warisgill / FedDefenderLinks
FedDefender is a novel defense mechanism designed to safeguard Federated Learning from the poisoning attacks (i.e., backdoor attacks).
☆15Updated last year
Alternatives and similar repositories for FedDefender
Users that are interested in FedDefender are comparing it to the libraries listed below
Sorting:
- The official code of KDD22 paper "FLDetecotor: Defending Federated Learning Against Model Poisoning Attacks via Detecting Malicious Clien…☆84Updated 2 years ago
- PyTorch implementation of Security-Preserving Federated Learning via Byzantine-Sensitive Triplet Distance☆34Updated last year
- Official repository of the paper "Dynamic Defense Against Byzantine Poisoning Attacks in Federated Learning".☆12Updated 3 years ago
- ☆15Updated last year
- Official implementation of "FL-WBC: Enhancing Robustness against Model Poisoning Attacks in Federated Learning from a Client Perspective"…☆43Updated 4 years ago
- Code for Data Poisoning Attacks Against Federated Learning Systems☆203Updated 4 years ago
- [ICLR 2023, Best Paper Award at ECCV’22 AROW Workshop] FLIP: A Provable Defense Framework for Backdoor Mitigation in Federated Learning☆60Updated 11 months ago
- reproduce the FLTrust model based on the paper "FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping"☆32Updated 2 years ago
- Code for NDSS 2021 Paper "Manipulating the Byzantine: Optimizing Model Poisoning Attacks and Defenses Against Federated Learning"☆147Updated 3 years ago
- Official implementation of "Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective"☆57Updated 2 years ago
- Github Repo for AAAI 2023 paper: On the Vulnerability of Backdoor Defenses for Federated Learning☆40Updated 2 years ago
- ☆43Updated 2 years ago
- ☆24Updated 2 weeks ago
- ☆24Updated 3 years ago
- ☆55Updated 2 years ago
- This is the code for our paper `Robust Federated Learning with Attack-Adaptive Aggregation' accepted by FTL-IJCAI'21.☆46Updated 2 years ago
- ☆38Updated 4 years ago
- Code & supplementary material of the paper Label Inference Attacks Against Federated Learning on Usenix Security 2022.☆87Updated 2 years ago
- ☆16Updated 2 years ago
- The code of AAAI-21 paper titled "Defending against Backdoors in Federated Learning with Robust Learning Rate".☆34Updated 3 years ago
- A backdoor defense for federated learning via isolated subspace training (NeurIPS2023)☆28Updated last year
- Federated Learning and Membership Inference Attacks experiments on CIFAR10☆23Updated 5 years ago
- [Usenix Security 2024] Official code implementation of "BackdoorIndicator: Leveraging OOD Data for Proactive Backdoor Detection in Federa…☆47Updated 2 months ago
- Adversarial attacks and defenses against federated learning.☆20Updated 2 years ago
- IBA: Towards Irreversible Backdoor Attacks in Federated Learning (Poster at NeurIPS 2023)☆38Updated 2 months ago
- ☆13Updated 3 years ago
- ☆70Updated 3 years ago
- Differentially Private Federated Learning on Heterogeneous Data☆69Updated 3 years ago
- ☆55Updated 2 years ago
- ☆39Updated last year