A Little Is Enough: Circumventing Defenses For Distributed Learning

16 February 2019

Papers citing "A Little Is Enough: Circumventing Defenses For Distributed Learning"

32 / 32 papers shown

Title
Performance Guaranteed Poisoning Attacks in Federated Learning: A Sliding Mode Approach Huazi Pan Yanjun Zhang Leo Yu Zhang Scott Adams Abbas Kouzani Suiyang Khoo FedML 41 0 0 22 May 2025
Unlearning for Federated Online Learning to Rank: A Reproducibility Study Yiling Tao Shuyi Wang Jiaxi Yang Guido Zuccon MU 39 0 0 19 May 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 186 2 0 11 Mar 2025
On the Byzantine Fault Tolerance of signSGD with Majority Vote Emanuele Mengoli Luzius Moll Virgilio Strozzi El-Mahdi El-Mhamdi AAML FedML 89 0 0 26 Feb 2025
FedSV: Byzantine-Robust Federated Learning via Shapley Value Khaoula Otmani Rachid Elazouzi Vincent Labatut FedML AAML 145 2 0 24 Feb 2025
Decentralized and Robust Privacy-Preserving Model Using Blockchain-Enabled Federated Deep Learning in Intelligent Enterprises Reza Fotohi Fereidoon Shams Aliee Bahar Farahani FedML 109 8 0 18 Feb 2025
Dual Defense: Enhancing Privacy and Mitigating Poisoning Attacks in Federated Learning Runhua Xu Shiqi Gao Chao Li J. Joshi Jianxin Li 59 2 0 08 Feb 2025
LiD-FL: Towards List-Decodable Federated Learning Hong Liu Liren Shan Han Bao Ronghui You Yuhao Yi Jiancheng Lv FedML 116 0 0 09 Aug 2024
A Mirror Descent-Based Algorithm for Corruption-Tolerant Distributed Gradient Descent Shuche Wang Vincent Y. F. Tan FedML OOD 65 1 0 19 Jul 2024
On the Byzantine-Resilience of Distillation-Based Federated Learning Christophe Roux Max Zimmer Sebastian Pokutta AAML 102 1 0 19 Feb 2024
FedCC: Robust Federated Learning against Model Poisoning Attacks Hyejun Jeong Hamin Son Seohu Lee Jayun Hyun Tai-Myoung Chung FedML 88 6 0 05 Dec 2022
Detecting Backdoor Attacks on Deep Neural Networks by Activation Clustering Bryant Chen Wilka Carvalho Wenjie Li Heiko Ludwig Benjamin Edwards Chengyao Chen Ziqiang Cao Biplav Srivastava AAML 77 786 0 09 Nov 2018
Spectral Signatures in Backdoor Attacks Brandon Tran Jerry Li Aleksander Madry AAML 73 778 0 01 Nov 2018
Mitigating Sybils in Federated Learning Poisoning Clement Fung Chris J. M. Yoon Ivan Beschastnikh AAML 51 498 0 14 Aug 2018
How To Backdoor Federated Learning Eugene Bagdasaryan Andreas Veit Yiqing Hua D. Estrin Vitaly Shmatikov SILM FedML 80 1,892 0 02 Jul 2018
DRACO: Byzantine-resilient Distributed Training via Redundant Gradients Lingjiao Chen Hongyi Wang Zachary B. Charles Dimitris Papailiopoulos 38 244 0 27 Mar 2018
Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates Dong Yin Yudong Chen Kannan Ramchandran Peter L. Bartlett OOD FedML 84 1,483 0 05 Mar 2018
Generalized Byzantine-tolerant SGD Cong Xie Oluwasanmi Koyejo Indranil Gupta AAML 68 257 0 27 Feb 2018
The Hidden Vulnerability of Distributed Learning in Byzantium El-Mahdi El-Mhamdi R. Guerraoui Sébastien Rouault AAML FedML 65 743 0 22 Feb 2018
An Alternative View: When Does SGD Escape Local Minima? Robert D. Kleinberg Yuanzhi Li Yang Yuan MLT 62 316 0 17 Feb 2018
Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning Xinyun Chen Chang-rui Liu Yue Liu Kimberly Lu D. Song AAML SILM 86 1,822 0 15 Dec 2017
Learning Discrete Distributions from Untrusted Batches Mingda Qiao Gregory Valiant FedML 53 34 0 22 Nov 2017
Poseidon: An Efficient Communication Architecture for Distributed Deep Learning on GPU Clusters Huatian Zhang Zeyu Zheng Shizhen Xu Wei-Ming Dai Qirong Ho Xiaodan Liang Zhiting Hu Jinliang Wei P. Xie Eric Xing GNN 56 343 0 11 Jun 2017
Certified Defenses for Data Poisoning Attacks Jacob Steinhardt Pang Wei Koh Percy Liang AAML 75 751 0 09 Jun 2017
Federated Learning: Strategies for Improving Communication Efficiency Jakub Konecný H. B. McMahan Felix X. Yu Peter Richtárik A. Suresh Dave Bacon FedML 271 4,620 0 18 Oct 2016
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima N. Keskar Dheevatsa Mudigere J. Nocedal M. Smelyanskiy P. T. P. Tang ODL 380 2,922 0 15 Sep 2016
Wide Residual Networks Sergey Zagoruyko N. Komodakis 281 7,951 0 23 May 2016
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 251 17,328 0 17 Feb 2016
Adding Gradient Noise Improves Learning for Very Deep Networks Arvind Neelakantan Luke Vilnis Quoc V. Le Ilya Sutskever Lukasz Kaiser Karol Kurach James Martens AI4CE ODL 59 544 0 21 Nov 2015
Automatic differentiation in machine learning: a survey A. G. Baydin Barak A. Pearlmutter Alexey Radul J. Siskind PINN AI4CE ODL 141 2,775 0 20 Feb 2015
Poisoning Attacks against Support Vector Machines Battista Biggio B. Nelson Pavel Laskov AAML 107 1,580 0 27 Jun 2012
HOGWILD!: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent Feng Niu Benjamin Recht Christopher Ré Stephen J. Wright 150 2,272 0 28 Jun 2011