Local Model Poisoning Attacks to Byzantine-Robust Federated Learning

26 November 2019

Papers citing "Local Model Poisoning Attacks to Byzantine-Robust Federated Learning"

50 / 151 papers shown

Title
Communication Compression for Byzantine Robust Learning: New Efficient Algorithms and Improved Rates Ahmad Rammal Kaja Gruntkowska Nikita Fedin Eduard A. Gorbunov Peter Richtárik 37 5 0 15 Oct 2023
Enabling Quartile-based Estimated-Mean Gradient Aggregation As Baseline for Federated Image Classifications Yusen Wu Jamie Deng Hao Chen Phuong Nguyen Yelena Yesha FedML 23 0 0 21 Sep 2023
Byzantine-Robust Federated Learning with Variance Reduction and Differential Privacy Zikai Zhang Rui Hu 30 11 0 07 Sep 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
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 29 20 0 07 Aug 2023
Compressed Private Aggregation for Scalable and Robust Federated Learning over Massive Networks Natalie Lang Nir Shlezinger Rafael G. L. DÓliveira S. E. Rouayheb FedML 70 4 0 01 Aug 2023
High Dimensional Distributed Gradient Descent with Arbitrary Number of Byzantine Attackers Puning Zhao Zhiguo Wan OOD FedML 38 4 0 25 Jul 2023
A Survey of What to Share in Federated Learning: Perspectives on Model Utility, Privacy Leakage, and Communication Efficiency Jiawei Shao Zijian Li Wenqiang Sun Tailin Zhou Yuchang Sun Lumin Liu Zehong Lin Yuyi Mao Jun Zhang FedML 37 23 0 20 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
Hiding in Plain Sight: Differential Privacy Noise Exploitation for Evasion-resilient Localized Poisoning Attacks in Multiagent Reinforcement Learning Md Tamjid Hossain Hung M. La AAML 16 0 0 01 Jul 2023
When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions Weiming Zhuang Chen Chen Lingjuan Lyu C. L. P. Chen Yaochu Jin Lingjuan Lyu AIFin AI4CE 99 85 0 27 Jun 2023
A First Order Meta Stackelberg Method for Robust Federated Learning Yunian Pan Tao Li Henger Li Tianyi Xu Zizhan Zheng Quanyan Zhu FedML 29 10 0 23 Jun 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 23 43 0 17 Jun 2023
Avoid Adversarial Adaption in Federated Learning by Multi-Metric Investigations T. Krauß Alexandra Dmitrienko AAML 19 4 0 06 Jun 2023
A Framework for Incentivized Collaborative Learning Xinran Wang Qi Le Ahmad Faraz Khan Jie Ding A. Anwar FedML 37 4 0 26 May 2023
PS-FedGAN: An Efficient Federated Learning Framework Based on Partially Shared Generative Adversarial Networks For Data Privacy Achintha Wijesinghe Songyang Zhang Zhi Ding FedML 24 7 0 19 May 2023
Attacks on Robust Distributed Learning Schemes via Sensitivity Curve Maximization Christian A. Schroth Stefan Vlaski A. Zoubir FedML 53 1 0 27 Apr 2023
Blockchain-based Federated Learning with SMPC Model Verification Against Poisoning Attack for Healthcare Systems Aditya Pribadi Kalapaaking Ibrahim Khalil X. Yi 19 41 0 26 Apr 2023
Protecting Federated Learning from Extreme Model Poisoning Attacks via Multidimensional Time Series Anomaly Detection Edoardo Gabrielli Dimitri Belli Vittorio Miori Gabriele Tolomei AAML 13 4 0 29 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 84 47 0 21 Feb 2023
Revisiting Personalized Federated Learning: Robustness Against Backdoor Attacks Zeyu Qin Liuyi Yao Daoyuan Chen Yaliang Li Bolin Ding Minhao Cheng FedML 35 25 0 03 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
Poisoning Attacks and Defenses in Federated Learning: A Survey S. Sagar Chang-Sun Li S. W. Loke Jinho D. Choi OOD FedML 18 9 0 14 Jan 2023
XMAM:X-raying Models with A Matrix to Reveal Backdoor Attacks for Federated Learning Jianyi Zhang Fangjiao Zhang Qichao Jin Zhiqiang Wang Xiaodong Lin X. Hei AAML FedML 32 0 0 28 Dec 2022
Skefl: Single-Key Homomorphic Encryption for Secure Federated Learning Dongfang Zhao FedML 17 0 0 21 Dec 2022
