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Robust Aggregation for Federated Learning

IEEE Transactions on Signal Processing (IEEE Trans. Signal Process.), 2019

31 December 2019

Papers citing "Robust Aggregation for Federated Learning"

50 / 303 papers shown

Title
Detection and Mitigation of Byzantine Attacks in Distributed TrainingIEEE/ACM Transactions on Networking (TON), 2022 Konstantinos Konstantinidis Namrata Vaswani Aditya Ramamoorthy AAML 233 1 0 17 Aug 2022
A Knowledge Distillation-Based Backdoor Attack in Federated Learning Yifan Wang Wei Fan Keke Yang Naji Alhusaini Jing Li AAML FedML 153 4 0 12 Aug 2022
A New Implementation of Federated Learning for Privacy and Security EnhancementGlobal Communications Conference (GLOBECOM), 2022 Xiang Ma Haijian Sun R. Hu Yi Qian FedML 189 3 0 03 Aug 2022
Technical Report: Assisting Backdoor Federated Learning with Whole Population Knowledge Alignment Tian Liu Xueyang Hu Tao Shu AAML FedML 124 7 0 25 Jul 2022
Using Anomaly Detection to Detect Poisoning Attacks in Federated Learning Applications Ali Raza Shujun Li K. Tran L. Koehl Kim Duc Tran AAML 327 7 0 18 Jul 2022
MixTailor: Mixed Gradient Aggregation for Robust Learning Against Tailored Attacks Ali Ramezani-Kebrya Iman Tabrizian Fartash Faghri P. Popovski AAML FedML 126 7 0 16 Jul 2022
Federated and Transfer Learning: A Survey on Adversaries and Defense Mechanisms Ehsan Hallaji R. Razavi-Far R. Razavi-Far AAML FedML 125 15 0 05 Jul 2022
Backdoor Attack is a Devil in Federated GAN-based Medical Image Synthesis Ruinan Jin Xiaoxiao Li AAML FedML MedIm 266 13 0 02 Jul 2022
Cross-Silo Federated Learning: Challenges and Opportunities Chao Huang Jianwei Huang Xin Liu FedML 183 85 0 26 Jun 2022
zPROBE: Zero Peek Robustness Checks for Federated LearningIEEE International Conference on Computer Vision (ICCV), 2022 Zahra Ghodsi Mojan Javaheripi Nojan Sheybani Xinqiao Zhang Ke Huang F. Koushanfar FedML 314 27 0 24 Jun 2022
Blades: A Unified Benchmark Suite for Byzantine Attacks and Defenses in Federated LearningInternational Conference on Internet-of-Things Design and Implementation (IoTDI), 2022 Shenghui Li Edith C.H. Ngai Fanghua Ye Li Ju Tianru Zhang Thiemo Voigt AAML FedML 286 15 0 10 Jun 2022
Variance Reduction is an Antidote to Byzantines: Better Rates, Weaker Assumptions and Communication Compression as a Cherry on the Top Eduard A. Gorbunov Samuel Horváth Peter Richtárik Gauthier Gidel AAML 247 0 0 01 Jun 2022
Communication-efficient distributed eigenspace estimation with arbitrary node failuresNeural Information Processing Systems (NeurIPS), 2022 Vasileios Charisopoulos Anil Damle 150 1 0 31 May 2022
QUIC-FL: Quick Unbiased Compression for Federated Learning Ran Ben-Basat S. Vargaftik Amit Portnoy Gil Einziger Y. Ben-Itzhak Michael Mitzenmacher FedML 301 14 0 26 May 2022
A Survey of Graph-Theoretic Approaches for Analyzing the Resilience of Networked Control Systems Mohammad Pirani A. Mitra S. Sundaram AI4CE 148 10 0 25 May 2022
Byzantine Machine Learning Made Easy by Resilient Averaging of MomentumsInternational Conference on Machine Learning (ICML), 2022 Sadegh Farhadkhani R. Guerraoui Nirupam Gupta Rafael Pinot John Stephan FedML 202 86 0 24 May 2022
