| Denial-of-Service or Fine-Grained Control: Towards Flexible Model Poisoning Attacks on Federated Learning | Apr 21, 2023 | Federated LearningModel Poisoning | —Unverified | 0 | 0 |
| Backdoor Attacks in Federated Learning by Rare Embeddings and Gradient Ensembling | Apr 29, 2022 | Federated LearningModel Poisoning | —Unverified | 0 | 0 |
| Data and Model Poisoning Backdoor Attacks on Wireless Federated Learning, and the Defense Mechanisms: A Comprehensive Survey | Dec 14, 2023 | Data PoisoningFederated Learning | —Unverified | 0 | 0 |
| Data-Agnostic Model Poisoning against Federated Learning: A Graph Autoencoder Approach | Nov 30, 2023 | Federated LearningModel Poisoning | —Unverified | 0 | 0 |
| A Synergetic Attack against Neural Network Classifiers combining Backdoor and Adversarial Examples | Sep 3, 2021 | Federated LearningModel Poisoning | —Unverified | 0 | 0 |
| Covert Model Poisoning Against Federated Learning: Algorithm Design and Optimization | Jan 28, 2021 | Federated LearningModel Poisoning | —Unverified | 0 | 0 |
| Turning Federated Learning Systems Into Covert Channels | Apr 21, 2021 | Federated LearningModel Poisoning | —Unverified | 0 | 0 |
| A Streamlit-based Artificial Intelligence Trust Platform for Next-Generation Wireless Networks | Oct 25, 2022 | Model PoisoningSelf-Learning | —Unverified | 0 | 0 |
| A First Order Meta Stackelberg Method for Robust Federated Learning | Jun 23, 2023 | Federated LearningMeta-Learning | —Unverified | 0 | 0 |
| Protecting Federated Learning from Extreme Model Poisoning Attacks via Multidimensional Time Series Anomaly Detection | Mar 29, 2023 | Anomaly DetectionFederated Learning | —Unverified | 0 | 0 |
