Towards Communication-efficient and Attack-Resistant Federated Edge Learning for Industrial Internet of Things

8 December 2020

Dusit Niyato

Papers citing "Towards Communication-efficient and Attack-Resistant Federated Edge Learning for Industrial Internet of Things"

36 / 36 papers shown

Title
Deep Anomaly Detection for Time-series Data in Industrial IoT: A Communication-Efficient On-device Federated Learning Approach Yi Liu S. Garg Jiangtian Nie Yan Zhang Zehui Xiong Jiawen Kang M. S. Hossain FedML 67 380 0 19 Jul 2020
Data Poisoning Attacks Against Federated Learning Systems Vale Tolpegin Stacey Truex Mehmet Emre Gursoy Ling Liu FedML 111 653 0 16 Jul 2020
Federated Learning for 6G Communications: Challenges, Methods, and Future Directions Yi Liu Lizhen Qu Zehui Xiong Jiawen Kang Xiaofei Wang Dusit Niyato FedML AI4CE 46 280 0 04 Jun 2020
A Secure Federated Learning Framework for 5G Networks Yi Liu Jia-Jie Peng Jiawen Kang Abdullah M. Iliyasu Dusit Niyato A. El-latif FedML 44 198 0 12 May 2020
A Framework for Evaluating Gradient Leakage Attacks in Federated Learning Wenqi Wei Ling Liu Margaret Loper Ka-Ho Chow Mehmet Emre Gursoy Stacey Truex Yanzhao Wu FedML 68 148 0 22 Apr 2020
Privacy-preserving Traffic Flow Prediction: A Federated Learning Approach Yi Liu James Jianqiao Yu Jiawen Kang Dusit Niyato Shuyu Zhang AI4TS 66 448 0 19 Mar 2020
Federated Variance-Reduced Stochastic Gradient Descent with Robustness to Byzantine Attacks Zhaoxian Wu Qing Ling Tianyi Chen G. Giannakis FedML AAML 81 183 0 29 Dec 2019
Local Model Poisoning Attacks to Byzantine-Robust Federated Learning Minghong Fang Xiaoyu Cao Jinyuan Jia Neil Zhenqiang Gong AAML OOD FedML 103 1,108 0 26 Nov 2019
Shielding Collaborative Learning: Mitigating Poisoning Attacks through Client-Side Detection Lingchen Zhao Shengshan Hu Qian Wang Jianlin Jiang Chao Shen Xiangyang Luo Pengfei Hu AAML 55 94 0 29 Oct 2019
Abnormal Client Behavior Detection in Federated Learning Suyi Li Yong Cheng Yang Liu Wei Wang Tianjian Chen AAML 51 134 0 22 Oct 2019
Reliable Federated Learning for Mobile Networks Jiawen Kang Zehui Xiong Dusit Niyato Y. Zou Yang Zhang Mohsen Guizani FedML 50 464 0 14 Oct 2019
PPGAN: Privacy-preserving Generative Adversarial Network Yi Liu Jialiang Peng James Jianqiao Yu Yi Wu 54 70 0 04 Oct 2019
Federated Learning: Challenges, Methods, and Future Directions Tian Li Anit Kumar Sahu Ameet Talwalkar Virginia Smith FedML 121 4,514 0 21 Aug 2019
DETOX: A Redundancy-based Framework for Faster and More Robust Gradient Aggregation Shashank Rajput Hongyi Wang Zachary B. Charles Dimitris Papailiopoulos FedML 62 133 0 29 Jul 2019
The Tradeoff Between Privacy and Accuracy in Anomaly Detection Using Federated XGBoost Mengwei Yang Linqi Song Jie Xu Congduan Li Guozhen Tan FedML 109 31 0 16 Jul 2019
Deep Leakage from Gradients Ligeng Zhu Zhijian Liu Song Han FedML 94 2,204 0 21 Jun 2019
Qsparse-local-SGD: Distributed SGD with Quantization, Sparsification, and Local Computations Debraj Basu Deepesh Data C. Karakuş Suhas Diggavi MQ 60 405 0 06 Jun 2019
Why gradient clipping accelerates training: A theoretical justification for adaptivity J.N. Zhang Tianxing He S. Sra Ali Jadbabaie 72 460 0 28 May 2019
Communication-Efficient Federated Deep Learning with Asynchronous Model Update and Temporally Weighted Aggregation Y. Chen Xiaoyan Sun Yaochu Jin FedML 59 442 0 18 Mar 2019
Asynchronous Federated Optimization Cong Xie Oluwasanmi Koyejo Indranil Gupta FedML 70 567 0 10 Mar 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 2,664 0 04 Feb 2019
Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference Attacks against Centralized and Federated Learning Milad Nasr Reza Shokri Amir Houmansadr FedML MIACV AAML 54 250 0 03 Dec 2018
Analyzing Federated Learning through an Adversarial Lens A. Bhagoji Supriyo Chakraborty Prateek Mittal S. Calo FedML 280 1,054 0 29 Nov 2018
A generic framework for privacy preserving deep learning Wenbo Guo Yunzhe Tao Morten Dahl Sui Huang Masashi Sugiyama Daniel Rueckert Lin Lin FedML 102 438 0 09 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 112 595 0 09 Nov 2018
The Convergence of Sparsified Gradient Methods Dan Alistarh Torsten Hoefler M. Johansson Sarit Khirirat Nikola Konstantinov Cédric Renggli 165 493 0 27 Sep 2018
Sparsified SGD with Memory Sebastian U. Stich Jean-Baptiste Cordonnier Martin Jaggi 74 750 0 20 Sep 2018
How To Backdoor Federated Learning Eugene Bagdasaryan Andreas Veit Yiqing Hua D. Estrin Vitaly Shmatikov SILM FedML 97 1,913 0 02 Jul 2018
ATOMO: Communication-efficient Learning via Atomic Sparsification Hongyi Wang Scott Sievert Zachary B. Charles Shengchao Liu S. Wright Dimitris Papailiopoulos 67 353 0 11 Jun 2018
DÏoT: A Federated Self-learning Anomaly Detection System for IoT T. D. Nguyen Samuel Marchal Markus Miettinen Hossein Fereidooni Nadarajah Asokan A. Sadeghi 131 493 0 20 Apr 2018
Byzantine Stochastic Gradient Descent Dan Alistarh Zeyuan Allen-Zhu Jingkai Li FedML 68 297 0 23 Mar 2018
Differentially Private Federated Learning: A Client Level Perspective Robin C. Geyer T. Klein Moin Nabi FedML 118 1,294 0 20 Dec 2017
Deep Gradient Compression: Reducing the Communication Bandwidth for Distributed Training Chengyue Wu Song Han Huizi Mao Yu Wang W. Dally 130 1,407 0 05 Dec 2017
Gradient Sparsification for Communication-Efficient Distributed Optimization Jianqiao Wangni Jialei Wang Ji Liu Tong Zhang 80 525 0 26 Oct 2017
Federated Learning: Strategies for Improving Communication Efficiency Jakub Konecný H. B. McMahan Felix X. Yu Peter Richtárik A. Suresh Dave Bacon FedML 297 4,643 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 203 6,121 0 01 Jul 2016