Byzantine-Robust Federated Learning with Optimal Statistical Rates and Privacy GuaranteesInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2022 Banghua Zhu Lun Wang Qi Pang Shuai Wang Jiantao Jiao Basel Alomair Sai Li FedML 286 40 0 24 May 2022
Towards a Defense Against Federated Backdoor Attacks Under Continuous Training Shuai Wang J. Hayase Giulia Fanti Sewoong Oh FedML 251 6 0 24 May 2022
Robust Quantity-Aware Aggregation for Federated Learning Jingwei Yi Fangzhao Wu Huishuai Zhang Bin Zhu Tao Qi Guangzhong Sun Xing Xie FedML 214 2 0 22 May 2022
FedNoiL: A Simple Two-Level Sampling Method for Federated Learning with Noisy Labels Zhuowei Wang Wanrong Zhu Guodong Long Bo Han Jing Jiang FedML 243 21 0 20 May 2022
Federated Multi-Armed Bandits Under Byzantine AttacksIEEE Transactions on Artificial Intelligence (IEEE TAI), 2022 Artun Saday Ilker Demirel Yiğit Yıldırım Cem Tekin AAML 200 15 0 09 May 2022
Over-The-Air Federated Learning under Byzantine Attacks Houssem Sifaou Geoffrey Ye Li OOD FedML 182 8 0 05 May 2022
Performance Weighting for Robust Federated Learning Against Corrupted Sources Dimitris Stripelis M. Abram J. Ambite FedML 170 9 0 02 May 2022
Distributed Statistical Min-Max Learning in the Presence of Byzantine AgentsIEEE Conference on Decision and Control (CDC), 2022 Arman Adibi A. Mitra George J. Pappas Hamed Hassani 150 3 0 07 Apr 2022
Byzantine-Robust Federated Linear BanditsIEEE Conference on Decision and Control (CDC), 2022 Ali Jadbabaie Haochuan Li Jian Qian Yi Tian FedML 179 13 0 03 Apr 2022
Robust and Efficient Aggregation for Distributed LearningEuropean Signal Processing Conference (EUSIPCO), 2022 Stefan Vlaski Christian A. Schroth Michael Muma A. Zoubir OOD FedML 190 4 0 01 Apr 2022
Trusted AI in Multi-agent Systems: An Overview of Privacy and Security for Distributed LearningProceedings of the IEEE (Proc. IEEE), 2022 Chuan Ma Jun Li Kang Wei Bo Liu Ming Ding Long Yuan Zhu Han H. Vincent Poor 301 63 0 18 Feb 2022
More is Better (Mostly): On the Backdoor Attacks in Federated Graph Neural NetworksAsia-Pacific Computer Systems Architecture Conference (ACSA), 2022 Jing Xu Rui Wang Stefanos Koffas K. Liang S. Picek FedML AAML 281 35 0 07 Feb 2022
Byzantine-Robust Decentralized Learning via ClippedGossip Lie He Sai Praneeth Karimireddy Martin Jaggi FedML 176 33 0 03 Feb 2022
Studying the Robustness of Anti-adversarial Federated Learning Models Detecting Cyberattacks in IoT Spectrum SensorsIEEE Transactions on Dependable and Secure Computing (TDSC), 2022 Pedro Miguel Sánchez Sánchez Alberto Huertas Celdrán T. Schenk A. Iten Gérome Bovet Gregorio Martínez Pérez Burkhard Stiller AAML 192 26 0 31 Jan 2022
Survey on Federated Learning Threats: concepts, taxonomy on attacks and defences, experimental study and challengesInformation Fusion (Inf. Fusion), 2022 Nuria Rodríguez-Barroso Daniel Jiménez López M. V. Luzón Francisco Herrera Eugenio Martínez-Cámara FedML 181 277 0 20 Jan 2022
How to Backdoor HyperNetwork in Personalized Federated Learning? Phung Lai Nhathai Phan Issa M. Khalil Abdallah Khreishah Xintao Wu AAML FedML 174 0 0 18 Jan 2022
