Get Rid Of Your Trail: Remotely Erasing Backdoors in Federated Learning

20 April 2023

Papers citing "Get Rid Of Your Trail: Remotely Erasing Backdoors in Federated Learning"

49 / 49 papers shown

Title
FedQUIT: On-Device Federated Unlearning via a Quasi-Competent Virtual Teacher Alessio Mora Lorenzo Valerio Paolo Bellavista A. Passarella FedML MU 111 2 0 14 Aug 2024
BayBFed: Bayesian Backdoor Defense for Federated Learning Kavita Kumari Phillip Rieger Hossein Fereidooni Murtuza Jadliwala A. Sadeghi AAML FedML 59 33 0 23 Jan 2023
On the Vulnerability of Backdoor Defenses for Federated Learning Pei Fang Jinghui Chen FedML 55 32 0 19 Jan 2023
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 90 56 0 23 Oct 2022
Thinking Two Moves Ahead: Anticipating Other Users Improves Backdoor Attacks in Federated Learning Yuxin Wen Jonas Geiping Liam H. Fowl Hossein Souri Ramalingam Chellappa Micah Goldblum Tom Goldstein AAML SILM FedML 78 9 0 17 Oct 2022
Vertical Semi-Federated Learning for Efficient Online Advertising Wenjie Li Qiaolin Xia Hao Cheng Kouying Xue Shutao Xia FedML 90 14 0 30 Sep 2022
A Knowledge Distillation-Based Backdoor Attack in Federated Learning Yifan Wang Wei Fan Keke Yang Naji Alhusaini Jing Li AAML FedML 54 3 0 12 Aug 2022
Federated Unlearning: How to Efficiently Erase a Client in FL? Anisa Halimi S. Kadhe Ambrish Rawat Nathalie Baracaldo MU 72 129 0 12 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 86 137 0 12 Jun 2022
PerDoor: Persistent Non-Uniform Backdoors in Federated Learning using Adversarial Perturbations Manaar Alam Esha Sarkar Michail Maniatakos AAML FedML 113 8 0 26 May 2022
VeriFi: Towards Verifiable Federated Unlearning Xiangshan Gao Xingjun Ma Jingyi Wang Youcheng Sun Bo Li S. Ji Peng Cheng Jiming Chen MU 94 48 0 25 May 2022
The Right to be Forgotten in Federated Learning: An Efficient Realization with Rapid Retraining Yi Liu Lei Xu Lizhen Qu Cong Wang Bo Li MU 61 146 0 14 Mar 2022
Backdoor Defense in Federated Learning Using Differential Testing and Outlier Detection Y. Kim Huili Chen F. Koushanfar FedML AAML 61 9 0 21 Feb 2022
Backdoor Defense with Machine Unlearning Yang Liu Mingyuan Fan Cen Chen Ximeng Liu Zhuo Ma Li Wang Jianfeng Ma AAML 70 75 0 24 Jan 2022
Federated Unlearning with Knowledge Distillation Chen Wu Sencun Zhu P. Mitra MU 49 109 0 24 Jan 2022
DeepSight: Mitigating Backdoor Attacks in Federated Learning Through Deep Model Inspection Phillip Rieger T. D. Nguyen Markus Miettinen A. Sadeghi FedML AAML 87 154 0 03 Jan 2022
SparseFed: Mitigating Model Poisoning Attacks in Federated Learning with Sparsification Ashwinee Panda Saeed Mahloujifar A. Bhagoji Supriyo Chakraborty Prateek Mittal FedML AAML 53 87 0 12 Dec 2021
Forget-SVGD: Particle-Based Bayesian Federated Unlearning J. Gong Osvaldo Simeone Rahif Kassab Joonhyuk Kang FedML MU 86 24 0 23 Nov 2021
Federated Unlearning via Class-Discriminative Pruning Junxiao Wang Song Guo Xin Xie Heng Qi MU 42 142 0 22 Oct 2021
Hard to Forget: Poisoning Attacks on Certified Machine Unlearning Neil G. Marchant Benjamin I. P. Rubinstein Scott Alfeld MU AAML 72 71 0 17 Sep 2021
Machine Unlearning of Features and Labels Alexander Warnecke Lukas Pirch Christian Wressnegger Konrad Rieck MU 78 186 0 26 Aug 2021
Federated Learning for Open Banking Guodong Long Yue Tan Jing Jiang Chengqi Zhang AIFin FedML 85 275 0 24 Aug 2021
Back to the Drawing Board: A Critical Evaluation of Poisoning Attacks on Production Federated Learning Virat Shejwalkar Amir Houmansadr Peter Kairouz Daniel Ramage AAML 100 216 0 23 Aug 2021
