Back to the Drawing Board: A Critical Evaluation of Poisoning Attacks on Production Federated Learning

23 August 2021

Papers citing "Back to the Drawing Board: A Critical Evaluation of Poisoning Attacks on Production Federated Learning"

41 / 41 papers shown

Title
Toward Malicious Clients Detection in Federated Learning Zhihao Dou Jiaqi Wang Wei Sun Zhuqing Liu Minghong Fang AAML 29 0 0 14 May 2025
Bayesian Robust Aggregation for Federated Learning Aleksandr Karakulev Usama Zafar Salman Toor Prashant Singh FedML 38 0 0 05 May 2025
A Client-level Assessment of Collaborative Backdoor Poisoning in Non-IID Federated Learning Phung Lai Guanxiong Liu Hai Phan Issa M. Khalil Abdallah Khreishah Xintao Wu FedML 36 0 0 17 Apr 2025
FedSV: Byzantine-Robust Federated Learning via Shapley Value Khaoula Otmani Rachid Elazouzi Vincent Labatut FedML AAML 90 2 0 24 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
Do We Really Need to Design New Byzantine-robust Aggregation Rules? Minghong Fang Seyedsina Nabavirazavi Zhuqing Liu Wei Sun S. Iyengar Haibo Yang AAML OOD 84 6 0 29 Jan 2025
Uncovering, Explaining, and Mitigating the Superficial Safety of Backdoor Defense Rui Min Zeyu Qin Nevin L. Zhang Li Shen Minhao Cheng AAML 39 4 0 13 Oct 2024
Advancing Hybrid Defense for Byzantine Attacks in Federated Learning Kai Yue Richeng Jin Chau-Wai Wong H. Dai AAML 39 0 0 10 Sep 2024
LiD-FL: Towards List-Decodable Federated Learning Hong Liu Liren Shan Han Bao Ronghui You Yuhao Yi Jiancheng Lv FedML 44 0 0 09 Aug 2024
DeepiSign-G: Generic Watermark to Stamp Hidden DNN Parameters for Self-contained Tracking A. Abuadbba Nicholas Rhodes Kristen Moore Bushra Sabir Shuo Wang Yansong Gao AAML 35 2 0 01 Jul 2024
Data Quality in Edge Machine Learning: A State-of-the-Art Survey M. D. Belgoumri Mohamed Reda Bouadjenek Sunil Aryal Hakim Hacid 41 1 0 01 Jun 2024
Precision Guided Approach to Mitigate Data Poisoning Attacks in Federated Learning Naveen Kumar Krishna Mohan Aravind Machiry AAML 36 1 0 05 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
Data-Agnostic Model Poisoning against Federated Learning: A Graph Autoencoder Approach Kai Li Jingjing Zheng Xinnan Yuan W. Ni Ozgur B. Akan H. Vincent Poor AAML 27 15 0 30 Nov 2023
Voyager: MTD-Based Aggregation Protocol for Mitigating Poisoning Attacks on DFL Chao Feng Alberto Huertas Celdrán Michael Vuong Gérome Bovet Burkhard Stiller AAML 24 1 0 12 Oct 2023
A Survey for Federated Learning Evaluations: Goals and Measures Di Chai Leye Wang Liu Yang Junxue Zhang Kai Chen Qian Yang ELM FedML 17 21 0 23 Aug 2023
Samplable Anonymous Aggregation for Private Federated Data Analysis Kunal Talwar Shan Wang Audra McMillan Vojta Jina Vitaly Feldman ... Congzheng Song Karl Tarbe Sebastian Vogt L. Winstrom Shundong Zhou FedML 38 13 0 27 Jul 2023
FedDefender: Client-Side Attack-Tolerant Federated Learning Sungwon Park Sungwon Han Fangzhao Wu Sundong Kim Bin Zhu Xing Xie Meeyoung Cha FedML AAML 25 20 0 18 Jul 2023
Edge Learning for 6G-enabled Internet of Things: A Comprehensive Survey of Vulnerabilities, Datasets, and Defenses M. Ferrag Othmane Friha B. Kantarci Norbert Tihanyi Lucas C. Cordeiro Merouane Debbah Djallel Hamouda Muna Al-Hawawreh K. Choo 25 43 0 17 Jun 2023
Incentivizing Honesty among Competitors in Collaborative Learning and Optimization Florian E. Dorner Nikola Konstantinov Georgi Pashaliev Martin Vechev FedML 22 5 0 25 May 2023
