Backdoor Attacks in Federated Learning

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Overview

These attacks exploit local training and model aggregation to implant behavior that produces a target prediction when a trigger appears, often while preserving accuracy on ordinary inputs. Methods range from poisoned examples and patch triggers to semantic or contextual triggers, distributed and triggerless attacks, and updates designed to evade aggregation rules; studies span image, text, graph, vertical, and decentralized settings with heterogeneous clients. Defenses include robust aggregation such as Krum and trimmed mean, update anomaly and alignment checks, structural or spectral analysis, client reputation, active auditing, and post-training unlearning, measured by attack success alongside clean accuracy and false positives. A central tension is that stealthy adaptive attacks can evade defenses, especially under non-IID data, privacy constraints, or varied network topologies, while aggressive filtering can harm utility; realistic threat models and reproducible cross-setting evaluations remain important.

Latest papers

CardsList

32 papers4 papers in the last four weeks, up 33% on the four weeks before. 0.0% of all new papers.

  1. ShadowFPT: Backdooring Federated Prompt Tuning via Shadow Triggers

    Oct 16, 2026Kun Zhai, Teng Li, Yunhao Feng +1Backdoor Attacks in Federated LearningBackdoor Attacks on VLMs

    Fudan University, Shanghai, China · Alibaba Group, Hangzhou, China

  2. Federated Art Chase: Privacy Leakage and Data Poisoning in Federated Fine-Tuning

    Oct 15, 2026Vasileios Perifanis, Nikolaos PavlidisFederated LearningFederated Fine-Tuning

    Indigma Innovations Greece

  3. FedGraph: Defending Federated Large Language Model Fine-Tuning Against Backdoor Attacks via Graph-Based Aggregation

    Oct 13, 2026Xi Chen, Chunyi Zhou, Rui Zeng +3Backdoor Attacks in Federated LearningLLM Backdoor Attacks

    Zhejiang University, Hangzhou, China

  4. DecoyTrace: Toxic Decoys for Active Defense in Decentralized Federated Learning

    Sep 28, 2026Pedro Beltrán-López, Enrique Tomás Martínez Beltrán, Pantaleone Nespoli +2Byzantine-Robust Federated LearningBackdoor Attacks in Federated Learning

    Department of Information and Communication Engineering, University of Murcia, Murcia, 30100, Spain

  5. Fine-grained Distributed Backdoor Attacks in Federated Learning

    Sep 7, 2026Jian Wang, Hong Shen, Wei Ke +1Backdoor Attacks in Federated LearningFederated Learning

    Faculty of Applied Sciences, Macao Polytechnic University, R. de Luís Gonzaga Gomes, Macao, 999078, China · Faculty of Cyberspace Security, Guangzhou University of Software, No.548 Guangcong South Road, High-tech Industrial Park, Conghua Economic Development Zone, Guangzhou, 501900, China · School of Engineering and Technology, Central Queensland University, Bruce Highway, Norman Gardens, Rockhampton, Queensland, 4702, Australia +1

  6. Backdoors Leave Structural Traces: FedMAST for Backdoor Detection and Containment in Federated Learning

    Sep 4, 2026Srinivasan Subramanian, Md. Abdullah Al Hafiz Khan, Kazi Aminul IslamFederated Learning AggregationByzantine-Robust Federated Learning

    Department of Computer Science Kennesaw State University Marietta, USA

  7. CACTUS: Mask-Guided Semantic Clean-Label Backdoors in Decentralized Federated Learning

    Sep 2, 2026Chao Feng, Burkhard StillerBackdoor AttacksBackdoor Attacks in Federated Learning

    Communication Systems Group, Department of Informatics University of Zurich, Switzerland

  8. STAIN-FL: Stealthy Targeted Attack Injection with Contextual Triggers in Federated Learning

    Aug 25, 2026Ashlinder Kaur, Purnima Murali Mohan, Zengxiang Li +1Backdoor AttacksBackdoor Attacks in Federated Learning

    Singapore Institute of Technology (SIT) Singapore · SingHealth Duke-NUS AI in Medicine Institute SingHealth AI Office, Singapore

  9. BackDFL: A Unified Benchmark For Backdoor Attacks and Defenses In Decentralized Federated Learning

    Aug 21, 2026Mouhamed Amine Bouchiha, Gregory Blanc, Yufei HanBackdoor Attacks in Federated LearningFederated Learning

    SAMOVAR, Télécom SudParis, Institut Polytechnique de Paris · PIRAT, INRIA Rennes, Rennes, France

  10. Understanding Backdoor Vulnerabilities in Vertical Federated Learning: The Gap Between Research and Practice

    Aug 13, 2026Ziqi Zhao, Jialin Lu, Junjie Shan +3Backdoor AttacksBackdoor Attacks in Federated Learning

