Inverting Gradients -- How easy is it to break privacy in federated learning?

31 March 2020

Papers citing "Inverting Gradients -- How easy is it to break privacy in federated learning?"

27 / 177 papers shown

Title
Federated Learning for Internet of Things: Applications, Challenges, and Opportunities Tuo Zhang Lei Gao Chaoyang He Mi Zhang Bhaskar Krishnamachari Salman Avestimehr FedML 19 168 0 15 Nov 2021
Bayesian Framework for Gradient Leakage Mislav Balunović Dimitar I. Dimitrov Robin Staab Martin Vechev FedML 16 41 0 08 Nov 2021
Privacy attacks for automatic speech recognition acoustic models in a federated learning framework N. Tomashenko Salima Mdhaffar Marc Tommasi Yannick Esteve J. Bonastre 33 25 0 06 Nov 2021
Confidential Machine Learning Computation in Untrusted Environments: A Systems Security Perspective Kha Dinh Duy Taehyun Noh Siwon Huh Hojoon Lee 56 9 0 05 Nov 2021
What Do We Mean by Generalization in Federated Learning? Honglin Yuan Warren Morningstar Lin Ning K. Singhal OOD FedML 24 71 0 27 Oct 2021
Robbing the Fed: Directly Obtaining Private Data in Federated Learning with Modified Models Liam H. Fowl Jonas Geiping W. Czaja Micah Goldblum Tom Goldstein FedML 10 144 0 25 Oct 2021
SoK: Machine Learning Governance Varun Chandrasekaran Hengrui Jia Anvith Thudi Adelin Travers Mohammad Yaghini Nicolas Papernot 30 16 0 20 Sep 2021
Privacy-Preserving Machine Learning: Methods, Challenges and Directions Runhua Xu Nathalie Baracaldo J. Joshi 24 100 0 10 Aug 2021
Private Retrieval, Computing and Learning: Recent Progress and Future Challenges S. Ulukus Salman Avestimehr Michael C. Gastpar S. Jafar Ravi Tandon Chao Tian FedML 20 64 0 30 Jul 2021
Defending against Reconstruction Attack in Vertical Federated Learning Jiankai Sun Yuanshun Yao Weihao Gao Junyuan Xie Chong-Jun Wang AAML FedML 6 28 0 21 Jul 2021
Gradient-Leakage Resilient Federated Learning Wenqi Wei Ling Liu Yanzhao Wu Gong Su Arun Iyengar FedML 19 81 0 02 Jul 2021
Federated Learning with Buffered Asynchronous Aggregation John Nguyen Kshitiz Malik Hongyuan Zhan Ashkan Yousefpour Michael G. Rabbat Mani Malek Dzmitry Huba FedML 13 288 0 11 Jun 2021
Rethinking Architecture Design for Tackling Data Heterogeneity in Federated Learning Liangqiong Qu Yuyin Zhou Paul Pu Liang Yingda Xia Feifei Wang Ehsan Adeli L. Fei-Fei D. Rubin FedML AI4CE 19 173 0 10 Jun 2021
Vertical Federated Learning without Revealing Intersection Membership Jiankai Sun Xin Yang Yuanshun Yao Aonan Zhang Weihao Gao Junyuan Xie Chong-Jun Wang FedML 23 37 0 10 Jun 2021
Privacy-Preserving Federated Learning on Partitioned Attributes Shuang Zhang Liyao Xiang Xi Yu Pengzhi Chu Yingqi Chen Chen Cen L. Wang FedML 16 2 0 29 Apr 2021
From Distributed Machine Learning to Federated Learning: A Survey Ji Liu Jizhou Huang Yang Zhou Xuhong Li Shilei Ji Haoyi Xiong Dejing Dou FedML OOD 44 243 0 29 Apr 2021
Property Inference Attacks on Convolutional Neural Networks: Influence and Implications of Target Model's Complexity Mathias Parisot Balázs Pejó Dayana Spagnuelo MIACV 19 33 0 27 Apr 2021
See through Gradients: Image Batch Recovery via GradInversion Hongxu Yin Arun Mallya Arash Vahdat J. Álvarez Jan Kautz Pavlo Molchanov FedML 23 459 0 15 Apr 2021
Privacy-preserving medical image analysis Alexander Ziller Jonathan Passerat-Palmbach T. Ryffel Dmitrii Usynin Andrew Trask ... Jason V. Mancuso Marcus R. Makowski Daniel Rueckert R. Braren Georgios Kaissis 16 8 0 10 Dec 2020
Privacy Amplification by Decentralization Edwige Cyffers A. Bellet FedML 42 39 0 09 Dec 2020
Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective Jingwei Sun Ang Li Binghui Wang Huanrui Yang Hai Li Yiran Chen FedML 11 162 0 08 Dec 2020
A Federated Learning Approach to Anomaly Detection in Smart Buildings Raed Abdel Sater A. Ben Hamza 9 121 0 20 Oct 2020
R-GAP: Recursive Gradient Attack on Privacy Junyi Zhu Matthew Blaschko FedML 6 132 0 15 Oct 2020
Witches' Brew: Industrial Scale Data Poisoning via Gradient Matching Jonas Geiping Liam H. Fowl W. R. Huang W. Czaja Gavin Taylor Michael Moeller Tom Goldstein AAML 19 215 0 04 Sep 2020
Byzantine-Resilient Secure Federated Learning Jinhyun So Başak Güler A. Avestimehr FedML 11 236 0 21 Jul 2020
Rethinking Privacy Preserving Deep Learning: How to Evaluate and Thwart Privacy Attacks Lixin Fan Kam Woh Ng Ce Ju Tianyu Zhang Chang Liu Chee Seng Chan Qiang Yang MIACV 9 63 0 20 Jun 2020
Introducing the VoicePrivacy Initiative N. Tomashenko B. M. L. Srivastava Xin Wang Emmanuel Vincent A. Nautsch ... Nicholas W. D. Evans J. Patino J. Bonastre Paul-Gauthier Noé Massimiliano Todisco 28 127 0 04 May 2020