Evaluating Gradient Inversion Attacks and Defenses in Federated Learning

30 November 2021

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

50 / 143 papers shown

Title
FedLoGe: Joint Local and Generic Federated Learning under Long-tailed Data Zikai Xiao Zihan Chen Liyinglan Liu Yang Feng Jian Wu Wanlu Liu Qiufeng Wang Howard H. Yang Zuo-Qiang Liu FedML 39 6 0 17 Jan 2024
AIJack: Let's Hijack AI! Security and Privacy Risk Simulator for Machine Learning Hideaki Takahashi SILM 35 2 0 29 Dec 2023
Foreseeing Reconstruction Quality of Gradient Inversion: An Optimization Perspective H. Hong Yooshin Cho Hanbyel Cho Jaesung Ahn Junmo Kim 17 0 0 19 Dec 2023
Enabling End-to-End Secure Federated Learning in Biomedical Research on Heterogeneous Computing Environments with APPFLx Trung-Hieu Hoang Jordan D. Fuhrman Ravi K. Madduri Miao Li Pranshu Chaturvedi ... Kibaek Kim Minseok Ryu Ryan Chard Eliu A. Huerta Maryellen L. Giger 26 5 0 14 Dec 2023
Beyond Gradient and Priors in Privacy Attacks: Leveraging Pooler Layer Inputs of Language Models in Federated Learning Jianwei Li Sheng Liu Qi Lei PILM SILM AAML 30 4 0 10 Dec 2023
Privacy-preserving quantum federated learning via gradient hiding Changhao Li Niraj Kumar Zhixin Song Shouvanik Chakrabarti Marco Pistoia FedML 31 19 0 07 Dec 2023
Data-Agnostic Model Poisoning against Federated Learning: A Graph Autoencoder Approach Kai Li Jingjing Zheng Xinnan Yuan W. Ni Ozgur B. Akan H. Vincent Poor AAML 27 15 0 30 Nov 2023
FedHCA $^2$ : Towards Hetero-Client Federated Multi-Task Learning Yuxiang Lu Suizhi Huang Yuwen Yang Shalayiding Sirejiding Yue Ding Hongtao Lu FedML 50 3 0 22 Nov 2023
Scale-MIA: A Scalable Model Inversion Attack against Secure Federated Learning via Latent Space Reconstruction Shanghao Shi Ning Wang Yang Xiao Chaoyu Zhang Yi Shi Y. T. Hou W. Lou 13 7 0 10 Nov 2023
Maximum Knowledge Orthogonality Reconstruction with Gradients in Federated Learning Feng Wang Senem Velipasalar M. C. Gursoy 25 2 0 30 Oct 2023
RAIFLE: Reconstruction Attacks on Interaction-based Federated Learning with Adversarial Data Manipulation Dzung Pham Shreyas Kulkarni Amir Houmansadr 33 0 0 29 Oct 2023
FedTherapist: Mental Health Monitoring with User-Generated Linguistic Expressions on Smartphones via Federated Learning Jaemin Shin Hyungjun Yoon Seungjoo Lee Sungjoon Park Yunxin Liu Jinho D. Choi Sung-Ju Lee 32 5 0 25 Oct 2023
FLTrojan: Privacy Leakage Attacks against Federated Language Models Through Selective Weight Tampering Md. Rafi Ur Rashid Vishnu Asutosh Dasu Kang Gu Najrin Sultana Shagufta Mehnaz AAML FedML 46 10 0 24 Oct 2023
Privacy-Preserving Encrypted Low-Dose CT Denoising Ziyuan Yang Huijie Huangfu Maosong Ran Zhiwen Wang Hui Yu Yi Zhang 31 0 0 13 Oct 2023
Fed-GraB: Federated Long-tailed Learning with Self-Adjusting Gradient Balancer Zikai Xiao Zihan Chen Songshan Liu Hualiang Wang Yang Feng Jinxiang Hao Qiufeng Wang Jian Wu Howard H. Yang Zuo-Qiang Liu FedML 32 10 0 11 Oct 2023
