{"total":98,"rows":[{"id":"2307.10616","title":"Heterogeneous Federated Learning: State-of-the-art and Research Challenges","created":"2023-07-20","cited_by_count":161,"area":null},{"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":"2211.02408","title":"Rickrolling the Artist: Injecting Backdoors into Text Encoders for Text-to-Image Synthesis","created":"2022-11-04","cited_by_count":59,"area":"safety"},{"id":"2301.01299","title":"Recent Advances on Federated Learning: A Systematic Survey","created":"2023-01-03","cited_by_count":41,"area":null},{"id":"2303.02213","title":"Backdoor Attacks and Defenses in Federated Learning: Survey, Challenges and Future Research Directions","created":"2023-03-03","cited_by_count":33,"area":null},{"id":"2403.00871","title":"Teach LLMs to Phish: Stealing Private Information from Language Models","created":"2024-03-01","cited_by_count":32,"area":null},{"id":"2301.08170","title":"On the Vulnerability of Backdoor Defenses for Federated Learning","created":"2023-01-19","cited_by_count":27,"area":null},{"id":"2312.04432","title":"FreqFed: A Frequency Analysis-Based Approach for Mitigating Poisoning Attacks in Federated Learning","created":"2023-12-07","cited_by_count":27,"area":null},{"id":"2304.12961","title":"Chameleon: Adapting to Peer Images for Planting Durable Backdoors in Federated Learning","created":"2023-04-25","cited_by_count":21,"area":null},{"id":"2306.04959","title":"FedSecurity: Benchmarking Attacks and Defenses in Federated Learning and Federated LLMs","created":"2023-06-08","cited_by_count":21,"area":null},{"id":"2302.09457","title":"Attacks in Adversarial Machine Learning: A Systematic Survey from the Life-cycle Perspective","created":"2023-02-19","cited_by_count":20,"area":null},{"id":"2407.19845","title":"BackdoorBench: A Comprehensive Benchmark and Analysis of Backdoor Learning","created":"2024-07-29","cited_by_count":19,"area":null},{"id":"2308.04466","title":"Backdoor Federated Learning by Poisoning Backdoor-Critical Layers","created":"2023-08-08","cited_by_count":18,"area":null},{"id":"2312.08667","title":"Data and Model Poisoning Backdoor Attacks on Wireless Federated Learning, and the Defense Mechanisms: A Comprehensive Survey","created":"2023-12-14","cited_by_count":18,"area":null},{"id":"2302.01677","title":"Revisiting Personalized Federated Learning: Robustness Against Backdoor Attacks","created":"2023-02-03","cited_by_count":16,"area":null},{"id":"2501.17381","title":"Do We Really Need to Design New Byzantine-robust Aggregation Rules?","created":"2025-01-29","cited_by_count":15,"area":null},{"id":"2304.10638","title":"Get Rid Of Your Trail: Remotely Erasing Backdoors in Federated Learning","created":"2023-04-20","cited_by_count":13,"area":null},{"id":"2503.07978","title":"Detecting Backdoor Attacks in Federated Learning via Direction Alignment Inspection","created":"2025-03-11","cited_by_count":13,"area":null},{"id":"2410.02159","title":"Mitigating Memorization In Language Models","created":"2024-10-03","cited_by_count":12,"area":"safety"},{"id":"2304.08847","title":"BadVFL: Backdoor Attacks in Vertical Federated Learning","created":"2023-04-18","cited_by_count":10,"area":null},{"id":"2306.04984","title":"G$^2$uardFL: Safeguarding Federated Learning Against Backdoor Attacks through Attributed Client Graph Clustering","created":"2023-06-08","cited_by_count":9,"area":null},{"id":"2311.16065","title":"A Survey on Vulnerability of Federated Learning: A Learning Algorithm Perspective","created":"2023-11-27","cited_by_count":9,"area":null},{"id":"2210.07376","title":"ScionFL: Efficient and Robust Secure Quantized Aggregation","created":"2022-10-13","cited_by_count":8,"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":"2306.10746","title":"Practical and General Backdoor Attacks against Vertical Federated Learning","created":"2023-06-19","cited_by_count":6,"area":null},{"id":"2406.06207","title":"Lurking in the shadows: Unveiling Stealthy Backdoor Attacks against Personalized Federated Learning","created":"2024-06-10","cited_by_count":6,"area":null},{"id":"2308.09490","title":"Balancing Transparency and Risk: The Security and Privacy Risks of Open-Source Machine Learning Models","created":"2023-08-18","cited_by_count":5,"area":null},{"id":"2405.20975","title":"ACE: A Model Poisoning Attack on Contribution Evaluation Methods in Federated Learning","created":"2024-05-31","cited_by_count":5,"area":null},{"id":"2410.11205","title":"Adversarially Guided Stateful Defense Against Backdoor Attacks in Federated Deep Learning","created":"2024-10-15","cited_by_count":5,"area":null},{"id":"2307.15971","title":"You Can Backdoor