iDLG: Improved Deep Leakage from Gradients

8 January 2020

Papers citing "iDLG: Improved Deep Leakage from Gradients"

50 / 349 papers shown

Title
SPEAR++: Scaling Gradient Inversion via Sparsely-Used Dictionary Learning Alexander Bakarsky Dimitar I. Dimitrov Maximilian Baader Martin Vechev FedML 32 0 0 28 Oct 2025
Differential Privacy: Gradient Leakage Attacks in Federated Learning Environments Miguel Fernandez-de-Retana Unai Zulaika Rubén Sánchez-Corcuera Aitor Almeida FedML 68 0 0 27 Oct 2025
CLIP: Client-Side Invariant Pruning for Mitigating Stragglers in Secure Federated Learning Anthony DiMaggio Raghav Sharma Gururaj Saileshwar 24 0 0 19 Oct 2025
SVDefense: Effective Defense against Gradient Inversion Attacks via Singular Value Decomposition Chenxiang Luo David K.Y. Yau Qun Song AAML 60 0 0 01 Oct 2025
CoSIFL: Collaborative Secure and Incentivized Federated Learning with Differential Privacy Zhanhong Xie Meifan Zhang Lihua Yin FedML 50 0 0 27 Sep 2025
Non-Linear Trajectory Modeling for Multi-Step Gradient Inversion Attacks in Federated Learning Li Xia Zheng Liu Sili Huang Wei Tang Xuan Liu AAML 48 0 0 26 Sep 2025
Advancing Practical Homomorphic Encryption for Federated Learning: Theoretical Guarantees and Efficiency Optimizations Ren-Yi Huang Dumindu Samaraweera Prashant Shekhar J. Morris Chang FedML 40 0 0 24 Sep 2025
Uncovering Privacy Vulnerabilities through Analytical Gradient Inversion Attacks T. Eltaras Q. Malluhi Alessandro Savino S. Di Carlo Adnan Qayyum AAML 94 0 0 23 Sep 2025
Differentially private federated learning for localized control of infectious disease dynamics Raouf Kerkouche Henrik Zunker Mario Fritz Martin J. Kühn 8 0 0 17 Sep 2025
MAGIA: Sensing Per-Image Signals from Single-Round Averaged Gradients for Label-Inference-Free Gradient Inversion Zhanting Zhou Jinbo Wang Zeqin Wu Fengli Zhang 36 0 0 17 Sep 2025
MAUI: Reconstructing Private Client Data in Federated Transfer Learning Ahaan Dabholkar Atul Sharma Z. Berkay Celik S. Bagchi 60 0 0 14 Sep 2025
Balancing Utility and Privacy: Dynamically Private SGD with Random Projection Zhanhong Jiang Md Zahid Hasan Nastaran Saadati Aditya Balu Chao Liu Soumik Sarkar 59 0 0 11 Sep 2025
Images in Motion?: A First Look into Video Leakage in Collaborative Deep Learning Md Fazle Rasul Alanood Alqobaisi Bruhadeshwar Bezawada I. Ray AAML FedML 48 0 0 11 Sep 2025
AI-in-the-Loop: Privacy Preserving Real-Time Scam Detection and Conversational Scambaiting by Leveraging LLMs and Federated Learning Ismail Hossain Sai Puppala Sajedul Talukder Md. jahangir Alam 64 0 0 04 Sep 2025
Adversarial Robustness in Distributed Quantum Machine Learning Pouya Kananian Hans-Arno Jacobsen OOD AAML 68 0 0 16 Aug 2025
Deciphering the Interplay between Attack and Protection Complexity in Privacy-Preserving Federated Learning Xiaojin Zhang Mingcong Xu Yiming Li Wei Chen Qiang Yang 48 0 0 16 Aug 2025
Label Inference Attacks against Federated Unlearning Wei Wang Xiangyun Tang Y. Wang Yijing Lin Tao Zhang Meng Shen Dusit Niyato Liehuang Zhu 64 0 0 09 Aug 2025
