SPIN-UMass / FRL
Code for USENIX Security 2023 Paper "Every Vote Counts: Ranking-Based Training of Federated Learning to Resist Poisoning Attacks"
☆17Updated 6 months ago
Related projects ⓘ
Alternatives and complementary repositories for FRL
- ICML 2022 code for "Neurotoxin: Durable Backdoors in Federated Learning" https://arxiv.org/abs/2206.10341☆63Updated last year
- ☆45Updated last year
- [Usenix Security 2024] Official code implementation of "BackdoorIndicator: Leveraging OOD Data for Proactive Backdoor Detection in Federa…☆27Updated last month
- ☆16Updated last year
- Code & supplementary material of the paper Label Inference Attacks Against Federated Learning on Usenix Security 2022.☆79Updated last year
- 基于《A Little Is Enough: Circumventing Defenses For Distributed Learning》的联邦学习攻击模型☆61Updated 4 years ago
- The official code of KDD22 paper "FLDetecotor: Defending Federated Learning Against Model Poisoning Attacks via Detecting Malicious Clien…☆74Updated last year
- Code for NDSS 2021 Paper "Manipulating the Byzantine: Optimizing Model Poisoning Attacks and Defenses Against Federated Learning"☆135Updated 2 years ago
- ☆22Updated 9 months ago
- ☆65Updated 2 years ago
- ☆34Updated 3 years ago
- ☆53Updated last year
- ☆38Updated 3 years ago
- Multi-metrics adaptively identifies backdoors in Federated learning☆22Updated 11 months ago
- Backdoor detection in Federated learning with similarity measurement☆20Updated 2 years ago
- This is the code for our paper `Robust Federated Learning with Attack-Adaptive Aggregation' accepted by FTL-IJCAI'21.☆43Updated last year
- CRFL: Certifiably Robust Federated Learning against Backdoor Attacks (ICML 2021)☆71Updated 3 years ago
- Official implementation of "Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective"☆55Updated last year
- ☆12Updated 5 months ago
- ☆37Updated 9 months ago
- Blades: A Unified Benchmark Suite for Byzantine Attacks and Defenses in Federated Learning☆133Updated 3 months ago
- Local Differential Privacy for Federated Learning☆16Updated 2 years ago
- ☆32Updated 2 years ago
- Code for Data Poisoning Attacks Against Federated Learning Systems☆169Updated 3 years ago
- PyTorch implementation of Security-Preserving Federated Learning via Byzantine-Sensitive Triplet Distance☆31Updated last month
- reproduce the FLTrust model based on the paper "FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping"☆26Updated last year
- [ICLR 2023, Best Paper Award at ECCV’22 AROW Workshop] FLIP: A Provable Defense Framework for Backdoor Mitigation in Federated Learning☆44Updated last year
- ☆36Updated last year
- Eluding Secure Aggregation in Federated Learning via Model Inconsistency☆12Updated last year