Evaluating Gradient Inversion Attacks and Defenses in Federated Learning

30 November 2021

Papers citing "Evaluating Gradient Inversion Attacks and Defenses in Federated Learning"

43 / 143 papers shown

Title
Why Batch Normalization Damage Federated Learning on Non-IID Data? Yanmeng Wang Qingjiang Shi Tsung-Hui Chang FedML 18 33 0 08 Jan 2023
Recent Advances on Federated Learning: A Systematic Survey Bingyan Liu Nuoyan Lv Yuanchun Guo Yawen Li FedML 60 78 0 03 Jan 2023
Reconstructing Training Data from Model Gradient, Provably Zihan Wang Jason D. Lee Qi Lei FedML 32 24 0 07 Dec 2022
DYNAFED: Tackling Client Data Heterogeneity with Global Dynamics Renjie Pi Weizhong Zhang Yueqi Xie Jiahui Gao Xiaoyu Wang Sunghun Kim Qifeng Chen DD 39 26 0 20 Nov 2022
Directional Privacy for Deep Learning Pedro Faustini Natasha Fernandes Shakila Mahjabin Tonni Annabelle McIver Mark Dras 19 1 0 09 Nov 2022
Local Model Reconstruction Attacks in Federated Learning and their Uses Ilias Driouich Chuan Xu Giovanni Neglia F. Giroire Eoin Thomas AAML FedML 36 2 0 28 Oct 2022
Backdoor Attack and Defense in Federated Generative Adversarial Network-based Medical Image Synthesis Ruinan Jin Xiaoxiao Li FedML AAML MedIm 50 23 0 19 Oct 2022
TabLeak: Tabular Data Leakage in Federated Learning Mark Vero Mislav Balunović Dimitar I. Dimitrov Martin Vechev FedML 37 7 0 04 Oct 2022
Concealing Sensitive Samples against Gradient Leakage in Federated Learning Jing Wu Munawar Hayat Min Zhou Mehrtash Harandi FedML 16 10 0 13 Sep 2022
Privacy of Autonomous Vehicles: Risks, Protection Methods, and Future Directions Chulin Xie Zhong Cao Yunhui Long Diange Yang Ding Zhao Bo-wen Li 19 4 0 08 Sep 2022
A Framework for Evaluating Privacy-Utility Trade-off in Vertical Federated Learning Yan Kang Jiahuan Luo Yuanqin He Xiaojin Zhang Lixin Fan Qiang Yang FedML 11 15 0 08 Sep 2022
Joint Privacy Enhancement and Quantization in Federated Learning Natalie Lang Elad Sofer Tomer Shaked Nir Shlezinger FedML 37 46 0 23 Aug 2022
Personalizing or Not: Dynamically Personalized Federated Learning with Incentives Zichen Ma Yu Lu Wenye Li Shuguang Cui FedML 11 1 0 12 Aug 2022
Dropout is NOT All You Need to Prevent Gradient Leakage Daniel Scheliga Patrick Mäder M. Seeland FedML 42 12 0 12 Aug 2022
FOCUS: Fairness via Agent-Awareness for Federated Learning on Heterogeneous Data Wen-Hsuan Chu Chulin Xie Wei Ping Linyi Li Lang Yin Arash Nourian Hantong Zhao Bo-wen Li FedML 27 12 0 21 Jul 2022
PASS: A Parameter Audit-based Secure and Fair Federated Learning Scheme against Free-Rider Attack Jianhua Wang Xiaolin Chang J. Misic Vojislav B. Mišić Yixiang Wang 24 7 0 15 Jul 2022
Smart Multi-tenant Federated Learning Weiming Zhuang Yonggang Wen Shuai Zhang FedML 36 2 0 09 Jul 2022
Backdoor Attack is a Devil in Federated GAN-based Medical Image Synthesis Ruinan Jin Xiaoxiao Li AAML FedML MedIm 39 12 0 02 Jul 2022
Class Impression for Data-free Incremental Learning Sana Ayromlou Purang Abolmaesumi Teresa S. M. Tsang Xiaoxiao Li 23 4 0 26 Jun 2022
Data Leakage in Federated Averaging Dimitar I. Dimitrov Mislav Balunović Nikola Konstantinov Martin Vechev FedML 27 28 0 24 Jun 2022
Reconstructing Training Data from Trained Neural Networks Niv Haim Gal Vardi Gilad Yehudai Ohad Shamir Michal Irani 40 132 0 15 Jun 2022
A Survey on Gradient Inversion: Attacks, Defenses and Future Directions Rui Zhang Song Guo Junxiao Wang Xin Xie Dacheng Tao 35 36 0 15 Jun 2022
