Papers citing 'Exploiting Unintended Feature Leakage in Collaborative Learning'

Title
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 638 6 0 28 Jan 2025
Fed-AugMix: Balancing Privacy and Utility via Data Augmentation HaoYang Li Wei Chen Xiaojin Zhang FedML 221 0 0 18 Dec 2024
Efficiently Achieving Secure Model Training and Secure Aggregation to Ensure Bidirectional Privacy-Preservation in Federated Learning Xue Yang Depan Peng Yan Feng Xiaohu Tang Weijun Fang Jun Shao FedML 182 0 0 16 Dec 2024
Learning Robust and Privacy-Preserving Representations via Information TheoryAAAI Conference on Artificial Intelligence (AAAI), 2024 Binghui Zhang Sayedeh Leila Noorbakhsh Yun Dong Yuan Hong Binghui Wang 340 2 0 15 Dec 2024
Membership Inference Attacks and Defenses in Federated Learning: A SurveyACM Computing Surveys (ACM CSUR), 2024 Li Bai Haibo Hu Qingqing Ye Haoyang Li Leixia Wang Jianliang Xu FedML 229 49 0 09 Dec 2024
BGTplanner: Maximizing Training Accuracy for Differentially Private Federated Recommenders via Strategic Privacy Budget Allocation Xianzhi Zhang Yipeng Zhou Di Wu Di Wu Pengshan Liao Mohsen Guizani Michael Sheng 286 0 0 04 Dec 2024
Privacy-Preserving Federated Learning via Homomorphic Adversarial Networks Wenhan Dong Chao Lin Xinlei He Xinyi Huang Shengmin Xu PICV 311 0 0 02 Dec 2024
Attribute Inference Attacks for Federated Regression TasksAAAI Conference on Artificial Intelligence (AAAI), 2024 Francesco Diana Othmane Marfoq Chuan Xu Giovanni Neglia F. Giroire Eoin Thomas AAML 1.1K 1 0 19 Nov 2024
How to Defend Against Large-scale Model Poisoning Attacks in Federated Learning: A Vertical Solution Jinbo Wang Ruijin Wang Fengli Zhang FedML AAML 211 0 0 16 Nov 2024
TEESlice: Protecting Sensitive Neural Network Models in Trusted Execution Environments When Attackers have Pre-Trained ModelsACM Transactions on Software Engineering and Methodology (TOSEM), 2024 Ding Li Ziqi Zhang Mengyu Yao Y. Cai Yao Guo Xiangqun Chen FedML 181 8 0 15 Nov 2024
On Active Privacy Auditing in Supervised Fine-tuning for White-Box Language Models Qian Sun Hanpeng Wu Xi Sheryl Zhang 222 1 0 11 Nov 2024
Can Graph Neural Networks Expose Training Data Properties? An Efficient Risk Assessment ApproachNeural Information Processing Systems (NeurIPS), 2024 Hanyang Yuan Jiarong Xu Renhong Huang Mingli Song Chunping Wang Yang Yang AAML 183 1 0 06 Nov 2024
NeurIPS 2023 Competition: Privacy Preserving Federated Learning Document VQA Marlon Tobaben Mohamed Ali Souibgui Rubèn Pérez Tito Khanh Nguyen Raouf Kerkouche ... Josep Lladós Ernest Valveny Antti Honkela Mario Fritz Dimosthenis Karatzas FedML 317 1 0 06 Nov 2024
Gradient-Guided Conditional Diffusion Models for Private Image Reconstruction: Analyzing Adversarial Impacts of Differential Privacy and Denoising Tao Huang Jiayang Meng Hong Chen Guolong Zheng Xu Yang Xun Yi Hua Wang DiffM 150 3 0 05 Nov 2024
Trustworthy Federated Learning: Privacy, Security, and BeyondKnowledge and Information Systems (KAIS), 2024 Chunlu Chen Ji Liu Haowen Tan Xingjian Li Kevin I-Kai Wang Peng Li Kouichi Sakurai Dejing Dou FedML 244 34 0 03 Nov 2024
Anomalous Client Detection in Federated Learning Dipanwita Thakur Antonella Guzzo Giancarlo Fortino FedML 88 1 0 03 Nov 2024
