Learning to Detect Malicious Clients for Robust Federated Learning

1 February 2020

Yang Liu

Papers citing "Learning to Detect Malicious Clients for Robust Federated Learning"

50 / 88 papers shown

Title
Robust Federated Learning Against Poisoning Attacks: A GAN-Based Defense Framework Usama Zafar André Teixeira Salman Toor FedML AAML 54 0 0 26 Mar 2025
Moss: Proxy Model-based Full-Weight Aggregation in Federated Learning with Heterogeneous Models Y. Cai Ziqi Zhang Ding Li Yao Guo Xiangqun Chen 48 0 0 13 Mar 2025
Runtime Backdoor Detection for Federated Learning via Representational Dissimilarity Analysis X. Zhang Xiaoyong Xue Xiaoning Du Xiaofei Xie Y. Liu Meng Sun FedML AAML 60 0 0 06 Mar 2025
FedSV: Byzantine-Robust Federated Learning via Shapley Value Khaoula Otmani Rachid Elazouzi Vincent Labatut FedML AAML 80 2 0 24 Feb 2025
FedNIA: Noise-Induced Activation Analysis for Mitigating Data Poisoning in FL Ehsan Hallaji R. Razavi-Far M. Saif AAML 43 0 0 23 Feb 2025
FedEAT: A Robustness Optimization Framework for Federated LLMs Yahao Pang Xingyuan Wu Xiaojin Zhang Wei Chen Hai Jin FedML 77 0 0 17 Feb 2025
Decoding FL Defenses: Systemization, Pitfalls, and Remedies M. A. Khan Virat Shejwalkar Yasra Chandio Amir Houmansadr Fatima M. Anwar AAML 38 0 0 03 Feb 2025
FedCLEAN: byzantine defense by CLustering Errors of Activation maps in Non-IID federated learning environments Mehdi Ben Ghali R. Bellafqira G. Coatrieux AAML FedML 43 0 0 21 Jan 2025
Fine-Tuning Personalization in Federated Learning to Mitigate Adversarial Clients Youssef Allouah Abdellah El Mrini R. Guerraoui Nirupam Gupta Rafael Pinot FedML 27 0 0 30 Sep 2024
Leveraging Pre-trained Models for Robust Federated Learning for Kidney Stone Type Recognition Iván Reyes-Amezcua Michael Rojas-Ruiz Gilberto Ochoa-Ruiz Andres Mendez-Vazquez C. Daul 24 0 0 30 Sep 2024
Data Distribution Shifts in (Industrial) Federated Learning as a Privacy Issue David Brunner Alessio Montuoro FedML 18 0 0 20 Sep 2024
Data Poisoning and Leakage Analysis in Federated Learning Wenqi Wei Tiansheng Huang Zachary Yahn Anoop Singhal Margaret Loper Ling Liu FedML SILM 18 0 0 19 Sep 2024
BoBa: Boosting Backdoor Detection through Data Distribution Inference in Federated Learning Ning Wang Shanghao Shi Yang Xiao Yimin Chen Y. T. Hou W. Lou FedML AAML 28 1 0 12 Jul 2024
DART: A Solution for Decentralized Federated Learning Model Robustness Analysis Chao Feng Alberto Huertas Celdrán Jan von der Assen Enrique Tomás Martínez Beltrán Gérome Bovet Burkhard Stiller OOD AAML 48 8 0 11 Jul 2024
Non-Cooperative Backdoor Attacks in Federated Learning: A New Threat Landscape Tuan Nguyen Dung Thuy Nguyen Khoa D. Doan Kok-Seng Wong AAML 31 1 0 05 Jul 2024
A Whole-Process Certifiably Robust Aggregation Method Against Backdoor Attacks in Federated Learning Anqi Zhou Yezheng Liu Yidong Chai Hongyi Zhu Xinyue Ge Yuanchun Jiang Meng Wang AAML 39 0 0 30 Jun 2024