SelectiveShield: Lightweight Hybrid Defense Against Gradient Leakage in Federated Learning Borui Li Li Yan Jianmin Liu FedML 76 0 0 06 Aug 2025
Evaluating the Dynamics of Membership Privacy in Deep Learning Yuetian Chen Zhiqi Wang Nathalie Baracaldo S. Kadhe Lei Yu MIACV 166 1 0 31 Jul 2025
Hypernetworks for Model-Heterogeneous Personalized Federated Learning Chen Zhang Husheng Li Xiang Liu Linshan Jiang Danxin Wang FedML 74 0 0 30 Jul 2025
Uncovering Gradient Inversion Risks in Practical Language Model TrainingConference on Computer and Communications Security (CCS), 2024 Xinguo Feng Zhongkui Ma Zihan Wang Eu Joe Chegne Mengyao Ma Alsharif Abuadbba Guangdong Bai 114 7 0 28 Jul 2025
Who Owns This Sample: Cross-Client Membership Inference Attack in Federated Graph Neural Networks K. Li Di Wu Jun Bai Jing Xu Lei Yang Ziyi Zhang Yiliao Song Wencheng Yang Taotao Cai Yan Li AAML FedML 100 0 0 26 Jul 2025
Shift Happens: Mixture of Experts based Continual Adaptation in Federated Learning R. Bhope K.R. Jayaram Praveen Venkateswaran N. Venkatasubramanian OOD 133 0 0 23 Jun 2025
ImprovDML: Improved Trade-off in Private Byzantine-Resilient Distributed Machine Learning Bing Liu Chengcheng Zhao L. Chai Peng Cheng Yaonan Wang FedML 95 0 0 18 Jun 2025
Byzantine Outside, Curious Inside: Reconstructing Data Through Malicious Updates Kai Yue Richeng Jin Chau-Wai Wong H. Dai AAML 130 0 0 13 Jun 2025
Secure Distributed Learning for CAVs: Defending Against Gradient Leakage with Leveled Homomorphic Encryption Muhammad Ali Najjar Ren-Yi Huang Dumindu Samaraweera Prashant Shekhar FedML 119 0 0 09 Jun 2025
DRAUN: An Algorithm-Agnostic Data Reconstruction Attack on Federated Unlearning Systems Hithem Lamri Manaar Alam Haiyan Jiang Michail Maniatakos MU 107 0 0 02 Jun 2025
Privacy-preserving Prompt Personalization in Federated Learning for Multimodal Large Language Models Sizai Hou Songze Li Baturalp Buyukates 139 1 0 28 May 2025
Label Leakage in Federated Inertial-based Human Activity Recognition Marius Bock Maximilian Hopp Kristof Van Laerhoven Michael Moeller AAML 204 0 0 27 May 2025
LAPA-based Dynamic Privacy Optimization for Wireless Federated Learning in Heterogeneous Environments Pengcheng Sun Erwu Liu Wei Ni Rui Wang Yuanzhe Geng Lijuan Lai Abbas Jamalipour 141 0 0 26 May 2025
EC-LDA : Label Distribution Inference Attack against Federated Graph Learning with Embedding Compression Tong Cheng Fu Jie Xinpeng Ling Huifa Li Zhili Chen Haifeng Qian Junqing Gong AAML FedML 161 0 0 21 May 2025
Efficient Privacy-Preserving Cross-Silo Federated Learning with Multi-Key Homomorphic Encryption Abdullah Al Omar Xin Yang Euijin Choo Omid Ardakanian 112 0 0 20 May 2025
Cutting Through Privacy: A Hyperplane-Based Data Reconstruction Attack in Federated LearningConference on Uncertainty in Artificial Intelligence (UAI), 2025 Francesco Diana André Nusser Chuan Xu Giovanni Neglia 243 0 0 15 May 2025
PEEL the Layers and Find Yourself: Revisiting Inference-time Data Leakage for Residual Neural Networks Huzaifa Arif K. Murugesan Payel Das Alex Gittens Pin-Yu Chen AAML 149 0 0 08 Apr 2025
