SparseFed: Mitigating Model Poisoning Attacks in Federated Learning with Sparsification

12 December 2021

Papers citing "SparseFed: Mitigating Model Poisoning Attacks in Federated Learning with Sparsification"

41 / 41 papers shown

Title
Sparsification Under Siege: Defending Against Poisoning Attacks in Communication-Efficient Federated Learning Zhiyong Jin Runhua Xu Chong Li Y. Liu Jianxin Li AAML FedML 39 0 0 30 Apr 2025
Like Oil and Water: Group Robustness Methods and Poisoning Defenses May Be at Odds Michael-Andrei Panaitescu-Liess Yigitcan Kaya Sicheng Zhu Furong Huang Tudor Dumitras AAML 37 0 0 02 Apr 2025
Towards Resilient Federated Learning in CyberEdge Networks: Recent Advances and Future Trends Kai Li Zhengyang Zhang Azadeh Pourkabirian Wei Ni Falko Dressler Ozgur B. Akan 50 0 0 01 Apr 2025
Data Poisoning in Deep Learning: A Survey Pinlong Zhao Weiyao Zhu Pengfei Jiao Di Gao Ou Wu AAML 39 0 0 27 Mar 2025
Detecting Backdoor Attacks in Federated Learning via Direction Alignment Inspection Jiahao Xu Zikai Zhang Rui Hu AAML FedML Presented at ResearchTrend Connect \| FedML on 28 Mar 2025 152 0 0 11 Mar 2025
Trustworthy Federated Learning: Privacy, Security, and Beyond Chunlu Chen Ji Liu Haowen Tan Xingjian Li Kevin I-Kai Wang Peng Li Kouichi Sakurai Dejing Dou FedML 52 3 0 03 Nov 2024
EAB-FL: Exacerbating Algorithmic Bias through Model Poisoning Attacks in Federated Learning Syed Irfan Ali Meerza Jian-Dong Liu 37 2 0 02 Oct 2024
Privacy Attack in Federated Learning is Not Easy: An Experimental Study Hangyu Zhu Liyuan Huang Zhenping Xie FedML 26 0 0 28 Sep 2024
Federated Learning for Smart Grid: A Survey on Applications and Potential Vulnerabilities Zikai Zhang Suman Rath Jiaohao Xu Tingsong Xiao 48 1 0 16 Sep 2024
Achieving Byzantine-Resilient Federated Learning via Layer-Adaptive Sparsified Model Aggregation Jiahao Xu Zikai Zhang Rui Hu 44 4 0 02 Sep 2024
Random Gradient Masking as a Defensive Measure to Deep Leakage in Federated Learning Joon Kim Sejin Park AAML FedML 40 1 0 15 Aug 2024
A Unified Learn-to-Distort-Data Framework for Privacy-Utility Trade-off in Trustworthy Federated Learning Xiaojin Zhang Mingcong Xu Wei Chen FedML 29 0 0 05 Jul 2024
Teach LLMs to Phish: Stealing Private Information from Language Models Ashwinee Panda Christopher A. Choquette-Choo Zhengming Zhang Yaoqing Yang Prateek Mittal PILM 37 20 0 01 Mar 2024
Trustworthy Distributed AI Systems: Robustness, Privacy, and Governance Wenqi Wei Ling Liu 31 16 0 02 Feb 2024
The Landscape of Modern Machine Learning: A Review of Machine, Distributed and Federated Learning Omer Subasi Oceane Bel Joseph Manzano Kevin J. Barker FedML OOD PINN 25 2 0 05 Dec 2023
PA-iMFL: Communication-Efficient Privacy Amplification Method against Data Reconstruction Attack in Improved Multi-Layer Federated Learning Jianhua Wang Xiaolin Chang Jelena Mivsić Vojislav B. Mivsić Zhi Chen Junchao Fan 39 2 0 25 Sep 2023
Byzantine-Robust Federated Learning with Variance Reduction and Differential Privacy Zikai Zhang Rui Hu 38 11 0 07 Sep 2023
FTA: Stealthy and Adaptive Backdoor Attack with Flexible Triggers on Federated Learning Yanqi Qiao Dazhuang Liu Congwen Chen Rui Wang Kaitai Liang FedML AAML 38 1 0 31 Aug 2023
A Four-Pronged Defense Against Byzantine Attacks in Federated Learning Wei Wan Shengshan Hu Minghui Li Jianrong Lu Longling Zhang Leo Yu Zhang Hai Jin AAML FedML 42 20 0 07 Aug 2023