Bayesian Variational Federated Learning and Unlearning in Decentralized Networks J. Gong Osvaldo Simeone Joonhyuk Kang FedML MU 44 13 0 08 Apr 2021
Remember What You Want to Forget: Algorithms for Machine Unlearning Ayush Sekhari Jayadev Acharya Gautam Kamath A. Suresh FedML MU 83 308 0 04 Mar 2021
Dynamic backdoor attacks against federated learning Anbu Huang AAML FedML 36 20 0 15 Nov 2020
BaFFLe: Backdoor detection via Feedback-based Federated Learning Sébastien Andreina G. Marson Helen Möllering Ghassan O. Karame FedML 60 138 0 04 Nov 2020
Mitigating Backdoor Attacks in Federated Learning Chen Wu Xian Yang Sencun Zhu P. Mitra FedML AAML 76 104 0 28 Oct 2020
Amnesiac Machine Learning Laura Graves Vineel Nagisetty Vijay Ganesh MU MIACV 75 267 0 21 Oct 2020
Attack of the Tails: Yes, You Really Can Backdoor Federated Learning Hongyi Wang Kartik K. Sreenivasan Shashank Rajput Harit Vishwakarma Saurabh Agarwal Jy-yong Sohn Kangwook Lee Dimitris Papailiopoulos FedML 76 606 0 09 Jul 2020
Defending against Backdoors in Federated Learning with Robust Learning Rate Mustafa Safa Ozdayi Murat Kantarcioglu Yulia R. Gel FedML 56 169 0 07 Jul 2020
Descent-to-Delete: Gradient-Based Methods for Machine Unlearning Seth Neel Aaron Roth Saeed Sharifi-Malvajerdi MU 70 271 0 06 Jul 2020
The Future of Digital Health with Federated Learning Nicola Rieke Jonny Hancox Wenqi Li Fausto Milletari H. Roth ... Ronald M. Summers Andrew Trask Daguang Xu Maximilian Baust M. Jorge Cardoso OOD 259 1,774 0 18 Mar 2020
Forgetting Outside the Box: Scrubbing Deep Networks of Information Accessible from Input-Output Observations Aditya Golatkar Alessandro Achille Stefano Soatto MU OOD 123 195 0 05 Mar 2020
Machine Unlearning Lucas Bourtoule Varun Chandrasekaran Christopher A. Choquette-Choo Hengrui Jia Adelin Travers Baiwu Zhang David Lie Nicolas Papernot MU 120 868 0 09 Dec 2019
PyTorch: An Imperative Style, High-Performance Deep Learning Library Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury ... Sasank Chilamkurthy Benoit Steiner Lu Fang Junjie Bai Soumith Chintala ODL 496 42,449 0 03 Dec 2019
Can You Really Backdoor Federated Learning? Ziteng Sun Peter Kairouz A. Suresh H. B. McMahan FedML 75 572 0 18 Nov 2019
Eternal Sunshine of the Spotless Net: Selective Forgetting in Deep Networks Aditya Golatkar Alessandro Achille Stefano Soatto CLL MU 73 495 0 12 Nov 2019
Certified Data Removal from Machine Learning Models Chuan Guo Tom Goldstein Awni Y. Hannun Laurens van der Maaten MU 107 446 0 08 Nov 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 2,666 0 04 Feb 2019
Federated Learning for Mobile Keyboard Prediction Andrew Straiton Hard Kanishka Rao Zhifeng Lin Swaroop Indra Ramaswamy Youjie Li S. Augenstein Alex Schwing M. Annavaram A. Avestimehr FedML 136 1,541 0 08 Nov 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
Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates Dong Yin Yudong Chen Kannan Ramchandran Peter L. Bartlett OOD FedML 121 1,500 0 05 Mar 2018
Federated Multi-Task Learning Virginia Smith Chao-Kai Chiang Maziar Sanjabi Ameet Talwalkar FedML 152 1,809 0 30 May 2017
Federated Learning: Strategies for Improving Communication Efficiency Jakub Konecný H. B. McMahan Felix X. Yu Peter Richtárik A. Suresh Dave Bacon FedML 306 4,646 0 18 Oct 2016
Federated Optimization: Distributed Machine Learning for On-Device Intelligence Jakub Konecný H. B. McMahan Daniel Ramage Peter Richtárik FedML 138 1,899 0 08 Oct 2016
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 406 17,486 0 17 Feb 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.2K 194,020 0 10 Dec 2015
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 1.6K 100,386 0 04 Sep 2014