Secure Generalization through Stochastic Bidirectional Parameter Updates Using Dual-Gradient Mechanism Shourya Goel Himanshi Tibrewal Anant Jain Anshul Pundhir Pravendra Singh FedML 203 0 0 03 Apr 2025
On Model Protection in Federated Learning against Eavesdropping Attacks Dipankar Maity Kushal Chakrabarti FedML 181 1 0 02 Apr 2025
TS-Inverse: A Gradient Inversion Attack Tailored for Federated Time Series Forecasting Models Caspar Meijer Jiyue Huang Shreshtha Sharma Elena Lazovik Lydia Y. Chen AI4TS 107 1 0 26 Mar 2025
Towards a Barrier-free GeoQA Portal: Natural Language Interaction with Geospatial Data Using Multi-Agent LLMs and Semantic SearchInternational Journal of Applied Earth Observation and Geoinformation (JAEOG), 2025 Yu Feng Puzhen Zhang Guohui Xiao Linfang Ding Liqiu Meng AI4CE 229 0 0 18 Mar 2025
Empirical Calibration and Metric Differential Privacy in Language Models Pedro Faustini Natasha Fernandes Annabelle McIver Mark Dras 168 0 0 18 Mar 2025
PAUSE: Low-Latency and Privacy-Aware Active User Selection for Federated Learning Ori Peleg Natalie Lang Stefano Rini Stefano Rini Nir Shlezinger Kobi Cohen FedML 183 0 0 17 Mar 2025
From Centralized to Decentralized Federated Learning: Theoretical Insights, Privacy Preservation, and Robustness Challenges Qiongxiu Li Wenrui Yu Yufei Xia Jun Pang FedML 161 4 0 10 Mar 2025
FedEM: A Privacy-Preserving Framework for Concurrent Utility Preservation in Federated Learning Mingcong Xu Xiaojin Zhang Wei Chen Hai Jin FedML 132 0 0 08 Mar 2025
GRAIN: Exact Graph Reconstruction from GradientsInternational Conference on Learning Representations (ICLR), 2025 Maria Drencheva Ivo Petrov Maximilian Baader Dimitar I. Dimitrov Martin Vechev FedML 202 3 0 03 Mar 2025
A Survey of Model Extraction Attacks and Defenses in Distributed Computing Environments Kaixiang Zhao Lincan Li Kaize Ding Neil Zhenqiang Gong Yue Zhao Yushun Dong AAML 128 6 0 22 Feb 2025
E-3SFC: Communication-Efficient Federated Learning with Double-way Features SynthesizingIEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), 2025 Yuhao Zhou Yuxin Tian Mingjia Shi Yuanxi Li Yanan Sun Qing Ye Jiancheng Lv 109 2 0 05 Feb 2025
CENSOR: Defense Against Gradient Inversion via Orthogonal Subspace Bayesian SamplingNetwork and Distributed System Security Symposium (NDSS), 2025 Kaiyuan Zhang Siyuan Cheng Guangyu Shen Bruno Ribeiro Shengwei An Pin-Yu Chen Xinming Zhang Ninghui Li 508 6 0 28 Jan 2025
CYCle: Choosing Your Collaborators Wisely to Enhance Collaborative Fairness in Decentralized Learning Nurbek Tastan Samuel Horváth Karthik Nandakumar FedML 186 2 0 21 Jan 2025
Fed-AugMix: Balancing Privacy and Utility via Data Augmentation HaoYang Li Wei Chen Xiaojin Zhang FedML 173 0 0 18 Dec 2024
Just a Simple Transformation is Enough for Data Protection in Vertical Federated Learning Andrei Semenov Philip Zmushko Alexander Pichugin Aleksandr Beznosikov 175 0 0 16 Dec 2024
Training Data Reconstruction: Privacy due to Uncertainty? Christina Runkel Kanchana Vaishnavi Gandikota Jonas Geiping Carola-Bibiane Schönlieb Michael Moeller 109 2 0 11 Dec 2024