| SoK: Benchmarking Poisoning Attacks and Defenses in Federated Learning | Feb 6, 2025 | BenchmarkingData Poisoning | CodeCode Available | 2 | 5 |
| FedDefender: Client-Side Attack-Tolerant Federated Learning | Jul 18, 2023 | Federated LearningKnowledge Distillation | CodeCode Available | 1 | 5 |
| How To Backdoor Federated Learning | Jul 2, 2018 | Anomaly DetectionData Poisoning | CodeCode Available | 1 | 5 |
| Chameleon: Adapting to Peer Images for Planting Durable Backdoors in Federated Learning | Apr 25, 2023 | Contrastive LearningFederated Learning | CodeCode Available | 1 | 5 |
| BEAS: Blockchain Enabled Asynchronous & Secure Federated Machine Learning | Feb 6, 2022 | Anomaly DetectionBIG-bench Machine Learning | CodeCode Available | 1 | 5 |
| ARFED: Attack-Resistant Federated averaging based on outlier elimination | Nov 8, 2021 | Data PoisoningFederated Learning | CodeCode Available | 1 | 5 |
| Robust Federated Learning with Attack-Adaptive Aggregation | Feb 10, 2021 | Federated LearningModel Poisoning | CodeCode Available | 1 | 5 |
| Byzantine-robust Federated Learning through Collaborative Malicious Gradient Filtering | Sep 13, 2021 | Federated LearningModel Poisoning | CodeCode Available | 1 | 5 |
| FL-WBC: Enhancing Robustness against Model Poisoning Attacks in Federated Learning from a Client Perspective | Oct 26, 2021 | Federated LearningModel Poisoning | CodeCode Available | 1 | 5 |
| FLDetector: Defending Federated Learning Against Model Poisoning Attacks via Detecting Malicious Clients | Jul 19, 2022 | Federated LearningModel Poisoning | CodeCode Available | 1 | 5 |
| FedRecAttack: Model Poisoning Attack to Federated Recommendation | Apr 1, 2022 | Federated Learningmodel | CodeCode Available | 1 | 5 |
| Ditto: Fair and Robust Federated Learning Through Personalization | Dec 8, 2020 | FairnessFederated Learning | CodeCode Available | 1 | 5 |
| Analyzing Federated Learning through an Adversarial Lens | Nov 29, 2018 | Federated LearningModel Poisoning | CodeCode Available | 1 | 5 |
| Back to the Drawing Board: A Critical Evaluation of Poisoning Attacks on Production Federated Learning | Aug 23, 2021 | Federated LearningMisconceptions | CodeCode Available | 1 | 5 |
| Semi-Targeted Model Poisoning Attack on Federated Learning via Backward Error Analysis | Mar 22, 2022 | Backdoor AttackFederated Learning | CodeCode Available | 0 | 5 |
| On the Security Risks of AutoML | Oct 12, 2021 | AutoMLModel Poisoning | CodeCode Available | 0 | 5 |
| Mitigating Sybils in Federated Learning Poisoning | Aug 14, 2018 | DiversityFederated Learning | CodeCode Available | 0 | 5 |
| Leverage Variational Graph Representation For Model Poisoning on Federated Learning | Apr 23, 2024 | Federated LearningModel Poisoning | CodeCode Available | 0 | 5 |
| MPAF: Model Poisoning Attacks to Federated Learning based on Fake Clients | Mar 16, 2022 | Federated LearningModel Poisoning | CodeCode Available | 0 | 5 |
| FedSECA: Sign Election and Coordinate-wise Aggregation of Gradients for Byzantine Tolerant Federated Learning | Nov 6, 2024 | Federated LearningModel Poisoning | CodeCode Available | 0 | 5 |
| A Novel Defense Against Poisoning Attacks on Federated Learning: LayerCAM Augmented with Autoencoder | Jun 2, 2024 | Federated LearningModel Poisoning | CodeCode Available | 0 | 5 |
| EAB-FL: Exacerbating Algorithmic Bias through Model Poisoning Attacks in Federated Learning | Oct 2, 2024 | FairnessFederated Learning | CodeCode Available | 0 | 5 |
| Exploring the Limits of Model-Targeted Indiscriminate Data Poisoning Attacks | Mar 7, 2023 | Data PoisoningModel Poisoning | CodeCode Available | 0 | 5 |
| Defending Against Sophisticated Poisoning Attacks with RL-based Aggregation in Federated Learning | Jun 20, 2024 | Federated LearningModel Poisoning | CodeCode Available | 0 | 5 |
| Dual Defense: Enhancing Privacy and Mitigating Poisoning Attacks in Federated Learning | Feb 8, 2025 | Anomaly DetectionFederated Learning | CodeCode Available | 0 | 5 |
