Data Poisoning Attacks on Federated Machine Learning

19 April 2020

Papers citing "Data Poisoning Attacks on Federated Machine Learning"

26 / 26 papers shown

Title
Intelligent Attacks and Defense Methods in Federated Learning-enabled Energy-Efficient Wireless Networks Han Zhang Hao Zhou Medhat H. M. Elsayed Majid Bavand Raimundas Gaigalas Yigit Ozcan Melike Erol-Kantarci AAML 72 0 0 25 Apr 2025
Technical Insights and Legal Considerations for Advancing Federated Learning in Bioinformatics Daniele Malpetti Marco Scutari Francesco Gualdi Jessica van Setten Sander van der Laan Saskia Haitjema Aaron Mark Lee Isabelle Hering Francesca Mangili FedML AI4CE 109 1 0 12 Mar 2025
Chemical knowledge-informed framework for privacy-aware retrosynthesis learning Guikun Chen Xu Zhang Yuqing Yang Wenguan Wang 47 0 0 26 Feb 2025
Secure Federated Data Distillation Marco Arazzi Mert Cihangiroglu S. Nicolazzo Antonino Nocera FedML DD 101 0 0 19 Feb 2025
Achieving Byzantine-Resilient Federated Learning via Layer-Adaptive Sparsified Model Aggregation Jiahao Xu Zikai Zhang Rui Hu 44 5 0 02 Sep 2024
FACT or Fiction: Can Truthful Mechanisms Eliminate Federated Free Riding? Marco Bornstein Amrit Singh Bedi Abdirisak Mohamed Furong Huang FedML 44 0 0 22 May 2024
A Survey on Vulnerability of Federated Learning: A Learning Algorithm Perspective Xianghua Xie Chen Hu Hanchi Ren Jingjing Deng FedML AAML 47 19 0 27 Nov 2023
Privacy Preservation in Artificial Intelligence and Extended Reality (AI-XR) Metaverses: A Survey Mahdi Alkaeed Adnan Qayyum Junaid Qadir 29 16 0 19 Sep 2023
High Dimensional Distributed Gradient Descent with Arbitrary Number of Byzantine Attackers Puning Zhao Zhiguo Wan OOD FedML 38 4 0 25 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
Avoid Adversarial Adaption in Federated Learning by Multi-Metric Investigations T. Krauß Alexandra Dmitrienko AAML 27 4 0 06 Jun 2023
Can Decentralized Learning be more robust than Federated Learning? Mathilde Raynal Dario Pasquini Carmela Troncoso OOD FedML 38 4 0 07 Mar 2023
Backdoor Learning for NLP: Recent Advances, Challenges, and Future Research Directions Marwan Omar SILM AAML 33 20 0 14 Feb 2023
Open RAN Security: Challenges and Opportunities Madhusanka Liyanage An Braeken Shahriar Shahabuddin Pasika Sashmal Ranaweera 37 84 0 03 Dec 2022
Byzantine Spectral Ranking Arnhav Datar A. Rajkumar Jonathan C. Augustine 28 4 0 15 Nov 2022
Federated Learning based on Defending Against Data Poisoning Attacks in IoT Jiayin Li Wenzhong Guo Xingshuo Han Jianping Cai Ximeng Liu AAML 83 1 0 14 Sep 2022
Using Anomaly Detection to Detect Poisoning Attacks in Federated Learning Applications Ali Raza Shujun Li K. Tran L. Koehl Kim Duc Tran AAML 33 3 0 18 Jul 2022
Certified Robustness in Federated Learning Motasem Alfarra Juan C. Pérez Egor Shulgin Peter Richtárik Guohao Li AAML FedML 23 7 0 06 Jun 2022
Byzantine-Robust Federated Learning with Optimal Statistical Rates and Privacy Guarantees Banghua Zhu Lun Wang Qi Pang Shuai Wang Jiantao Jiao D. Song Michael I. Jordan FedML 98 30 0 24 May 2022
Robust and Privacy-Preserving Collaborative Learning: A Comprehensive Survey Shangwei Guo Xu Zhang Feiyu Yang Tianwei Zhang Yan Gan Tao Xiang Yang Liu FedML 31 9 0 19 Dec 2021
Turning Federated Learning Systems Into Covert Channels Gabriele Costa Fabio Pinelli S. Soderi Gabriele Tolomei FedML 37 10 0 21 Apr 2021
Privacy and Trust Redefined in Federated Machine Learning Pavlos Papadopoulos Will Abramson A. Hall Nikolaos Pitropakis William J. Buchanan 33 42 0 29 Mar 2021
Federated Learning: Opportunities and Challenges P. Mammen FedML 51 212 0 14 Jan 2021
Dataset Security for Machine Learning: Data Poisoning, Backdoor Attacks, and Defenses Micah Goldblum Dimitris Tsipras Chulin Xie Xinyun Chen Avi Schwarzschild D. Song A. Madry Bo-wen Li Tom Goldstein SILM 27 270 0 18 Dec 2020
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
An Exploratory Analysis on Users' Contributions in Federated Learning Jiyue Huang Rania Talbi Zilong Zhao S. Bouchenak L. Chen Stefanie Roos FedML 26 30 0 13 Nov 2020