    School of Computing and Data Science, The University of Hong Kong, Hong Kong SAR, China

  11. Analysis of Federated Aggregation under Model Poisoning and Backdoor Attacks: A Reconstructed Cross-Dataset and Cross-Architecture Benchmark

    Aug 11, 2026Soumya Mazumdar, Vineet Kumar Rakesh, Tapas SamantaFederated Learning AggregationByzantine-Robust Federated Learning

    Department of Computer Science and Business Systems Gargi Memorial Institute of Technology Affiliated to Maulana Abul Kalam Azad University of Technology Balarampur, Mouza Beralia, Baruipur, Kolkata 700144, West Bengal, India · Computer and Informatics Group, Variable Energy Cyclotron Centre 1/AF, Bidhannagar, Kolkata 700064, West Bengal, India · Engineering Sciences, Homi Bhabha National Institute Anushaktinagar, Mumbai, Maharashtra 400094, India

  12. Bypassing Krum: Selection-Aware Backdoor Attacks in Federated Learning

    Aug 6, 2026Srinivasan Subramanian, Md. Abdullah Al Hafiz Khan, Kazi Aminul IslamFederated Learning AggregationByzantine-Robust Federated Learning

    Department of Computer Science Kennesaw State University Marietta, USA

  13. Robust and Personalized Federated Learning for Aircraft-Engine Prognostics under Benign and Adversarial Client Heterogeneity

    Aug 4, 2026Chinmoy Mitra, Md. Mehedi Hasan Nipu, Mohammad Sakib Mahmood +2Federated Learning AggregationRUL Estimation

    Department of Computer Science and Engineering, Rajshahi University of Engineering & Technology, Kazla, Rajshahi, 6204, Bangladesh · Department of Electrical and Computer Engineering, North South University, Dhaka 1229, Bangladesh. · Department of Computer Science, Missouri State University, Springfield, MO, 65809, USA. +2

  14. TriShield: Zero-Utility-Loss Defense Against Privacy Backdoors in Federated Language Model Fine-Tuning via Orthogonal Gradient Projection and Optimizer State Entanglement

    Jul 30, 2026Cheng WeiBackdoor AttacksBackdoor Attacks in Federated Learning

    Honor Device Co., Ltd., Shenzhen, China

  15. Defending Against Backdoor Attacks via Alignment Checking in Model-Contrastive Federated Learning

    Jul 29, 2026Hongliang Zhang, Zhongyuan Yu, Guijuan Wang +4Federated Learning AggregationByzantine-Robust Federated Learning

    Key Laboratory of Computing Power Network and Information Security, Ministry of Education, Shandong Computer Science Center, Qilu University of Technology (Shandong Academy of Sciences), Jinan, 250353, China · College of computer science and technology, China University of Petroleum, Qingdao, 266580, China · School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 611731, China

  16. FedLSG: LLM-Enhanced Semantic Calibration for Federated Graph Backdoor Defense

    Jul 22, 2026Chenyu Zhou, Yabin Peng, Wei Huang +3Graph Neural NetworksBackdoor Attacks

    Southeast University Purple Mountain Laboratories · Institute of AI for Industries Chinese Academy of Sciences · Purple Mountain Laboratories

  17. Color Matters: Trigger Color Affects Success in Federated Backdoor Attacks

    Jun 24, 2026Kavindu Herath, Joshua C. Zhao, Saurabh BagchiBackdoor AttacksBackdoor Attacks in Federated Learning

    Department of Electrical and Computer Engineering, Purdue University, West Lafayette, USA

  18. SCRUB-FL: Sanitizing and Cleansing Representations via Unlearning of Backdoors

    Jun 21, 2026Osama Wehbi, Sarhad Arisdakessian, Omar Abdel Wahab +2Backdoor Attacks in Federated LearningFederated Learning

    Department of Computer and Software Engineering, Polytechnique Montréal, Montreal, Quebec, Canada · Department of Computer Science, Khalifa University, Abu Dhabi, UAE

  19. Your Privacy My Cloak: Backdoor Attacks on Differentially Private Federated Learning

    Jun 15, 2026Xiaolin Li, Ning Wang, Ninghui Li +1Backdoor Attacks in Federated LearningDifferentially Private Federated Learning

    Purdue University West Lafayette, IN, USA · University of South Florida Tampa, FL, USA

  20. Model Poisoning Against Federated Model Adaptation with Chain of Bit-Flips

    Jun 8, 2026Bastien Vuillod, Kevin Hector, Pierre-Alain Moellic +2Adversarial AttacksBackdoor Attacks in Federated Learning