Federated Learning with Reduced Information Leakage and Computation Tongxin Yin Xueru Zhang Mohammad Mahdi Khalili Mingyan Liu FedML 31 2 0 10 Oct 2023
A Survey of Incremental Transfer Learning: Combining Peer-to-Peer Federated Learning and Domain Incremental Learning for Multicenter Collaboration Yixing Huang Christoph Bert Rostislav Makarov Alexander Alenin Andreas Maier F. Putz FedML CLL 24 1 0 29 Sep 2023
Privacy Assessment on Reconstructed Images: Are Existing Evaluation Metrics Faithful to Human Perception? Xiaoxiao Sun Nidham Gazagnadou Vivek Sharma Lingjuan Lyu Hongdong Li Liang Zheng 47 7 0 22 Sep 2023
Understanding Deep Gradient Leakage via Inversion Influence Functions Haobo Zhang Junyuan Hong Yuyang Deng M. Mahdavi Jiayu Zhou FedML 67 6 0 22 Sep 2023
Expressive variational quantum circuits provide inherent privacy in federated learning Niraj Kumar Jamie Heredge Changhao Li Shaltiel Eloul Shree Hari Sureshbabu Marco Pistoia FedML 59 8 0 22 Sep 2023
Enabling Quartile-based Estimated-Mean Gradient Aggregation As Baseline for Federated Image Classifications Yusen Wu Jamie Deng Hao Chen Phuong Nguyen Yelena Yesha FedML 26 0 0 21 Sep 2023
User Assignment and Resource Allocation for Hierarchical Federated Learning over Wireless Networks Tinghao Zhang Kwok-Yan Lam Jun Zhao 22 2 0 17 Sep 2023
Privacy Preserving Federated Learning with Convolutional Variational Bottlenecks Daniel Scheliga Patrick Mäder M. Seeland FedML AAML 26 5 0 08 Sep 2023
Internal Cross-layer Gradients for Extending Homogeneity to Heterogeneity in Federated Learning Yun-Hin Chan Rui Zhou Running Zhao Zhihan Jiang Edith C. H. Ngai FedML 35 8 0 22 Aug 2023
Federated Learning on Patient Data for Privacy-Protecting Polycystic Ovary Syndrome Treatment Lucía Morris Tori Qiu Nikhil Raghuraman 27 0 0 22 Aug 2023
Unlocking Accuracy and Fairness in Differentially Private Image Classification Leonard Berrada Soham De J. Shen Jamie Hayes Robert Stanforth David Stutz Pushmeet Kohli Samuel L. Smith Borja Balle 27 13 0 21 Aug 2023
FLShield: A Validation Based Federated Learning Framework to Defend Against Poisoning Attacks Ehsanul Kabir Zeyu Song Md. Rafi Ur Rashid Shagufta Mehnaz 24 6 0 10 Aug 2023
GIFD: A Generative Gradient Inversion Method with Feature Domain Optimization Hao Fang Bin Chen Xuan Wang Zhi Wang Shutao Xia 51 32 0 09 Aug 2023
Compressed Private Aggregation for Scalable and Robust Federated Learning over Massive Networks Natalie Lang Nir Shlezinger Rafael G. L. DÓliveira S. E. Rouayheb FedML 75 4 0 01 Aug 2023
Federated Learning for Data and Model Heterogeneity in Medical Imaging Hussain Ahmad Madni Rao Muhammad Umer G. Foresti FedML 23 4 0 31 Jul 2023
MAS: Towards Resource-Efficient Federated Multiple-Task Learning Weiming Zhuang Yonggang Wen Lingjuan Lyu Shuai Zhang FedML 30 15 0 21 Jul 2023
Deconstructing Data Reconstruction: Multiclass, Weight Decay and General Losses G. Buzaglo Niv Haim Gilad Yehudai Gal Vardi Yakir Oz Yaniv Nikankin Michal Irani 34 10 0 04 Jul 2023