Can Decentralized Learning be more robust than Federated Learning? Mathilde Raynal Dario Pasquini Carmela Troncoso OOD FedML 38 4 0 07 Mar 2023
FLINT: A Platform for Federated Learning Integration Ewen N. Wang Ajaykumar Kannan Yuefeng Liang Boyi Chen Mosharaf Chowdhury 40 24 0 24 Feb 2023
Revisiting Personalized Federated Learning: Robustness Against Backdoor Attacks Zeyu Qin Liuyi Yao Daoyuan Chen Yaliang Li Bolin Ding Minhao Cheng FedML 38 25 0 03 Feb 2023
Security Analysis of SplitFed Learning M. A. Khan Virat Shejwalkar Amir Houmansadr Fatima M. Anwar FedML 24 11 0 04 Dec 2022
FedCut: A Spectral Analysis Framework for Reliable Detection of Byzantine Colluders Hanlin Gu Lixin Fan Xingxing Tang Qiang Yang AAML FedML 22 1 0 24 Nov 2022
Rickrolling the Artist: Injecting Backdoors into Text Encoders for Text-to-Image Synthesis Lukas Struppek Dominik Hintersdorf Kristian Kersting SILM 22 36 0 04 Nov 2022
The Perils of Learning From Unlabeled Data: Backdoor Attacks on Semi-supervised Learning Virat Shejwalkar Lingjuan Lyu Amir Houmansadr AAML 27 10 0 01 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 42 51 0 23 Oct 2022
Thinking Two Moves Ahead: Anticipating Other Users Improves Backdoor Attacks in Federated Learning Yuxin Wen Jonas Geiping Liam H. Fowl Hossein Souri Ramalingam Chellappa Micah Goldblum Tom Goldstein AAML SILM FedML 30 9 0 17 Oct 2022
Byzantines can also Learn from History: Fall of Centered Clipping in Federated Learning Kerem Ozfatura Emre Ozfatura Alptekin Kupcu Deniz Gunduz AAML FedML 36 13 0 21 Aug 2022
PASS: A Parameter Audit-based Secure and Fair Federated Learning Scheme against Free-Rider Attack Jianhua Wang Xiaolin Chang J. Misic Vojislav B. Mišić Yixiang Wang 24 7 0 15 Jul 2022
FLVoogd: Robust And Privacy Preserving Federated Learning Yuhang Tian Rui Wang Yan Qiao E. Panaousis K. Liang FedML 28 4 0 24 Jun 2022
zPROBE: Zero Peek Robustness Checks for Federated Learning Zahra Ghodsi Mojan Javaheripi Nojan Sheybani Xinqiao Zhang Ke Huang F. Koushanfar FedML 47 17 0 24 Jun 2022
Neurotoxin: Durable Backdoors in Federated Learning Zhengming Zhang Ashwinee Panda Linyue Song Yaoqing Yang Michael W. Mahoney Joseph E. Gonzalez Kannan Ramchandran Prateek Mittal FedML 38 130 0 12 Jun 2022
Indiscriminate Data Poisoning Attacks on Neural Networks Yiwei Lu Gautam Kamath Yaoliang Yu AAML 43 24 0 19 Apr 2022
MPAF: Model Poisoning Attacks to Federated Learning based on Fake Clients Xiaoyu Cao Neil Zhenqiang Gong 20 108 0 16 Mar 2022
More is Better (Mostly): On the Backdoor Attacks in Federated Graph Neural Networks Jing Xu Rui Wang Stefanos Koffas K. Liang S. Picek FedML AAML 39 25 0 07 Feb 2022
Federated Evaluation and Tuning for On-Device Personalization: System Design & Applications Matthias Paulik M. Seigel Henry Mason Dominic Telaar Joris Kluivers ... Dominic Hughes O. Javidbakht Fei Dong Rehan Rishi Stanley Hung FedML 183 126 0 16 Feb 2021
Privacy and Robustness in Federated Learning: Attacks and Defenses Lingjuan Lyu Han Yu Xingjun Ma Chen Chen Lichao Sun Jun Zhao Qiang Yang Philip S. Yu FedML 183 355 0 07 Dec 2020
IBM Federated Learning: an Enterprise Framework White Paper V0.1 Heiko Ludwig Nathalie Baracaldo Gegi Thomas Yi Zhou Ali Anwar ... Sean Laguna Mikhail Yurochkin Mayank Agarwal Ebube Chuba Annie Abay FedML 131 157 0 22 Jul 2020
Analyzing Federated Learning through an Adversarial Lens A. Bhagoji Supriyo Chakraborty Prateek Mittal S. Calo FedML 191 1,032 0 29 Nov 2018