{"total":18,"rows":[{"id":"2311.06750","title":"Federated Learning for Generalization, Robustness, Fairness: A Survey and Benchmark","created":"2023-11-12","cited_by_count":99,"area":null},{"id":"2310.13424","title":"FLTracer: Accurate Poisoning Attack Provenance in Federated Learning","created":"2023-10-20","cited_by_count":8,"area":null},{"id":"2509.20383","title":"MARS: A Malignity-Aware Backdoor Defense in Federated Learning","created":"2025-09-21","cited_by_count":7,"area":null},{"id":"2409.14805","title":"SDBA: A Stealthy and Long-Lasting Durable Backdoor Attack in Federated Learning","created":"2024-09-23","cited_by_count":2,"area":null},{"id":"2508.13730","title":"On the Security and Privacy of Federated Learning: A Survey with Attacks, Defenses, Frameworks, Applications, and Future Directions","created":"2025-08-19","cited_by_count":2,"area":null},{"id":"2310.00616","title":"Towards Understanding Adversarial Transferability in Federated Learning","created":"2023-10-01","cited_by_count":1,"area":null},{"id":"2407.07917","title":"Non-Cooperative Backdoor Attacks in Federated Learning: A New Threat Landscape","created":"2024-07-05","cited_by_count":1,"area":null},{"id":"2411.16167","title":"Mind the Cost of Scaffold! Benign Clients May Even Become Accomplices of Backdoor Attack","created":"2024-11-25","cited_by_count":1,"area":null},{"id":"2501.15005","title":"DBA-DFL: Towards Distributed Backdoor Attacks with Network Detection in Decentralized Federated Learning","created":"2025-01-25","cited_by_count":1,"area":null},{"id":"2505.10297","title":"Defending the Edge: Representative-Attention Defense against Backdoor Attacks in Federated Learning","created":"2025-05-15","cited_by_count":1,"area":null},{"id":"2507.04903","title":"BackFed: An Efficient & Standardized Benchmark Suite for Backdoor Attacks in Federated Learning","created":"2025-07-07","cited_by_count":1,"area":null},{"id":"2309.00127","title":"FTA: Stealthy and Adaptive Backdoor Attack with Flexible Triggers on Federated Learning","created":"2023-08-31","cited_by_count":0,"area":null},{"id":"2407.00719","title":"A Whole-Process Certifiably Robust Aggregation Method Against Backdoor Attacks in Federated Learning","created":"2024-06-30","cited_by_count":0,"area":null},{"id":"2504.15674","title":"TrojanDam: Detection-Free Backdoor Defense in Federated Learning through Proactive Model Robustification utilizing OOD Data","created":"2025-04-22","cited_by_count":0,"area":null},{"id":"2508.02115","title":"Coward: Collision-based OOD Watermarking for Practical Proactive Federated Backdoor Detection","created":"2025-08-04","cited_by_count":0,"area":null},{"id":"2508.04064","title":"FLAT: Revealing Hidden Latent-Conditioned Backdoor Failures in Federated Learning","created":"2025-08-06","cited_by_count":0,"area":null},{"id":"2509.18904","title":"Enhancing the Effectiveness and Durability of Backdoor Attacks in Federated Learning through Maximizing Task Distinction","created":"2025-09-23","cited_by_count":0,"area":null},{"id":"2603.28652","title":"Mitigating Backdoor Attacks in Federated Learning Using PPA and MiniMax Game Theory","created":"2026-03-30","cited_by_count":0,"area":null}],"next_cursor":null}