FairRoad: Achieving Fairness for Recommender Systems with Optimized Antidote Data Minghong Fang Jia-Wei Liu Michinari Momma Yi Sun 19 4 0 13 Dec 2022
Security Analysis of SplitFed Learning M. A. Khan Virat Shejwalkar Amir Houmansadr Fatima M. Anwar FedML 13 11 0 04 Dec 2022
Castell: Scalable Joint Probability Estimation of Multi-dimensional Data Randomized with Local Differential Privacy H. Kikuchi 16 2 0 03 Dec 2022
Federated Learning Attacks and Defenses: A Survey Yao Chen Yijie Gui Hong Lin Wensheng Gan Yongdong Wu FedML 38 29 0 27 Nov 2022
FedCut: A Spectral Analysis Framework for Reliable Detection of Byzantine Colluders Hanlin Gu Lixin Fan Xingxing Tang Qiang Yang AAML FedML 20 1 0 24 Nov 2022
Resilience of Wireless Ad Hoc Federated Learning against Model Poisoning Attacks Naoya Tezuka H. Ochiai Yuwei Sun Hiroshi Esaki AAML 29 4 0 07 Nov 2022
Robust Distributed Learning Against Both Distributional Shifts and Byzantine Attacks Guanqiang Zhou Ping Xu Yue Wang Zhi Tian OOD FedML 23 4 0 29 Oct 2022
Security-Preserving Federated Learning via Byzantine-Sensitive Triplet Distance Youngjoon Lee Sangwoo Park Joonhyuk Kang FedML 38 7 0 29 Oct 2022
Robustness of Locally Differentially Private Graph Analysis Against Poisoning Jacob Imola A. Chowdhury Kamalika Chaudhuri AAML 20 6 0 25 Oct 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 40 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 15 73 0 20 Oct 2022
Federated Learning based on Defending Against Data Poisoning Attacks in IoT Jiayin Li Wenzhong Guo Xingshuo Han Jianping Cai Ximeng Liu AAML 75 1 0 14 Sep 2022
Unraveling the Connections between Privacy and Certified Robustness in Federated Learning Against Poisoning Attacks Chulin Xie Yunhui Long Pin-Yu Chen Qinbin Li Arash Nourian Sanmi Koyejo Bo Li FedML 35 13 0 08 Sep 2022
Network-Level Adversaries in Federated Learning Giorgio Severi Matthew Jagielski Gokberk Yar Yuxuan Wang Alina Oprea Cristina Nita-Rotaru FedML 18 17 0 27 Aug 2022
MUDGUARD: Taming Malicious Majorities in Federated Learning using Privacy-Preserving Byzantine-Robust Clustering Rui Wang Xingkai Wang H. Chen Jérémie Decouchant S. Picek Z. Liu K. Liang 29 1 0 22 Aug 2022
Byzantines can also Learn from History: Fall of Centered Clipping in Federated Learning Kerem Ozfatura Emre Ozfatura Alptekin Kupcu Deniz Gunduz AAML FedML 28 13 0 21 Aug 2022
Federated Learning for Medical Applications: A Taxonomy, Current Trends, Challenges, and Future Research Directions A. Rauniyar D. Hagos Debesh Jha J. E. Haakegaard Ulas Bagci D. Rawat Vladimir Vlassov OOD 41 91 0 05 Aug 2022
FLDetector: Defending Federated Learning Against Model Poisoning Attacks via Detecting Malicious Clients Zaixi Zhang Xiaoyu Cao Jin Jia Neil Zhenqiang Gong AAML FedML 13 214 0 19 Jul 2022
MUD-PQFed: Towards Malicious User Detection in Privacy-Preserving Quantized Federated Learning Hua Ma Qun Li Yifeng Zheng Zhi Zhang Xiaoning Liu Yan Gao S. Al-Sarawi Derek Abbott FedML 26 3 0 19 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 25 3 0 18 Jul 2022
Suppressing Poisoning Attacks on Federated Learning for Medical Imaging Naif Alkhunaizi Dmitry Kamzolov Martin Takávc Karthik Nandakumar OOD 15 9 0 15 Jul 2022
Enhanced Security and Privacy via Fragmented Federated Learning N. Jebreel J. Domingo-Ferrer Alberto Blanco-Justicia David Sánchez FedML 18 26 0 13 Jul 2022
Federated and Transfer Learning: A Survey on Adversaries and Defense Mechanisms Ehsan Hallaji R. Razavi-Far M. Saif AAML FedML 19 13 0 05 Jul 2022
Backdoor Attack is a Devil in Federated GAN-based Medical Image Synthesis Ruinan Jin Xiaoxiao Li AAML FedML MedIm 31 12 0 02 Jul 2022
DECK: Model Hardening for Defending Pervasive Backdoors Guanhong Tao Yingqi Liu Shuyang Cheng Shengwei An Zhuo Zhang Qiuling Xu Guangyu Shen Xiangyu Zhang AAML 18 7 0 18 Jun 2022