Certified Robustness to Data Poisoning in Gradient-Based Training Philip Sosnin Mark N. Müller Maximilian Baader Calvin Tsay Matthew Wicker AAML SILM 63 8 0 09 Jun 2024
Marking the Pace: A Blockchain-Enhanced Privacy-Traceable Strategy for Federated Recommender Systems Zhen Cai Tao Tang Shuo Yu Yunpeng Xiao Feng Xia 40 1 0 07 Jun 2024
Federated Learning in Healthcare: Model Misconducts, Security, Challenges, Applications, and Future Research Directions -- A Systematic Review Md. Shahin Ali M. Ahsan Lamia Tasnim Sadia Afrin Koushik Biswas Maruf Md. Sajjad Hossain Md Mahfuz Ahmed Ronok Hashan Md. Khairul Islam Shivakumar Raman 30 5 0 22 May 2024
Model Poisoning Attacks to Federated Learning via Multi-Round Consistency Yueqi Xie Minghong Fang Neil Zhenqiang Gong AAML 29 7 0 24 Apr 2024
Fin-Fed-OD: Federated Outlier Detection on Financial Tabular Data Dayananda Herurkar Sebastián M. Palacio Ahmed Anwar J¨orn Hees Andreas Dengel FedML 22 3 0 23 Apr 2024
FLGuard: Byzantine-Robust Federated Learning via Ensemble of Contrastive Models Younghan Lee Yungi Cho Woorim Han Ho Bae Y. Paek FedML AAML 27 2 0 05 Mar 2024
Decentralized Federated Learning: A Survey on Security and Privacy Ehsan Hallaji R. Razavi-Far M. Saif Boyu Wang Qiang Yang FedML 43 34 0 25 Jan 2024
Towards Efficient and Certified Recovery from Poisoning Attacks in Federated Learning Yu Jiang Jiyuan Shen Ziyao Liu Chee Wei Tan Kwok-Yan Lam AAML FedML 34 6 0 16 Jan 2024
Data and Model Poisoning Backdoor Attacks on Wireless Federated Learning, and the Defense Mechanisms: A Comprehensive Survey Yichen Wan Youyang Qu Wei Ni Yong Xiang Longxiang Gao Ekram Hossain AAML 45 33 0 14 Dec 2023
Defenses in Adversarial Machine Learning: A Survey Baoyuan Wu Shaokui Wei Mingli Zhu Meixi Zheng Zihao Zhu Mingda Zhang Hongrui Chen Danni Yuan Li Liu Qingshan Liu AAML 30 14 0 13 Dec 2023
A Survey on Federated Unlearning: Challenges, Methods, and Future Directions Ziyao Liu Yu Jiang Jiyuan Shen Minyi Peng Kwok-Yan Lam Xingliang Yuan Xiaoning Liu MU 26 43 0 31 Oct 2023
FLrce: Resource-Efficient Federated Learning with Early-Stopping Strategy Ziru Niu Senior Member Ieee Hai Dong •. A. K. Qin Senior Member Ieee Tao Gu 25 4 0 15 Oct 2023
Resisting Backdoor Attacks in Federated Learning via Bidirectional Elections and Individual Perspective Zhen Qin Feiyi Chen Chen Zhi Xueqiang Yan Shuiguang Deng AAML FedML 18 3 0 28 Sep 2023
SPIRT: A Fault-Tolerant and Reliable Peer-to-Peer Serverless ML Training Architecture Amine Barrak Mayssa Jaziri Ranim Trabelsi Fehmi Jaafar Fábio Petrillo 31 2 0 25 Sep 2023
SPFL: A Self-purified Federated Learning Method Against Poisoning Attacks Zizhen Liu Weiyang He Chip-Hong Chang Jing Ye Huawei Li Xiaowei Li 29 4 0 19 Sep 2023
When Federated Learning meets Watermarking: A Comprehensive Overview of Techniques for Intellectual Property Protection Mohammed Lansari R. Bellafqira K. Kapusta V. Thouvenot Olivier Bettan G. Coatrieux FedML 23 15 0 07 Aug 2023
