csl-cqu / awesome-secure-federated-learning-papersLinks
☆28Updated 2 years ago
Alternatives and similar repositories for awesome-secure-federated-learning-papers
Users that are interested in awesome-secure-federated-learning-papers are comparing it to the libraries listed below
Sorting:
- Code for Exploiting Unintended Feature Leakage in Collaborative Learning (in Oakland 2019)☆56Updated 6 years ago
- Code for ML Doctor☆91Updated last year
- Code for the paper: Label-Only Membership Inference Attacks☆66Updated 4 years ago
- Code for the paper "ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models"☆85Updated 4 years ago
- ☆46Updated 6 years ago
- FLTracer: Accurate Poisoning Attack Provenance in Federated Learning☆23Updated last year
- Code & supplementary material of the paper Label Inference Attacks Against Federated Learning on Usenix Security 2022.☆88Updated 2 years ago
- ☆25Updated 4 years ago
- Privacy attacks on Split Learning☆42Updated 4 years ago
- The code for "Improved Deep Leakage from Gradients" (iDLG).☆162Updated 4 years ago
- Code for Membership Inference Attack against Machine Learning Models (in Oakland 2017)☆200Updated 8 years ago
- Systematic Evaluation of Membership Inference Privacy Risks of Machine Learning Models☆133Updated last year
- Code for Machine Learning Models that Remember Too Much (in CCS 2017)☆31Updated 8 years ago
- ☆55Updated 2 years ago
- Privacy Risks of Securing Machine Learning Models against Adversarial Examples☆46Updated 6 years ago
- This is a python script to generate nice bibtex file for latex.☆17Updated 5 years ago
- ABS: Scanning Neural Networks for Back-doors by Artificial Brain Stimulation☆51Updated 3 years ago
- ☆30Updated 5 years ago
- CVPR 2021 Official repository for the Data-Free Model Extraction paper. https://arxiv.org/abs/2011.14779☆75Updated last year
- CRFL: Certifiably Robust Federated Learning against Backdoor Attacks (ICML 2021)☆73Updated 4 years ago
- ☆70Updated 3 years ago
- Membership Inference, Attribute Inference and Model Inversion attacks implemented using PyTorch.☆67Updated last year
- The code of AAAI-21 paper titled "Defending against Backdoors in Federated Learning with Robust Learning Rate".☆35Updated 3 years ago
- This project's goal is to evaluate the privacy leakage of differentially private machine learning models.☆135Updated 3 years ago
- Official implementation of "Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective"☆57Updated 2 years ago
- Code for "Analyzing Federated Learning through an Adversarial Lens" https://arxiv.org/abs/1811.12470☆152Updated 3 years ago
- ☆51Updated 4 years ago
- Membership Inference Attacks and Defenses in Neural Network Pruning☆28Updated 3 years ago
- ICML 2022 code for "Neurotoxin: Durable Backdoors in Federated Learning" https://arxiv.org/abs/2206.10341☆77Updated 2 years ago
- ☆36Updated 3 years ago