RFLBAT: A Robust Federated Learning Algorithm against Backdoor Attack Yongkang Wang Dihua Zhai Yufeng Zhan Yuanqing Xia FedML AAML 93 20 0 11 Jan 2022
Towards Understanding Quality Challenges of the Federated Learning for Neural Networks: A First Look from the Lens of RobustnessEmpirical Software Engineering (EMSE), 2022 Amin Eslami Abyane Derui Zhu Roberto Souza Lei Ma Hadi Hemmati AAML OOD FedML 109 5 0 05 Jan 2022
Challenges and Approaches for Mitigating Byzantine Attacks in Federated LearningInternational Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), 2021 Junyu Shi Wei Wan Shengshan Hu Jianrong Lu L. Zhang AAML 210 101 0 29 Dec 2021
On the Security & Privacy in Federated Learning Gorka Abad S. Picek Víctor Julio Ramírez-Durán A. Urbieta 289 12 0 10 Dec 2021
Eluding Secure Aggregation in Federated Learning via Model InconsistencyConference on Computer and Communications Security (CCS), 2021 Dario Pasquini Danilo Francati G. Ateniese FedML 484 130 0 14 Nov 2021
Robust Federated Learning via Over-The-Air ComputationInternational Workshop on Machine Learning for Signal Processing (MLSP), 2021 Houssem Sifaou Geoffrey Ye Li FedML 340 18 0 01 Nov 2021
FL-WBC: Enhancing Robustness against Model Poisoning Attacks in Federated Learning from a Client Perspective Jingwei Sun Ang Li Louis DiValentin Amin Hassanzadeh Yiran Chen Xue Yang FedML OOD AAML 195 103 0 26 Oct 2021
UniFed: A Unified Framework for Federated Learning on Non-IID Image Features Meirui Jiang Xiaoxiao Li Xiaofei Zhang Michael Kamp Qianming Dou FedML OOD 234 1 0 19 Oct 2021
Federated Learning from Small Datasets Michael Kamp Jonas Fischer Jilles Vreeken FedML 266 34 0 07 Oct 2021
Two-Bit Aggregation for Communication Efficient and Differentially Private Federated Learning M. Aghapour A. Ferdowsi Walid Saad FedML 54 1 0 06 Oct 2021
Secure Byzantine-Robust Distributed Learning via Clustering R. K. Velicheti Derek Xia Oluwasanmi Koyejo FedML OOD 192 20 0 06 Oct 2021
DeSMP: Differential Privacy-exploited Stealthy Model Poisoning Attacks in Federated Learning Md Tamjid Hossain Shafkat Islam S. Badsha Haoting Shen AAML 166 50 0 21 Sep 2021
Connecting Low-Loss Subspace for Personalized Federated Learning S. Hahn Minwoo Jeong Junghye Lee FedML 179 25 0 16 Sep 2021
Byzantine-Robust Federated Learning via Credibility Assessment on Non-IID Data Kun Zhai Qiang Ren Junli Wang Chungang Yan 120 14 0 06 Sep 2021
Back to the Drawing Board: A Critical Evaluation of Poisoning Attacks on Production Federated LearningIEEE Symposium on Security and Privacy (IEEE S&P), 2021 Virat Shejwalkar Amir Houmansadr Peter Kairouz Daniel Ramage AAML 285 262 0 23 Aug 2021
EDEN: Communication-Efficient and Robust Distributed Mean Estimation for Federated Learning S. Vargaftik Ran Ben-Basat Amit Portnoy Gal Mendelson Y. Ben-Itzhak Michael Mitzenmacher FedML 228 55 0 19 Aug 2021
Learning-to-learn non-convex piecewise-Lipschitz functions Maria-Florina Balcan M. Khodak Dravyansh Sharma Ameet Talwalkar 126 19 0 19 Aug 2021
ABC-FL: Anomalous and Benign client Classification in Federated Learning Hyejun Jeong Joonyong Hwang Tai-Myung Chung 118 4 0 10 Aug 2021