Abnormal Client Behavior Detection in Federated Learning

22 October 2019

Yang Liu

Papers citing "Abnormal Client Behavior Detection in Federated Learning"

21 / 21 papers shown

Title
Using Anomaly Detection to Detect Poisoning Attacks in Federated Learning Applications Ali Raza Shujun Li K. Tran L. Koehl Kim Duc Tran AAML 85 4 0 18 Jul 2022
On the Convergence of FedAvg on Non-IID Data Xiang Li Kaixuan Huang Wenhao Yang Shusen Wang Zhihua Zhang FedML 138 2,333 0 04 Jul 2019
Distributed Training with Heterogeneous Data: Bridging Median- and Mean-Based Algorithms Xiangyi Chen Tiancong Chen Haoran Sun Zhiwei Steven Wu Mingyi Hong FedML 44 74 0 04 Jun 2019
Incentive Design for Efficient Federated Learning in Mobile Networks: A Contract Theory Approach Jiawen Kang Zehui Xiong Dusit Niyato Han Yu Ying-Chang Liang Dong In Kim FedML 49 215 0 16 May 2019
Towards Federated Learning at Scale: System Design Keith Bonawitz Hubert Eichner W. Grieskamp Dzmitry Huba A. Ingerman ... H. B. McMahan Timon Van Overveldt David Petrou Daniel Ramage Jason Roselander FedML 121 2,660 0 04 Feb 2019
Federated Optimization in Heterogeneous Networks Tian Li Anit Kumar Sahu Manzil Zaheer Maziar Sanjabi Ameet Talwalkar Virginia Smith FedML 173 5,168 0 14 Dec 2018
LEAF: A Benchmark for Federated Settings S. Caldas Sai Meher Karthik Duddu Peter Wu Tian Li Jakub Konecný H. B. McMahan Virginia Smith Ameet Talwalkar FedML 134 1,419 0 03 Dec 2018
Analyzing Federated Learning through an Adversarial Lens A. Bhagoji Supriyo Chakraborty Prateek Mittal S. Calo FedML 276 1,054 0 29 Nov 2018
RSA: Byzantine-Robust Stochastic Aggregation Methods for Distributed Learning from Heterogeneous Datasets Liping Li Canran Xu Xiangnan He Yixin Cao Tat-Seng Chua FedML 109 593 0 09 Nov 2018
Multi-Institutional Deep Learning Modeling Without Sharing Patient Data: A Feasibility Study on Brain Tumor Segmentation Micah J. Sheller G. A. Reina Brandon Edwards Jason Martin Spyridon Bakas FedML 61 465 0 10 Oct 2018
Sparsified SGD with Memory Sebastian U. Stich Jean-Baptiste Cordonnier Martin Jaggi 71 749 0 20 Sep 2018
Privacy-Preserving Deep Learning via Weight Transmission L. T. Phong T. Phuong FedML 53 87 0 10 Sep 2018
Parallel Restarted SGD with Faster Convergence and Less Communication: Demystifying Why Model Averaging Works for Deep Learning Hao Yu Sen Yang Shenghuo Zhu MoMe FedML 73 605 0 17 Jul 2018
How To Backdoor Federated Learning Eugene Bagdasaryan Andreas Veit Yiqing Hua D. Estrin Vitaly Shmatikov SILM FedML 94 1,913 0 02 Jul 2018
Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates Dong Yin Yudong Chen Kannan Ramchandran Peter L. Bartlett OOD FedML 113 1,498 0 05 Mar 2018
Differentially Private Federated Learning: A Client Level Perspective Robin C. Geyer T. Klein Moin Nabi FedML 116 1,294 0 20 Dec 2017
Federated Multi-Task Learning Virginia Smith Chao-Kai Chiang Maziar Sanjabi Ameet Talwalkar FedML 148 1,807 0 30 May 2017
Practical Secure Aggregation for Federated Learning on User-Held Data Keith Bonawitz Vladimir Ivanov Ben Kreuter Antonio Marcedone H. B. McMahan Sarvar Patel Daniel Ramage Aaron Segal Karn Seth FedML 71 501 0 14 Nov 2016
Federated Learning: Strategies for Improving Communication Efficiency Jakub Konecný H. B. McMahan Felix X. Yu Peter Richtárik A. Suresh Dave Bacon FedML 293 4,642 0 18 Oct 2016
Deep Learning with Differential Privacy Martín Abadi Andy Chu Ian Goodfellow H. B. McMahan Ilya Mironov Kunal Talwar Li Zhang FedML SyDa 191 6,109 0 01 Jul 2016
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 380 17,437 0 17 Feb 2016