ago
- Code for Exploiting Unintended Feature Leakage in Collaborative Learning (in Oakland 2019)☆54Updated 6 years ago
- Code to reproduce experiments in "Antipodes of Label Differential Privacy PATE and ALIBI"☆32Updated 3 years ago
- Implementation of calibration bounds for differential privacy in the shuffle model☆21Updated 4 years ago
- ☆54Updated 2 years ago
- Privacy attacks on Split Learning☆42Updated 3 years ago
- ☆45Updated 5 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.☆74Updated last year
- A sybil-resilient distributed learning protocol.☆104Updated last month
- Official implementation of "Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective"☆57Updated 2 years ago
- ☆80Updated 3 years ago
- ☆37Updated 3 years ago
- A simple Python implementation of a secure aggregation protocole for federated learning.☆35Updated 2 years ago
- Learning from history for Byzantine Robustness☆25Updated 4 years ago
- [NeurIPS 2022] JAX/Haiku implementation of "On Privacy and Personalization in Cross-Silo Federated Learning"☆27Updated 2 years ago
- Distributed Momentum for Byzantine-resilient Stochastic Gradient Descent (ICLR 2021)☆22Updated 4 years ago
- Code for NDSS 2021 Paper "Manipulating the Byzantine: Optimizing Model Poisoning Attacks and Defenses Against Federated Learning"☆148Updated 3 years ago
- This repo implements several algorithms for learning with differential privacy.☆109Updated 2 years ago
- ☆50Updated 4 years ago
- DP-FTRL from "Practical and Private (Deep) Learning without Sampling or Shuffling" for centralized training.☆30Updated 4 months ago
- Fast, memory-efficient, scalable optimization of deep learning with differential privacy☆131Updated 2 months ago
- Code release for MPCViT accepted by ICCV 2023☆16Updated 9 months ago
- Membership Inference, Attribute Inference and Model Inversion attacks implemented using PyTorch.☆64Updated last year
- [CCS 2021] "DataLens: Scalable Privacy Preserving Training via Gradient Compression and Aggregation" by Boxin Wang*, Fan Wu*, Yunhui Long…☆38Updated 3 years ago
- Analytic calibration for differential privacy with Gaussian perturbations☆50Updated 7 years ago
- Eluding Secure Aggregation in Federated Learning via Model Inconsistency☆12Updated 2 years ago
- Byzantine-resilient distributed SGD with TensorFlow.☆40Updated 4 years ago
- Code & supplementary material of the paper Label Inference Attacks Against Federated Learning on Usenix Security 2022.☆83Updated 2 years ago
- Code for Auditing DPSGD☆37Updated 3 years ago