Bilateral Dependency Optimization: Defending Against Model-inversion Attacks Xiong Peng Feng Liu Jingfeng Zhang Long Lan Junjie Ye Tongliang Liu Bo Han 16 34 0 11 Jun 2022
Gradient Obfuscation Gives a False Sense of Security in Federated Learning Kai Yue Richeng Jin Chau-Wai Wong D. Baron H. Dai FedML 36 46 0 08 Jun 2022
Subject Membership Inference Attacks in Federated Learning Anshuman Suri Pallika H. Kanani Virendra J. Marathe Daniel W. Peterson 30 25 0 07 Jun 2022
Recovering Private Text in Federated Learning of Language Models Samyak Gupta Yangsibo Huang Zexuan Zhong Tianyu Gao Kai Li Danqi Chen FedML 38 74 0 17 May 2022
GradViT: Gradient Inversion of Vision Transformers Ali Hatamizadeh Hongxu Yin H. Roth Wenqi Li Jan Kautz Daguang Xu Pavlo Molchanov ViT 25 63 0 22 Mar 2022
Feature Distribution Matching for Federated Domain Generalization Yuwei Sun Ng Chong H. Ochiai OOD 15 30 0 22 Mar 2022
The Right to be Forgotten in Federated Learning: An Efficient Realization with Rapid Retraining Yi Liu Lei Xu Xingliang Yuan Cong Wang Bo Li MU 30 142 0 14 Mar 2022
LAMP: Extracting Text from Gradients with Language Model Priors Mislav Balunović Dimitar I. Dimitrov Nikola Jovanović Martin Vechev 27 57 0 17 Feb 2022
Fishing for User Data in Large-Batch Federated Learning via Gradient Magnification Yuxin Wen Jonas Geiping Liam H. Fowl Micah Goldblum Tom Goldstein FedML 92 93 0 01 Feb 2022
Submodularity In Machine Learning and Artificial Intelligence J. Bilmes 8 53 0 31 Jan 2022
Transformers in Medical Imaging: A Survey Fahad Shamshad Salman Khan Syed Waqas Zamir Muhammad Haris Khan Munawar Hayat Fahad Shahbaz Khan Huazhu Fu ViT LM&MA MedIm 111 663 0 24 Jan 2022
Robust and Privacy-Preserving Collaborative Learning: A Comprehensive Survey Shangwei Guo Xu Zhang Feiyu Yang Tianwei Zhang Yan Gan Tao Xiang Yang Liu FedML 31 9 0 19 Dec 2021
On Predicting Generalization using GANs Yi Zhang Arushi Gupta Nikunj Saunshi Sanjeev Arora AI4CE 25 6 0 28 Nov 2021
Eluding Secure Aggregation in Federated Learning via Model Inconsistency Dario Pasquini Danilo Francati G. Ateniese FedML 28 101 0 14 Nov 2021
UniFed: A Unified Framework for Federated Learning on Non-IID Image Features Meirui Jiang Xiaoxiao Li Xiaofei Zhang Michael Kamp Qianming Dou FedML OOD 34 0 0 19 Oct 2021
Handling Data Heterogeneity with Generative Replay in Collaborative Learning for Medical Imaging Liangqiong Qu N. Balachandar Miao Zhang D. Rubin MedIm 22 19 0 24 Jun 2021
Quantifying and Localizing Usable Information Leakage from Neural Network Gradients Fan Mo Anastasia Borovykh Mohammad Malekzadeh Soteris Demetriou Deniz Gündüz Hamed Haddadi FedML 29 3 0 28 May 2021
Emerging Trends in Federated Learning: From Model Fusion to Federated X Learning Shaoxiong Ji Yue Tan Teemu Saravirta Zhiqin Yang Yixin Liu Lauri Vasankari Shirui Pan Guodong Long A. Walid FedML 37 76 0 25 Feb 2021
FedBN: Federated Learning on Non-IID Features via Local Batch Normalization Xiaoxiao Li Meirui Jiang Xiaofei Zhang Michael Kamp Qi Dou OOD FedML 168 790 0 15 Feb 2021
Privacy and Robustness in Federated Learning: Attacks and Defenses Lingjuan Lyu Han Yu Xingjun Ma Chen Chen Lichao Sun Jun Zhao Qiang Yang Philip S. Yu FedML 183 355 0 07 Dec 2020
InstaHide's Sample Complexity When Mixing Two Private Images Baihe Huang Zhao Song Runzhou Tao Junze Yin Ruizhe Zhang Danyang Zhuo MIACV 28 9 0 24 Nov 2020