Fairness and Privacy-Preserving in Federated Learning: A Survey Taki Hasan Rafi Faiza Anan Noor Tahmid Hussain Dong-Kyu Chae FedML 35 39 0 14 Jun 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
Unlocking the Potential of Federated Learning for Deeper Models Hao Wang Xuefeng Liu Jianwei Niu Shaojie Tang Jiaxing Shen FedML AI4CE 11 1 0 05 Jun 2023
CRS-FL: Conditional Random Sampling for Communication-Efficient and Privacy-Preserving Federated Learning Jianhua Wang Xiaolin Chang J. Misic Vojislav B. Mišić Lin Li Yingying Yao FedML 19 3 0 01 Jun 2023
Understanding and Improving Model Averaging in Federated Learning on Heterogeneous Data Tailin Zhou Zehong Lin Jinchao Zhang Danny H. K. Tsang MoMe FedML 38 12 0 13 May 2023
Joint Compression and Deadline Optimization for Wireless Federated Learning Maojun Zhang Yongqian Li Dongzhu Liu Richeng Jin Guangxu Zhu Caijun Zhong Tony Q. S. Quek 27 5 0 06 May 2023
Denial-of-Service or Fine-Grained Control: Towards Flexible Model Poisoning Attacks on Federated Learning Hangtao Zhang Zeming Yao L. Zhang Shengshan Hu Chao Chen Alan Liew Zhetao Li 24 9 0 21 Apr 2023
Get Rid Of Your Trail: Remotely Erasing Backdoors in Federated Learning Manaar Alam Hithem Lamri Michail Maniatakos FedML AAML MU 26 14 0 20 Apr 2023
A Survey on Secure and Private Federated Learning Using Blockchain: Theory and Application in Resource-constrained Computing Ervin Moore Ahmed Imteaj S. Rezapour M. Amini 33 18 0 24 Mar 2023
Recent Advances on Federated Learning: A Systematic Survey Bingyan Liu Nuoyan Lv Yuanchun Guo Yawen Li FedML 60 78 0 03 Jan 2023
Robust Learning Protocol for Federated Tumor Segmentation Challenge Ambrish Rawat Giulio Zizzo S. Kadhe J. Epperlein S. Braghin FedML 28 3 0 16 Dec 2022
A New Linear Scaling Rule for Private Adaptive Hyperparameter Optimization Ashwinee Panda Xinyu Tang Saeed Mahloujifar Vikash Sehwag Prateek Mittal 43 11 0 08 Dec 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
Invariant Aggregator for Defending against Federated Backdoor Attacks Xiaoya Wang Dimitrios Dimitriadis Oluwasanmi Koyejo Shruti Tople FedML 37 1 0 04 Oct 2022
On the Impossible Safety of Large AI Models El-Mahdi El-Mhamdi Sadegh Farhadkhani R. Guerraoui Nirupam Gupta L. Hoang Rafael Pinot Sébastien Rouault John Stephan 30 31 0 30 Sep 2022
Communication-Efficient {Federated} Learning Using Censored Heavy Ball Descent Yicheng Chen Rick S. Blum Brian M. Sadler FedML 24 4 0 24 Sep 2022
FOCUS: Fairness via Agent-Awareness for Federated Learning on Heterogeneous Data Wen-Hsuan Chu Chulin Xie Wei Ping Linyi Li Lang Yin Arash Nourian Hantong Zhao Bo-wen Li FedML 21 12 0 21 Jul 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 32 130 0 12 Jun 2022
Federated Progressive Sparsification (Purge, Merge, Tune)+ Dimitris Stripelis Umang Gupta Greg Ver Steeg J. Ambite FedML 23 9 0 26 Apr 2022
EIFFeL: Ensuring Integrity for Federated Learning A. Chowdhury Chuan Guo S. Jha L. V. D. van der Maaten FedML 77 73 0 23 Dec 2021
FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping Xiaoyu Cao Minghong Fang Jia Liu Neil Zhenqiang Gong FedML 117 611 0 27 Dec 2020
Analyzing Federated Learning through an Adversarial Lens A. Bhagoji Supriyo Chakraborty Prateek Mittal S. Calo FedML 191 1,032 0 29 Nov 2018