| SoK: Benchmarking Poisoning Attacks and Defenses in Federated Learning | Feb 6, 2025 | BenchmarkingData Poisoning | CodeCode Available | 2 |
| FedDefender: Client-Side Attack-Tolerant Federated Learning | Jul 18, 2023 | Federated LearningKnowledge Distillation | CodeCode Available | 1 |
| Chameleon: Adapting to Peer Images for Planting Durable Backdoors in Federated Learning | Apr 25, 2023 | Contrastive LearningFederated Learning | CodeCode Available | 1 |
| FLDetector: Defending Federated Learning Against Model Poisoning Attacks via Detecting Malicious Clients | Jul 19, 2022 | Federated LearningModel Poisoning | CodeCode Available | 1 |
| FedRecAttack: Model Poisoning Attack to Federated Recommendation | Apr 1, 2022 | Federated Learningmodel | CodeCode Available | 1 |
| BEAS: Blockchain Enabled Asynchronous & Secure Federated Machine Learning | Feb 6, 2022 | Anomaly DetectionBIG-bench Machine Learning | CodeCode Available | 1 |
| ARFED: Attack-Resistant Federated averaging based on outlier elimination | Nov 8, 2021 | Data PoisoningFederated Learning | CodeCode Available | 1 |
| FL-WBC: Enhancing Robustness against Model Poisoning Attacks in Federated Learning from a Client Perspective | Oct 26, 2021 | Federated LearningModel Poisoning | CodeCode Available | 1 |
| Byzantine-robust Federated Learning through Collaborative Malicious Gradient Filtering | Sep 13, 2021 | Federated LearningModel Poisoning | CodeCode Available | 1 |
| Back to the Drawing Board: A Critical Evaluation of Poisoning Attacks on Production Federated Learning | Aug 23, 2021 | Federated LearningMisconceptions | CodeCode Available | 1 |
