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?"

50 / 177 papers shown

Title
LLM Security: Vulnerabilities, Attacks, Defenses, and Countermeasures Francisco Aguilera-Martínez Fernando Berzal PILM 50 0 0 02 May 2025
A Numerical Gradient Inversion Attack in Variational Quantum Neural-Networks Georgios Papadopoulos Shaltiel Eloul Yash Satsangi Jamie Heredge Niraj Kumar Chun-Fu Chen Marco Pistoia 51 0 0 17 Apr 2025
Quantifying Privacy Leakage in Split Inference via Fisher-Approximated Shannon Information Analysis Ruijun Deng Zhihui Lu Qiang Duan FedML 46 0 0 14 Apr 2025
Differentially Private 2D Human Pose Estimation Kaushik Bhargav Sivangi Idris Zakariyya Paul Henderson F. Deligianni 124 0 0 14 Apr 2025
Technical Insights and Legal Considerations for Advancing Federated Learning in Bioinformatics Daniele Malpetti Marco Scutari Francesco Gualdi Jessica van Setten Sander van der Laan Saskia Haitjema Aaron Mark Lee Isabelle Hering Francesca Mangili FedML AI4CE 107 1 0 12 Mar 2025
Controlled privacy leakage propagation throughout overlapping grouped learning Shahrzad Kiani Franziska Boenisch S. Draper FedML 72 0 0 06 Mar 2025
SpinML: Customized Synthetic Data Generation for Private Training of Specialized ML Models Jiang Zhang Rohan Sequeira Konstantinos Psounis SyDa 73 0 0 05 Mar 2025
Causality Is Key to Understand and Balance Multiple Goals in Trustworthy ML and Foundation Models Ruta Binkyte Ivaxi Sheth Zhijing Jin Mohammad Havaei Bernhard Schölkopf Mario Fritz 119 0 0 28 Feb 2025
Guarding the Privacy of Label-Only Access to Neural Network Classifiers via iDP Verification Anan Kabaha Dana Drachsler-Cohen AAML 43 0 0 23 Feb 2025
Towards Active Participant Centric Vertical Federated Learning: Some Representations May Be All You Need Jon Irureta Jon Imaz Aizea Lojo Javier Fernandez-Marques Marco González Iñigo Perona FedML 85 1 0 20 Feb 2025
Noise-Aware Algorithm for Heterogeneous Differentially Private Federated Learning Saber Malekmohammadi Yaoliang Yu Yang Cao FedML 83 5 0 17 Feb 2025
Privacy-Preserving Dataset Combination Keren Fuentes Mimee Xu Irene Chen 36 0 0 09 Feb 2025
CENSOR: Defense Against Gradient Inversion via Orthogonal Subspace Bayesian Sampling Kaiyuan Zhang Siyuan Cheng Guangyu Shen Bruno Ribeiro Shengwei An Pin-Yu Chen X. Zhang Ninghui Li 90 1 0 28 Jan 2025
PBM-VFL: Vertical Federated Learning with Feature and Sample Privacy Linh Tran Timothy Castiglia Stacy Patterson Ana Milanova FedML 40 0 0 23 Jan 2025
BlindFL: Segmented Federated Learning with Fully Homomorphic Encryption Evan Gronberg L. dÁliberti Magnus Saebo Aurora Hook FedML 41 0 0 20 Jan 2025
TAPFed: Threshold Secure Aggregation for Privacy-Preserving Federated Learning Runhua Xu Bo Li Chao Li J. Joshi Shuai Ma Jianxin Li FedML 33 10 0 10 Jan 2025
NET-SA: An Efficient Secure Aggregation Architecture Based on In-Network Computing Qingqing Ren Wen Wang Shuyong Zhu Zhiyuan Wu Yujun Zhang 35 0 0 02 Jan 2025
Attribute Inference Attacks for Federated Regression Tasks Francesco Diana Othmane Marfoq Chuan Xu Giovanni Neglia F. Giroire Eoin Thomas AAML 157 1 0 19 Nov 2024
Trustworthiness of Stochastic Gradient Descent in Distributed Learning Hongyang Li Caesar Wu Mohammed Chadli Said Mammar Pascal Bouvry 46 1 0 28 Oct 2024
Uncovering Attacks and Defenses in Secure Aggregation for Federated Deep Learning Yiwei Zhang R. Behnia A. Yavuz Reza Ebrahimi E. Bertino FedML 20 2 0 13 Oct 2024
Gradients Stand-in for Defending Deep Leakage in Federated Learning H. Yi H. Ren C. Hu Y. Li J. Deng Xin Xie FedML 25 0 0 11 Oct 2024
Differentially Private Active Learning: Balancing Effective Data Selection and Privacy Kristian Schwethelm Johannes Kaiser Jonas Kuntzer Mehmet Yigitsoy Daniel Rueckert Georgios Kaissis 32 0 0 01 Oct 2024
Advances in APPFL: A Comprehensive and Extensible Federated Learning Framework Zilinghan Li Shilan He Ze Yang Minseok Ryu Kibaek Kim Ravi K. Madduri FedML 52 5 0 17 Sep 2024
Risks When Sharing LoRA Fine-Tuned Diffusion Model Weights Dixi Yao 20 1 0 13 Sep 2024
