Exploiting Unintended Feature Leakage in Collaborative Learning

10 May 2018

Luca Melis

Congzheng Song

Emiliano De Cristofaro

Vitaly Shmatikov

FedML

ArXiv PDF HTML

Papers citing "Exploiting Unintended Feature Leakage in Collaborative Learning"

50 / 630 papers shown

Title
AugMixCloak: A Defense against Membership Inference Attacks via Image Transformation Heqing Ren Chao Feng Alberto Huertas Burkhard Stiller 21 0 0 11 May 2025
Towards Trustworthy Federated Learning with Untrusted Participants Youssef Allouah R. Guerraoui John Stephan FedML 43 0 0 03 May 2025
PDSL: Privacy-Preserved Decentralized Stochastic Learning with Heterogeneous Data Distribution Lina Wang Yunsheng Yuan Chunxiao Wang Feng Li FedML 43 0 0 31 Mar 2025
Defending Against Gradient Inversion Attacks for Biomedical Images via Learnable Data Perturbation Shiyi Jiang F. Firouzi Krishnendu Chakrabarty AAML MedIm 41 0 0 19 Mar 2025
Differential Privacy Personalized Federated Learning Based on Dynamically Sparsified Client Updates Chuanyin Wang Yifei Zhang Neng Gao Qiang Luo FedML 60 0 0 12 Mar 2025
All Your Knowledge Belongs to Us: Stealing Knowledge Graphs via Reasoning APIs Zhaohan Xi 56 0 0 12 Mar 2025
From Centralized to Decentralized Federated Learning: Theoretical Insights, Privacy Preservation, and Robustness Challenges Qiongxiu Li Wenrui Yu Yufei Xia Jun Pang FedML 50 1 0 10 Mar 2025
FedRand: Enhancing Privacy in Federated Learning with Randomized LoRA Subparameter Updates Sangwoo Park Seanie Lee Byungjoo Kim Sung Ju Hwang FedML 42 0 0 10 Mar 2025
Trustworthy Machine Learning via Memorization and the Granular Long-Tail: A Survey on Interactions, Tradeoffs, and Beyond Qiongxiu Li Xiaoyu Luo Yiyi Chen Johannes Bjerva 43 0 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 43 0 0 08 Mar 2025
LiteChain: A Lightweight Blockchain for Verifiable and Scalable Federated Learning in Massive Edge Networks Handi Chen Rui Zhou Yun-Hin Chan Zhihan Jiang Xianhao Chen Edith C. H. Ngai 50 0 0 06 Mar 2025
Theoretical Insights in Model Inversion Robustness and Conditional Entropy Maximization for Collaborative Inference Systems Song Xia Yi Yu Wenhan Yang Meiwen Ding Zhuo Chen Lingyu Duan Alex C. Kot Xudong Jiang 54 2 0 01 Mar 2025
Are Neuromorphic Architectures Inherently Privacy-preserving? An Exploratory Study Ayana Moshruba Ihsen Alouani Maryam Parsa AAML 46 3 0 24 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
Beyond the Crawl: Unmasking Browser Fingerprinting in Real User Interactions Meenatchi Sundaram Muthu Selva Annamalai Igor Bilogrevic Emiliano De Cristofaro 61 0 0 03 Feb 2025
FL-APU: A Software Architecture to Ease Practical Implementation of Cross-Silo Federated Learning F. Stricker J. A. Peregrina D. Bermbach C. Zirpins FedML 74 0 0 31 Jan 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
Fed-AugMix: Balancing Privacy and Utility via Data Augmentation HaoYang Li Wei Chen Xiaojin Zhang FedML 68 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 82 0 0 16 Dec 2024
Learning Robust and Privacy-Preserving Representations via Information Theory Binghui Zhang Sayedeh Leila Noorbakhsh Yun Dong Yuan Hong Binghui Wang 64 0 0 15 Dec 2024
Membership Inference Attacks and Defenses in Federated Learning: A Survey Li Bai Haibo Hu Qingqing Ye Haoyang Li Leixia Wang Jianliang Xu FedML 69 13 0 09 Dec 2024
BGTplanner: Maximizing Training Accuracy for Differentially Private Federated Recommenders via Strategic Privacy Budget Allocation Xianzhi Zhang Yipeng Zhou Miao Hu Di Wu Pengshan Liao Mohsen Guizani Michael Sheng 62 0 0 04 Dec 2024