Personalized Federated Learning","created":"2023-07-29","cited_by_count":4,"area":null},{"id":"2411.01040","title":"Identify Backdoored Model in Federated Learning via Individual Unlearning","created":"2024-11-01","cited_by_count":4,"area":null},{"id":"2303.00302","title":"Mitigating Backdoors in Federated Learning with FLD","created":"2023-03-01","cited_by_count":3,"area":null},{"id":"2306.08011","title":"Privacy Inference-Empowered Stealthy Backdoor Attack on Federated Learning under Non-IID Scenarios","created":"2023-06-13","cited_by_count":3,"area":null},{"id":"2401.01168","title":"FedQV: Leveraging Quadratic Voting in Federated Learning","created":"2024-01-02","cited_by_count":3,"area":null},{"id":"2406.10884","title":"Linkage on Security, Privacy and Fairness in Federated Learning: New Balances and New Perspectives","created":"2024-06-16","cited_by_count":3,"area":null},{"id":"2407.09658","title":"BoBa: Boosting Backdoor Detection through Data Distribution Inference in Federated Learning","created":"2024-07-12","cited_by_count":3,"area":null},{"id":"2409.10764","title":"Federated Learning for Smart Grid: A Survey on Applications and Potential Vulnerabilities","created":"2024-09-16","cited_by_count":3,"area":null},{"id":"2302.09904","title":"WW-FL: Secure and Private Large-Scale Federated Learning","created":"2023-02-20","cited_by_count":2,"area":null},{"id":"2310.04055","title":"Kick Bad Guys Out! Conditionally Activated Anomaly Detection in Federated Learning with Zero-Knowledge Proof Verification","created":"2023-10-06","cited_by_count":2,"area":"safety"},{"id":"2407.11372","title":"UNIT: Backdoor Mitigation via Automated Neural Distribution Tightening","created":"2024-07-16","cited_by_count":2,"area":null},{"id":"2407.15389","title":"Poisoning with A Pill: Circumventing Detection in Federated Learning","created":"2024-07-22","cited_by_count":2,"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":"2412.03441","title":"PBP: Post-training Backdoor Purification for Malware Classifiers","created":"2024-12-04","cited_by_count":2,"area":null},{"id":"2501.12736","title":"Bad-PFL: Exploring Backdoor Attacks against Personalized Federated Learning","created":"2025-01-22","cited_by_count":2,"area":null},{"id":"2502.16545","title":"Multi-Target Federated Backdoor Attack Based on Feature Aggregation","created":"2025-02-23","cited_by_count":2,"area":null},{"id":"2311.05826","title":"Honest Score Client Selection Scheme: Preventing Federated Learning Label Flipping Attacks in Non-IID Scenarios","created":"2023-11-10","cited_by_count":1,"area":"safety"},{"id":"2311.12715","title":"Attacks on fairness in Federated Learning","created":"2023-11-21","cited_by_count":1,"area":"safety"},{"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":"2406.19753","title":"Attack On Prompt: Backdoor Attack in Prompt-Based Continual Learning","created":"2024-06-28","cited_by_count":1,"area":"safety"},{"id":"2407.03144","title":"Venomancer: Towards Imperceptible and Target-on-Demand Backdoor Attacks in Federated Learning","created":"2024-07-03","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":"2408.14240","title":"Celtibero: Robust Layered Aggregation for Federated Learning","created":"2024-08-26","cited_by_count":1,"area":null},{"id":"2410.06509","title":"PFAttack: Stealthy Attack Bypassing Group Fairness in Federated Learning","created":"2024-10-09","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":"2502.07011","title":"DROP: Poison Dilution via Knowledge Distillation for Federated Learning","created":"2025-02-10","cited_by_count":1,"area":"safety"},{"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":"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":"2509.13219","title":"On the Out-of-Distribution Backdoor Attack for Federated Learning","created":"2025-09-16","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":"2605.21115","title":"Automated Byzantine-Resilient Clustered Decentralized Federated Learning for Battery Intelligence in Connected EVs","created":"2026-05-20","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":"2401.15002","title":"BackdoorBench: A Comprehensive Benchmark and Analysis of Backdoor Learning","created":"2024-01-26","cited_by_count":0,"area":null},{"id":"2403.02437","title":"A Survey on Federated Unlearning: Challenges and Opportunities","created":"2024-03-04","cited_by_count":0,"area":"safety"},{"id":"2408.13773","title":"SAB:A Stealing and Robust Backdoor Attack based on Steganographic Algorithm against Federated Learning","created":"2024-08-25","cited_by_count":0,"area":null},{"id":"2409.15067","title":"SHFL: Secure Hierarchical Federated