    CEA-Leti, Mines Saint-Etienne, Equipe Commune SAS, F-13541 Gardanne, France · Mines Saint-Etienne, CEA-Leti, Centre CMP, Equipe commune SAS, F-13541 Gardanne, France

  21. Can Quantum Federated Learning Withstand Circuit-Level Backdoors?

    May 18, 2026Aakar Mathur, Mohammed Ruknuddin, Ashish GuptaBackdoor Attacks in Federated LearningQuantum Machine Learning

    BITS Pilani Dubai Campus, Dubai, UAE

  22. FedSurrogate: Backdoor Defense in Federated Learning via Layer Criticality and Surrogate Replacement

    May 11, 2026Fatima Z. Abacha, Sin G. Teo, Yuanxiang Wu +2Backdoor AttacksBackdoor Attacks in Federated Learning

    The University of Manchester, UK · Institute for Infocomm Research, A*STAR, Singapore · Monash University, Australia +1

  23. Beyond Corner Patches: Semantics-Aware Backdoor Attack in Federated Learning

    Mar 31, 2026Kavindu Herath, Joshua Zhao, Saurabh BagchiBackdoor AttacksBackdoor Attacks in Federated Learning

    Department of Electrical and Computer Engineering, Purdue University, West Lafayette, USA

  24. FL-PBM: Pre-Training Backdoor Mitigation for Federated Learning

    Mar 30, 2026Osama Wehbi, Sarhad Arisdakessian, Omar Abdel Wahab +3Backdoor Attacks in Federated LearningFederated Learning

    Department of Computer and Software Engineering, Polytechnique Montréal, Montreal, Quebec, Canada · Department of Computer Science, Khalifa University, Abu Dhabi, UAE · Artificial Intelligence & Cyber Systems Research Center, Department of CSM, Lebanese American University +2

  25. Mitigating Backdoor Attacks in Federated Learning Using PPA and MiniMax Game Theory

    Mar 30, 2026Osama Wehbi, Sarhad Arisdakessian, Omar Abdel Wahab +3Backdoor Attacks in Federated LearningFederated Learning

    Department of Computer and Software Engineering, Polytechnique Montréal, Montreal, Quebec, Canada · Institut national de la recherche scientifique (INRS-EMT), Montréal, Canada · Department of Computer Science, Khalifa University, Abu Dhabi, UAE +1

  26. Beyond Passive Aggregation: Active Auditing and Topology-Aware Defense in Decentralized Federated Learning

    Mar 19, 2026Sheng Pan, Niansheng TangFederated LearningBackdoor Attacks in Federated Learning

    Yunnan Key Laboratory of Statistical Modeling and Data Analysis, Yunnan University, Kunming 650091, China

  27. TASER: Task-Aware Spectral Energy Refine for Backdoor Suppression in UAV Swarms Decentralized Federated Learning

    Mar 10, 2026Sizhe Huang, Shujie YangBackdoor Attacks in Federated LearningFederated Learning

  28. Structure-Aware Distributed Backdoor Attacks in Federated Learning

    Mar 4, 2026Wang Jian, Shen Hong, Ke Wei +1Backdoor Attacks in Federated LearningAdversarial Perturbations

    Faculty of Applied Sciences, Macao Polytechnic University, R. de Luís Gonzaga Gomes, Macao, 999078, China · Faculty of Cyberspace Security, Software Engineering Institute of Guangzhou, No.548 Guangcong South Road, High-tech Industrial Park, Conghua Economic Development Zone, Guangzhou, 501900, China · School of Engineering and Technology, Central Queensland University, Bruce Highway, Norman Gardens, Rockhampton, Queensland, 4702, Australia +1

  29. Is the Trigger Essential? A Feature-Based Triggerless Backdoor Attack in Vertical Federated Learning

    Feb 24, 2026Yige Liu, Yiwei Lou, Che Wang +2Backdoor AttacksBackdoor Attacks in Federated Learning

    Key Laboratory of High Confidence Software Technologies (Peking University), Ministry of Education; School of Computer Science, Peking University, Beijing, China. · Zhongguancun Laboratory, Beijing, China.

  30. Exploiting Layer-Specific Vulnerabilities to Backdoor Attack in Federated Learning

    Feb 16, 2026Mohammad Hadi Foroughi, Seyed Hamed Rastegar, Mohammad Sabokrou +1Backdoor AttacksBackdoor Attacks in Federated Learning

    School of Electrical and Computer Engineering, University of Tehran, Tehran, Iran. · School of Computer Science, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran. · School of Electrical and Computer Engineering, Shiraz University, Shiraz, Iran. +1