{"total":15,"rows":[{"id":"2412.07454","title":"Tazza: Shuffling Neural Network Parameters for Secure and Private Federated Learning","created":"2024-12-10","cited_by_count":2,"area":null},{"id":"2405.06206","title":"Concealing Backdoor Model Updates in Federated Learning by Trigger-Optimized Data Poisoning","created":"2024-05-10","cited_by_count":1,"area":null},{"id":"2412.10537","title":"VerifiableFL: Verifiable Claims for Federated Learning using Exclaves","created":"2024-12-13","cited_by_count":1,"area":null},{"id":"2503.23288","title":"Two Heads Are Better than One: Model-Weight and Latent-Space Analysis for Federated Learning on Non-iid Data against Poisoning Attacks","created":"2025-03-30","cited_by_count":1,"area":null},{"id":"2605.11122","title":"FedSurrogate: Backdoor Defense in Federated Learning via Layer Criticality and Surrogate Replacement","created":"2026-05-11","cited_by_count":1,"area":null},{"id":"2503.23511","title":"Buffer is All You Need: Defending Federated Learning against Backdoor Attacks under Non-iids via Buffering","created":"2025-03-30","cited_by_count":0,"area":null},{"id":"2507.02376","title":"On the Inference (In-)Security of Vertical Federated Learning: Efficient Auditing against Inference Tampering Attack","created":"2025-07-03","cited_by_count":0,"area":null},{"id":"2507.12127","title":"Self-Adaptive and Robust Federated Spectrum Sensing without Benign Majority for Cellular Networks","created":"2025-07-16","cited_by_count":0,"area":null},{"id":"2507.21177","title":"FedBAP: Backdoor Defense via Benign Adversarial Perturbation in Federated Learning","created":"2025-07-26","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":"2509.05833","title":"Benchmarking Robust Aggregation in Decentralized Gradient Marketplaces","created":"2025-09-06","cited_by_count":0,"area":null},{"id":"2509.23190","title":"CoSIFL: Collaborative Secure and Incentivized Federated Learning with Differential Privacy","created":"2025-09-27","cited_by_count":0,"area":null},{"id":"2604.03862","title":"SecureAFL: Secure Asynchronous Federated Learning","created":"2026-04-04","cited_by_count":0,"area":null},{"id":"2605.22506","title":"EnCAgg: Enhanced Clustering Aggregation for Robust Federated Learning against Dynamic Model Poisoning","created":"2026-05-21","cited_by_count":0,"area":null},{"id":"2606.17035","title":"Your Privacy My Cloak: Backdoor Attacks on Differentially Private Federated Learning","created":"2026-06-15","cited_by_count":0,"area":null}],"next_cursor":null}