Heterogeneous Federated Learning: State-of-the-art and Research Challenges Mang Ye Xiuwen Fang Bo Du PongChi Yuen Dacheng Tao FedML AAML 33 244 0 20 Jul 2023
FedVal: Different good or different bad in federated learning Viktor Valadi Xinchi Qiu Pedro Gusmão Nicholas D. Lane Mina Alibeigi FedML AAML 12 2 0 06 Jun 2023
Covert Communication Based on the Poisoning Attack in Federated Learning Junchuan Liang Rong Wang FedML 18 1 0 02 Jun 2023
Trustworthy Federated Learning: A Survey A. Tariq M. Serhani F. Sallabi Tariq Qayyum E. Barka K. Shuaib FedML 25 9 0 19 May 2023
FedGT: Identification of Malicious Clients in Federated Learning with Secure Aggregation M. Xhemrishi Johan Ostman A. Wachter-Zeh Alexandre Graell i Amat FedML 19 6 0 09 May 2023
Multi-metrics adaptively identifies backdoors in Federated learning Siquan Huang Yijiang Li Chong Chen Leyu Shi Ying Gao AAML 30 19 0 12 Mar 2023
Backdoor Attacks and Defenses in Federated Learning: Survey, Challenges and Future Research Directions Thuy-Dung Nguyen Tuan Nguyen Phi Le Nguyen Hieu H. Pham Khoa D. Doan Kok-Seng Wong AAML FedML 32 56 0 03 Mar 2023
A Survey of Trustworthy Federated Learning with Perspectives on Security, Robustness, and Privacy Yifei Zhang Dun Zeng Jinglong Luo Zenglin Xu Irwin King FedML 69 47 0 21 Feb 2023
Backdoor Learning for NLP: Recent Advances, Challenges, and Future Research Directions Marwan Omar SILM AAML 23 20 0 14 Feb 2023
BayBFed: Bayesian Backdoor Defense for Federated Learning Kavita Kumari Phillip Rieger Hossein Fereidooni Murtuza Jadliwala A. Sadeghi AAML FedML 21 31 0 23 Jan 2023
Hijack Vertical Federated Learning Models As One Party Pengyu Qiu Xuhong Zhang Shouling Ji Changjiang Li Yuwen Pu Xing Yang Ting Wang FedML 8 4 0 01 Dec 2022
FedLesScan: Mitigating Stragglers in Serverless Federated Learning M. Elzohairy Mohak Chadha Anshul Jindal Andreas Grafberger Jiatao Gu Michael Gerndt Osama Abboud FedML 19 7 0 10 Nov 2022
FLIP: A Provable Defense Framework for Backdoor Mitigation in Federated Learning Kaiyuan Zhang Guanhong Tao Qiuling Xu Shuyang Cheng Shengwei An ... Shiwei Feng Guangyu Shen Pin-Yu Chen Shiqing Ma Xiangyu Zhang FedML 30 51 0 23 Oct 2022
FedRecover: Recovering from Poisoning Attacks in Federated Learning using Historical Information Xiaoyu Cao Jinyuan Jia Zaixi Zhang Neil Zhenqiang Gong FedML MU AAML 11 72 0 20 Oct 2022
Long-Short History of Gradients is All You Need: Detecting Malicious and Unreliable Clients in Federated Learning Ashish Gupta Tie-Mei Luo Mao V. Ngo Sajal K. Das AAML FedML 29 13 0 14 Aug 2022
A New Implementation of Federated Learning for Privacy and Security Enhancement Xiang Ma Haijian Sun R. Hu Yi Qian FedML 24 3 0 03 Aug 2022
Privacy-Preserving Federated Recurrent Neural Networks Sinem Sav Abdulrahman Diaa Apostolos Pyrgelis Jean-Philippe Bossuat Jean-Pierre Hubaux 6 7 0 28 Jul 2022
Technical Report: Assisting Backdoor Federated Learning with Whole Population Knowledge Alignment Tian Liu Xueyang Hu Tao Shu AAML FedML 14 6 0 25 Jul 2022