Learning Framework for Edge Networks","created":"2024-09-23","cited_by_count":0,"area":"safety"},{"id":"2411.03926","title":"Act in Collusion: Distributed Multi-Target Backdoor Attacks in Federated Learning","created":"2024-11-06","cited_by_count":0,"area":null},{"id":"2412.10605","title":"Client-Side Patching against Backdoor Attacks in Federated Learning","created":"2024-12-13","cited_by_count":0,"area":null},{"id":"2501.19143","title":"Imitation Game for Adversarial Disillusion with Chain-of-Thought Reasoning in Generative AI","created":"2025-01-31","cited_by_count":0,"area":"lr"},{"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":"2506.11413","title":"Byzantine Outside, Curious Inside: Reconstructing Data Through Malicious Updates","created":"2025-06-13","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":"2511.09252","title":"Unveiling Hidden Threats: Using Fractal Triggers to Boost Stealthiness of Distributed Backdoor Attacks in Federated Learning","created":"2025-11-12","cited_by_count":0,"area":null},{"id":"2511.14406","title":"Watch Out for the Lifespan: Evaluating Backdoor Attacks Against Federated Model Adaptation","created":"2025-11-18","cited_by_count":0,"area":null},{"id":"2601.01833","title":"FAROS: Robust Federated Learning with Adaptive Scaling against Backdoor Attacks","created":"2026-01-05","cited_by_count":0,"area":null},{"id":"2603.10075","title":"TASER: Task-Aware Spectral Energy Refine for Backdoor Suppression in UAV Swarms Decentralized Federated Learning","created":"2026-03-10","cited_by_count":0,"area":null},{"id":"2603.10692","title":"Repurposing Backdoors for Good: Ephemeral Intrinsic Proofs for Verifiable Aggregation in Cross-silo Federated Learning","created":"2026-03-11","cited_by_count":0,"area":null},{"id":"2603.18538","title":"Beyond Passive Aggregation: Active Auditing and Topology-Aware Defense in Decentralized Federated Learning","created":"2026-03-19","cited_by_count":0,"area":"safety"},{"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},{"id":"2606.09548","title":"Model Poisoning Against Federated Model Adaptation with Chain of Bit-Flips","created":"2026-06-08","cited_by_count":0,"area":"safety"},{"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},{"id":"2606.25858","title":"Color Matters: Trigger Color Affects Success in Federated Backdoor Attacks","created":"2026-06-24","cited_by_count":0,"area":null},{"id":"2607.06643","title":"The Power of Backdoor Absorption in Community Training","created":"2026-07-07","cited_by_count":0,"area":null},{"id":"2607.07314","title":"FedCVESA: Taking Away Training Data in Federated Learning via Correlation Value Encoding and Segmented Aggregation","created":"2026-07-08","cited_by_count":0,"area":null},{"id":"2607.19674","title":"FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense","created":"2026-07-22","cited_by_count":0,"area":"safety"},{"id":"2607.26933","title":"Defending Against Backdoor Attacks via Alignment Checking in Model-Contrastive Federated Learning","created":"2026-07-29","cited_by_count":0,"area":null},{"id":"2608.01095","title":"FL-OA: A Byzantine-Robust Federated Learning Framework with Outsourced Auditing for Intelligent Devices","created":"2026-08-02","cited_by_count":0,"area":null},{"id":"2608.14861","title":"STAR-FL: Secure Federated Learning with Spatial-Temporal Analysis and Robust Aggregation","created":"2026-08-14","cited_by_count":0,"area":"safety"},{"id":"2608.21137","title":"BackDFL: A Unified Benchmark For Backdoor Attacks and Defenses In Decentralized Federated Learning","created":"2026-08-21","cited_by_count":0,"area":null},{"id":"2608.23952","title":"STAIN-FL: Stealthy Targeted Attack Injection with Contextual Triggers in Federated Learning","created":"2026-08-25","cited_by_count":0,"area":"safety"},{"id":"2609.01495","title":"Optimizing Byzantine Node Placement in Decentralized Federated Learning","created":"2026-09-01","cited_by_count":0,"area":null},{"id":"2609.02450","title":"CACTUS: Mask-Guided Semantic Clean-Label Backdoors in Decentralized Federated Learning","created":"2026-09-02","cited_by_count":0,"area":null},{"id":"2609.07147","title":"Fine-grained Distributed Backdoor Attacks in Federated Learning","created":"2026-09-07","cited_by_count":0,"area":null},{"id":"2609.27760","title":"Backdoors Leave Structural Traces: FedMAST for Backdoor Detection and Containment in Federated Learning","created":"2026-09-04","cited_by_count":0,"area":null},{"id":"2609.40312","title":"Compression Footprints as Security Signals for Model-Poisoning Defense in Federated Learning","created":"2026-09-30","cited_by_count":0,"area":null}],"next_cursor":null}