Trustworthiness of Stochastic Gradient Descent in Distributed LearningEuropean Control Conference (ECC), 2024 Hongyang Li Caesar Wu Mohammed Chadli Said Mammar Pascal Bouvry 293 3 0 28 Oct 2024
FuseFL: One-Shot Federated Learning through the Lens of Causality with Progressive Model FusionNeural Information Processing Systems (NeurIPS), 2024 Zhenheng Tang Yonggang Zhang Peijie Dong Yiu-ming Cheung Amelie Chi Zhou Bo Han Xiaowen Chu FedML MoMe AI4CE 254 14 0 27 Oct 2024
Data Obfuscation through Latent Space Projection (LSP) for Privacy-Preserving AI Governance: Case Studies in Medical Diagnosis and Finance Fraud Detection Mahesh Vaijainthymala Krishnamoorthy 45 0 0 22 Oct 2024
Acoustic Model Optimization over Multiple Data Sources: Merging and Valuation Victor Junqiu Wei Weicheng Wang Chen Zhang Conghui Tan Rongzhong Lian MoMe 257 1 0 21 Oct 2024
Investigating Effective Speaker Property Privacy Protection in Federated Learning for Speech Emotion RecognitionACM Multimedia Asia (MMAsia), 2024 Chao Tan Sheng Li Yang Cao Zhao Ren Tanja Schultz 125 1 0 17 Oct 2024
Uncovering Attacks and Defenses in Secure Aggregation for Federated Deep Learning Yiwei Zhang R. Behnia A. Yavuz Reza Ebrahimi E. Bertino FedML 165 6 0 13 Oct 2024
Edge AI Collaborative Learning: Bayesian Approaches to Uncertainty Estimation Gleb I. Radchenko Victoria Andrea Fill 164 0 0 11 Oct 2024
SoK: Towards Security and Safety of Edge AI Tatjana Wingarz Anne Lauscher Janick Edinger Dominik Kaaser Stefan Schulte Mathias Fischer 207 0 0 07 Oct 2024
Enhancing Security Using Random Binary Weights in Privacy-Preserving Federated LearningAsia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), 2024 Hiroto Sawada Shoko Imaizumi Hitoshi Kiya FedML AAML 120 0 0 30 Sep 2024
Subject Data Auditing via Source Inference Attack in Cross-Silo Federated LearningJournal of Information Security and Applications (JISA), 2024 Jiaxin Li Marco Arazzi Antonino Nocera Mauro Conti 141 3 0 28 Sep 2024
Privacy Attack in Federated Learning is Not Easy: An Experimental Study Hangyu Zhu Liyuan Huang Zhenping Xie FedML 197 1 0 28 Sep 2024
Investigating Privacy Attacks in the Gray-Box Setting to Enhance Collaborative Learning Schemes Federico Mazzone Ahmad Al Badawi Y. Polyakov Maarten Everts Florian Hahn Andreas Peter MIACV AAML 241 0 0 25 Sep 2024
Perfect Gradient Inversion in Federated Learning: A New Paradigm from the Hidden Subset Sum Problem Qiongxiu Li Lixia Luo Agnese Gini Changlong Ji Zhanhao Hu Xiao-Li Li Chengfang Fang Jie Shi Xiaolin Hu FedML 167 4 0 21 Sep 2024
Data Poisoning and Leakage Analysis in Federated Learning Wenqi Wei Tiansheng Huang Zachary Yahn Anoop Singhal Margaret Loper Ling Liu FedML SILM 168 2 0 19 Sep 2024
From Challenges and Pitfalls to Recommendations and Opportunities: Implementing Federated Learning in Healthcare Ming Li Pengcheng Xu Junjie Hu Zeyu Tang Guang Yang FedML 303 23 0 15 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 109 3 0 08 Sep 2024
Understanding Data Importance in Machine Learning Attacks: Does Valuable Data Pose Greater Harm?Network and Distributed System Security Symposium (NDSS), 2024 Rui Wen Michael Backes Yang Zhang TDI AAML 210 5 0 05 Sep 2024