Balancing Security and Accuracy: A Novel Federated Learning Approach for Cyberattack Detection in Blockchain Networks Tran Viet Khoa Mohammad Abu Alsheikh Yibeltal Alem D. Hoang FedML 26 3 0 08 Sep 2024
Universally Harmonizing Differential Privacy Mechanisms for Federated Learning: Boosting Accuracy and Convergence Shuya Feng Meisam Mohammady Hanbin Hong Shenao Yan Ashish Kundu Binghui Wang Yuan Hong FedML 36 3 0 20 Jul 2024
Gradient Inversion of Federated Diffusion Models Jiyue Huang Chi Hong Lydia Y. Chen Stefanie Roos FedML 34 1 0 30 May 2024
DAGER: Exact Gradient Inversion for Large Language Models Ivo Petrov Dimitar I. Dimitrov Maximilian Baader Mark Niklas Muller Martin Vechev FedML 51 3 0 24 May 2024
Leakage-Resilient and Carbon-Neutral Aggregation Featuring the Federated AI-enabled Critical Infrastructure Zehang Deng Ruoxi Sun Minhui Xue Sheng Wen S. Çamtepe Surya Nepal Yang Xiang 35 1 0 24 May 2024
DP-DyLoRA: Fine-Tuning Transformer-Based Models On-Device under Differentially Private Federated Learning using Dynamic Low-Rank Adaptation Jie Xu Karthikeyan P. Saravanan Rogier van Dalen Haaris Mehmood David Tuckey Mete Ozay 56 5 0 10 May 2024
On the Efficiency of Privacy Attacks in Federated Learning Nawrin Tabassum Ka-Ho Chow Xuyu Wang Wenbin Zhang Yanzhao Wu FedML 29 1 0 15 Apr 2024
You Can Use But Cannot Recognize: Preserving Visual Privacy in Deep Neural Networks Qiushi Li Yan Zhang Ju Ren Qi Li Yaoxue Zhang AAML PICV 36 23 0 05 Apr 2024
Threats, Attacks, and Defenses in Machine Unlearning: A Survey Ziyao Liu Huanyi Ye Chen Chen Yongsen Zheng K. Lam AAML MU 29 28 0 20 Mar 2024
Visual Privacy Auditing with Diffusion Models Kristian Schwethelm Johannes Kaiser Moritz Knolle Daniel Rueckert Daniel Rueckert Alexander Ziller DiffM AAML 33 0 0 12 Mar 2024
Data Reconstruction Attacks and Defenses: A Systematic Evaluation Sheng Liu Zihan Wang Yuxiao Chen Qi Lei AAML MIACV 59 4 0 13 Feb 2024
Decentralized Proactive Model Offloading and Resource Allocation for Split and Federated Learning Binbin Huang Hailiang Zhao Lingbin Wang Wenzhuo Qian Yuyu Yin Shuiguang Deng 29 0 0 09 Feb 2024
Federated Learning Priorities Under the European Union Artificial Intelligence Act Herbert Woisetschläger Alexander Erben Bill Marino Shiqiang Wang Nicholas D. Lane R. Mayer Hans-Arno Jacobsen 21 15 0 05 Feb 2024
Trustworthy Distributed AI Systems: Robustness, Privacy, and Governance Wenqi Wei Ling Liu 23 16 0 02 Feb 2024
Federated Continual Learning via Knowledge Fusion: A Survey Xin Yang Hao Yu Xin Gao Hao Wang Junbo Zhang Tianrui Li FedML 28 31 0 27 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 24 5 0 14 Dec 2023
Topology-Dependent Privacy Bound For Decentralized Federated Learning Qiongxiu Li Wenrui Yu Changlong Ji Richard Heusdens 16 3 0 13 Dec 2023
Privacy-preserving quantum federated learning via gradient hiding Changhao Li Niraj Kumar Zhixin Song Shouvanik Chakrabarti Marco Pistoia FedML 13 19 0 07 Dec 2023
A Survey on Vulnerability of Federated Learning: A Learning Algorithm Perspective Xianghua Xie Chen Hu Hanchi Ren Jingjing Deng FedML AAML 29 19 0 27 Nov 2023
RAIFLE: Reconstruction Attacks on Interaction-based Federated Learning with Adversarial Data Manipulation Dzung Pham Shreyas Kulkarni Amir Houmansadr 25 0 0 29 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 44 10 0 24 Oct 2023
Text Embeddings Reveal (Almost) As Much As Text John X. Morris Volodymyr Kuleshov Vitaly Shmatikov Alexander M. Rush RALM 26 94 0 10 Oct 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 39 7 0 22 Sep 2023
A Survey for Federated Learning Evaluations: Goals and Measures Di Chai Leye Wang Liu Yang Junxue Zhang Kai Chen Qian Yang ELM FedML 17 21 0 23 Aug 2023
GPFL: Simultaneously Learning Global and Personalized Feature Information for Personalized Federated Learning Jianqing Zhang Yang Hua Hao Wang Tao Song Zhengui Xue Ruhui Ma Jianyin Cao Haibing Guan 37 23 0 20 Aug 2023
Approximate and Weighted Data Reconstruction Attack in Federated Learning Yongcun Song Ziqi Wang Enrique Zuazua AAML FedML 16 4 0 13 Aug 2023