| Can We Trust the Similarity Measurement in Federated Learning? | Oct 20, 2023 | Federated LearningModel Poisoning | —Unverified | 0 |
| A Client-level Assessment of Collaborative Backdoor Poisoning in Non-IID Federated Learning | Apr 17, 2025 | Federated LearningModel Poisoning | —Unverified | 0 |
| 2CP: Decentralized Protocols to Transparently Evaluate Contributivity in Blockchain Federated Learning Environments | Nov 15, 2020 | Federated LearningModel Poisoning | —Unverified | 0 |
| FedCC: Robust Federated Learning against Model Poisoning Attacks | Dec 5, 2022 | Federated Learningmodel | —Unverified | 0 |
| CADeSH: Collaborative Anomaly Detection for Smart Homes | Mar 2, 2023 | Anomaly DetectionIntrusion Detection | —Unverified | 0 |
| Exact Support Recovery in Federated Regression with One-shot Communication | Jun 22, 2020 | Distributed ComputingFederated Learning | —Unverified | 0 |
| An Analysis of Untargeted Poisoning Attack and Defense Methods for Federated Online Learning to Rank Systems | Jul 4, 2023 | Federated LearningLearning-To-Rank | —Unverified | 0 |
| FedCom: A Byzantine-Robust Local Model Aggregation Rule Using Data Commitment for Federated Learning | Apr 16, 2021 | Data PoisoningFederated Learning | —Unverified | 0 |
| Federated Learning: Balancing the Thin Line Between Data Intelligence and Privacy | Apr 22, 2022 | Data PoisoningFederated Learning | —Unverified | 0 |
| Resilience in Online Federated Learning: Mitigating Model-Poisoning Attacks via Partial Sharing | Mar 19, 2024 | Federated LearningModel Poisoning | —Unverified | 0 |