Privacy-Preserving Federated Learning via Homomorphic Adversarial Networks Wenhan Dong Chao Lin Xinlei He Xinyi Huang Shengmin Xu PICV 79 0 0 02 Dec 2024
Attribute Inference Attacks for Federated Regression Tasks Francesco Diana Othmane Marfoq Chuan Xu Giovanni Neglia F. Giroire Eoin Thomas AAML 142 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 29 0 0 16 Nov 2024
TEESlice: Protecting Sensitive Neural Network Models in Trusted Execution Environments When Attackers have Pre-Trained Models Ding Li Ziqi Zhang Mengyu Yao Y. Cai Yao Guo Xiangqun Chen FedML 32 2 0 15 Nov 2024
On Active Privacy Auditing in Supervised Fine-tuning for White-Box Language Models Qian Sun Hanpeng Wu Xi Sheryl Zhang 36 0 0 11 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 28 0 0 06 Nov 2024
Can Graph Neural Networks Expose Training Data Properties? An Efficient Risk Assessment Approach Hanyang Yuan Jiarong Xu Renhong Huang Mingli Song Chunping Wang Yang Yang AAML 38 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 34 2 0 05 Nov 2024
Trustworthy Federated Learning: Privacy, Security, and Beyond Chunlu Chen Ji Liu Haowen Tan Xingjian Li Kevin I-Kai Wang Peng Li Kouichi Sakurai Dejing Dou FedML 52 3 0 03 Nov 2024
Anomalous Client Detection in Federated Learning Dipanwita Thakur Antonella Guzzo Giancarlo Fortino FedML 30 0 0 03 Nov 2024
Trustworthiness of Stochastic Gradient Descent in Distributed Learning Hongyang Li Caesar Wu Mohammed Chadli Said Mammar Pascal Bouvry 44 1 0 28 Oct 2024
FuseFL: One-Shot Federated Learning through the Lens of Causality with Progressive Model Fusion Zhenheng Tang Yonggang Zhang Peijie Dong Y. Cheung Amelie Chi Zhou Bo Han Xiaowen Chu FedML MoMe AI4CE 47 6 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 16 0 0 22 Oct 2024
Acoustic Model Optimization over Multiple Data Sources: Merging and Valuation Victor Junqiu Wei Weicheng Wang Di Jiang Conghui Tan Rongzhong Lian MoMe 30 0 0 21 Oct 2024
Investigating Effective Speaker Property Privacy Protection in Federated Learning for Speech Emotion Recognition Chao Tan Sheng Li Yang Cao Zhao Ren Tanja Schultz 30 0 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 11 2 0 13 Oct 2024
Edge AI Collaborative Learning: Bayesian Approaches to Uncertainty Estimation Gleb I. Radchenko Victoria Andrea Fill 26 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 27 0 0 07 Oct 2024
Enhancing Security Using Random Binary Weights in Privacy-Preserving Federated Learning Hiroto Sawada Shoko Imaizumi Hitoshi Kiya FedML AAML 23 0 0 30 Sep 2024
Subject Data Auditing via Source Inference Attack in Cross-Silo Federated Learning Jiaxin Li Marco Arazzi Antonino Nocera Mauro Conti 26 2 0 28 Sep 2024
Privacy Attack in Federated Learning is Not Easy: An Experimental Study Hangyu Zhu Liyuan Huang Zhenping Xie FedML 21 0 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 31 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 24 3 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 18 0 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 40 1 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 24 3 0 08 Sep 2024
Understanding Data Importance in Machine Learning Attacks: Does Valuable Data Pose Greater Harm? Rui Wen Michael Backes Yang Zhang TDI AAML 36 0 0 05 Sep 2024
Unveiling the Vulnerability of Private Fine-Tuning in Split-Based Frameworks for Large Language Models: A Bidirectionally Enhanced Attack Guanzhong Chen Zhenghan Qin Mingxin Yang Yajie Zhou Tao Fan Tianyu Du Zenglin Xu AAML 43 4 0 02 Sep 2024