FeSViBS: Federated Split Learning of Vision Transformer with Block Sampling Faris Almalik Naif Alkhunaizi Ibrahim Almakky Karthik Nandakumar FedML MedIm 24 9 0 26 Jun 2023
Privacy and Fairness in Federated Learning: on the Perspective of Trade-off Huiqiang Chen Tianqing Zhu Tao Zhang Wanlei Zhou Philip S. Yu FedML 29 43 0 25 Jun 2023
Fairness and Privacy-Preserving in Federated Learning: A Survey Taki Hasan Rafi Faiza Anan Noor Tahmid Hussain Dong-Kyu Chae FedML 35 39 0 14 Jun 2023
SRATTA : Sample Re-ATTribution Attack of Secure Aggregation in Federated Learning Tanguy Marchand Regis Loeb Ulysse Marteau-Ferey Jean Ogier du Terrail Arthur Pignet FedML 42 4 0 13 Jun 2023
Hiding in Plain Sight: Disguising Data Stealing Attacks in Federated Learning Kostadin Garov Dimitar I. Dimitrov Nikola Jovanović Martin Vechev AAML FedML 39 7 0 05 Jun 2023
GPT-FL: Generative Pre-trained Model-Assisted Federated Learning Tuo Zhang Tiantian Feng Samiul Alam Dimitrios Dimitriadis Sunwoo Lee Mi Zhang Shrikanth S. Narayanan Salman Avestimehr FedML 13 27 0 03 Jun 2023
Surrogate Model Extension (SME): A Fast and Accurate Weight Update Attack on Federated Learning Junyi Zhu Ruicong Yao Matthew B. Blaschko FedML 8 9 0 31 May 2023
Adaptive Self-Distillation for Minimizing Client Drift in Heterogeneous Federated Learning M.Yashwanth Gaurav Kumar Nayak Aryaveer Singh Yogesh Singh Anirban Chakraborty FedML 30 1 0 31 May 2023
Securing Distributed SGD against Gradient Leakage Threats Wenqi Wei Ling Liu Jingya Zhou Ka-Ho Chow Yanzhao Wu FedML 26 18 0 10 May 2023
Reconstructing Training Data from Multiclass Neural Networks G. Buzaglo Niv Haim Gilad Yehudai Gal Vardi Michal Irani 33 4 0 05 May 2023
FedCBO: Reaching Group Consensus in Clustered Federated Learning through Consensus-based Optimization J. Carrillo Nicolas García Trillos Sixu Li Yuhua Zhu FedML 31 17 0 04 May 2023
Selective Knowledge Sharing for Privacy-Preserving Federated Distillation without A Good Teacher Jiawei Shao Fangzhao Wu Jun Zhang FedML 26 26 0 04 Apr 2023
Bounding Training Data Reconstruction in DP-SGD Jamie Hayes Saeed Mahloujifar Borja Balle AAML FedML 33 39 0 14 Feb 2023
An Experimental Study of Byzantine-Robust Aggregation Schemes in Federated Learning Shenghui Li Edith C. H. Ngai Thiemo Voigt FedML AAML 23 53 0 14 Feb 2023
$z$ -SignFedAvg: A Unified Stochastic Sign-based Compression for Federated Learning Zhiwei Tang Yanmeng Wang Tsung-Hui Chang FedML 21 14 0 06 Feb 2023
Revisiting Personalized Federated Learning: Robustness Against Backdoor Attacks Zeyu Qin Liuyi Yao Daoyuan Chen Yaliang Li Bolin Ding Minhao Cheng FedML 38 25 0 03 Feb 2023
On the Efficacy of Differentially Private Few-shot Image Classification Marlon Tobaben Aliaksandra Shysheya J. Bronskill Andrew J. Paverd Shruti Tople Santiago Zanella Béguelin Richard Turner Antti Honkela 38 11 0 02 Feb 2023
Does Federated Learning Really Need Backpropagation? H. Feng Tianyu Pang Chao Du Wei Chen Shuicheng Yan Min-Bin Lin FedML 36 10 0 28 Jan 2023