Unveiling the Vulnerability of Private Fine-Tuning in Split-Based Frameworks for Large Language Models: A Bidirectionally Enhanced AttackConference on Computer and Communications Security (CCS), 2024 Guanzhong Chen Zhiqiang Shen Mingxin Yang Yajie Zhou Tao Fan Tianyu Du Zenglin Xu AAML 321 13 0 02 Sep 2024
Analyzing Inference Privacy Risks Through Gradients in Machine LearningConference on Computer and Communications Security (CCS), 2024 Zhuohang Li Andrew Lowy Jing Liu T. Koike-Akino K. Parsons Bradley Malin Ye Wang FedML 196 5 0 29 Aug 2024
LLM-PBE: Assessing Data Privacy in Large Language ModelsProceedings of the VLDB Endowment (PVLDB), 2024 Qinbin Li Junyuan Hong Chulin Xie Jeffrey Tan Rachel Xin ... Dan Hendrycks Zinan Lin Bo Li Bingsheng He Dawn Song ELM PILM 251 43 0 23 Aug 2024
A survey on secure decentralized optimization and learning Changxin Liu Nicola Bastianello Wei Huo Yang Shi Karl H. Johansson 201 9 0 16 Aug 2024
Voltran: Unlocking Trust and Confidentiality in Decentralized Federated Learning AggregationIEEE Transactions on Information Forensics and Security (IEEE TIFS), 2024 Hao Wang Yichen Cai Jun Wang Chuan Ma Chunpeng Ge Xiangmou Qu Lu Zhou 116 4 0 13 Aug 2024
Privacy-Preserved Taxi Demand Prediction System Utilizing Distributed Data Ren Ozeki Haruki Yonekura Hamada Rizk Hirozumi Yamaguchi 112 1 0 09 Aug 2024
Efficient Byzantine-Robust and Provably Privacy-Preserving Federated Learning Chenfei Nie Qiang Li Yuxin Yang Yuede Ji Binghui Wang 195 1 0 29 Jul 2024
Theoretical Analysis of Privacy Leakage in Trustworthy Federated Learning: A Perspective from Linear Algebra and Optimization Theory Xiaojin Zhang Wei Chen FedML 133 1 0 23 Jul 2024
Data Mixture Inference: What do BPE Tokenizers Reveal about their Training Data? J. Hayase Alisa Liu Yejin Choi Sewoong Oh Noah A. Smith 265 18 0 23 Jul 2024
SeqMIA: Sequential-Metric Based Membership Inference Attack Hao Li Zheng Li Siyuan Wu Chengrui Hu Yutong Ye Min Zhang Dengguo Feng Yang Zhang 159 24 0 21 Jul 2024
Feature Inference Attack on Shapley Values Xinjian Luo Yangfan Jiang X. Xiao AAML FAtt 250 32 0 16 Jul 2024
Partner in Crime: Boosting Targeted Poisoning Attacks against Federated Learning Shihua Sun Shridatt Sugrim Angelos Stavrou Haining Wang AAML 326 7 0 13 Jul 2024
Provable Privacy Advantages of Decentralized Federated Learning via Distributed Optimization Wenrui Yu Qiongxiu Li Milan Lopuhaä-Zwakenberg Mads Græsbøll Christensen Richard Heusdens FedML 153 8 0 12 Jul 2024
CURE: Privacy-Preserving Split Learning Done Right Halil Ibrahim Kanpak Aqsa Shabbir Esra Genç Alptekin Küpçü Sinem Sav 166 2 0 12 Jul 2024
Threats and Defenses in Federated Learning Life Cycle: A Comprehensive Survey and Challenges Yanli Li Zhongliang Guo Nan Yang Huaming Chen Dong Yuan Weiping Ding FedML 241 13 0 09 Jul 2024
Beyond the Federation: Topology-aware Federated Learning for Generalization to Unseen Clients Mengmeng Ma Tang Li Xi Peng 203 6 0 06 Jul 2024
A Unified Learn-to-Distort-Data Framework for Privacy-Utility Trade-off in Trustworthy Federated Learning Xiaojin Zhang Mingcong Xu Wei Chen FedML 164 0 0 05 Jul 2024