Exploiting Unintended Feature Leakage in Collaborative Learning

10 May 2018

Luca Melis

Congzheng Song

Emiliano De Cristofaro

Vitaly Shmatikov

FedML

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Papers citing "Exploiting Unintended Feature Leakage in Collaborative Learning"

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FACE-AUDITOR: Data Auditing in Facial Recognition Systems Min Chen Zhikun Zhang Tianhao Wang Michael Backes Yang Zhang CVBM 30 14 0 05 Apr 2023
Scalable and Privacy-Preserving Federated Principal Component Analysis D. Froelicher Hyunghoon Cho Manaswitha Edupalli João Sá Sousa Jean-Philippe Bossuat Apostolos Pyrgelis J. Troncoso-Pastoriza Bonnie Berger Jean-Pierre Hubaux FedML 24 15 0 31 Mar 2023
Robust and IP-Protecting Vertical Federated Learning against Unexpected Quitting of Parties Jingwei Sun Zhixu Du Anna Dai Saleh Baghersalimi Alireza Amirshahi David Atienza Yiran Chen FedML 21 7 0 28 Mar 2023
Edge-Based Video Analytics: A Survey Miao Hu Zhenxiao Luo A. Pasdar Young Choon Lee Yipeng Zhou Di Wu 47 14 0 25 Mar 2023
LOKI: Large-scale Data Reconstruction Attack against Federated Learning through Model Manipulation Joshua C. Zhao Atul Sharma A. Elkordy Yahya H. Ezzeldin Salman Avestimehr S. Bagchi AAML FedML 38 28 0 21 Mar 2023
Manipulating Transfer Learning for Property Inference Yulong Tian Fnu Suya Anshuman Suri Fengyuan Xu David Evans AAML 31 6 0 21 Mar 2023
Make Landscape Flatter in Differentially Private Federated Learning Yi Shi Yingqi Liu Kang Wei Li Shen Xueqian Wang Dacheng Tao FedML 25 55 0 20 Mar 2023
Efficient and Secure Federated Learning for Financial Applications Tao Liu Zhi Wang Hui He Wei Shi Liangliang Lin Wei Shi Ran An Chenhao Li FedML 16 20 0 15 Mar 2023
Private Read-Update-Write with Controllable Information Leakage for Storage-Efficient Federated Learning with Top $r$ Sparsification Sajani Vithana S. Ulukus FedML 30 5 0 07 Mar 2023
Client-specific Property Inference against Secure Aggregation in Federated Learning Raouf Kerkouche G. Ács Mario Fritz FedML 63 9 0 07 Mar 2023
Active Membership Inference Attack under Local Differential Privacy in Federated Learning Truc D. T. Nguyen Phung Lai K. Tran Nhathai Phan My T. Thai FedML 32 18 0 24 Feb 2023
Subspace based Federated Unlearning Guang-Ming Li Li Shen Yan Sun Yuejun Hu Han Hu Dacheng Tao MU FedML 28 20 0 24 Feb 2023
A Survey of Trustworthy Federated Learning with Perspectives on Security, Robustness, and Privacy Yifei Zhang Dun Zeng Jinglong Luo Zenglin Xu Irwin King FedML 84 47 0 21 Feb 2023
A Federated Approach for Hate Speech Detection Jay Gala Deep Gandhi Jash Mehta Zeerak Talat 21 4 0 18 Feb 2023
Multimodal Federated Learning via Contrastive Representation Ensemble Qiying Yu Yang Liu Yimu Wang Ke Xu Jingjing Liu 37 81 0 17 Feb 2023
On the Privacy-Robustness-Utility Trilemma in Distributed Learning Youssef Allouah R. Guerraoui Nirupam Gupta Rafael Pinot John Stephan FedML 26 21 0 09 Feb 2023
Exploratory Analysis of Federated Learning Methods with Differential Privacy on MIMIC-III Aron N. Horvath Matteo Berchier Farhad Nooralahzadeh Ahmed Allam Michael Krauthammer FedML 23 2 0 08 Feb 2023
Machine Learning for Synthetic Data Generation: A Review Ying-Cheng Lu Minjie Shen Huazheng Wang Xiao Wang Capucine Van Rechem Tianfan Fu Wenqi Wei SyDa 42 140 0 08 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
FedLAP-DP: Federated Learning by Sharing Differentially Private Loss Approximations Hui-Po Wang Dingfan Chen Raouf Kerkouche Mario Fritz FedML DD 26 4 0 02 Feb 2023
Privacy Risk for anisotropic Langevin dynamics using relative entropy bounds Anastasia Borovykh N. Kantas P. Parpas G. Pavliotis 19 1 0 01 Feb 2023
CATFL: Certificateless Authentication-based Trustworthy Federated Learning for 6G Semantic Communications Gaolei Li Yuanyuan Zhao Yi Li 21 13 0 01 Feb 2023
Dataset Distillation: A Comprehensive Review Ruonan Yu Songhua Liu Xinchao Wang DD 55 121 0 17 Jan 2023
Enforcing Privacy in Distributed Learning with Performance Guarantees Elsa Rizk Stefan Vlaski Ali H. Sayed FedML 30 9 0 16 Jan 2023
Reconstructing Individual Data Points in Federated Learning Hardened with Differential Privacy and Secure Aggregation Franziska Boenisch Adam Dziedzic R. Schuster Ali Shahin Shamsabadi Ilia Shumailov Nicolas Papernot FedML 19 20 0 09 Jan 2023
Model Segmentation for Storage Efficient Private Federated Learning with Top $r$ Sparsification Sajani Vithana S. Ulukus FedML 26 5 0 22 Dec 2022
Over-the-Air Federated Learning with Enhanced Privacy Xiaochan Xue Moh. Khalid Hasan Shucheng Yu Laxima Niure Kandel Min Song 34 2 0 22 Dec 2022
Differentially Private Decentralized Optimization with Relay Communication Luqing Wang Luyao Guo Shaofu Yang Xinli Shi 28 0 0 21 Dec 2022
Rate-Privacy-Storage Tradeoff in Federated Learning with Top $r$ Sparsification Sajani Vithana S. Ulukus FedML 26 5 0 19 Dec 2022
Membership Inference Attacks Against Latent Factor Model Dazhi Hu AAML 30 1 0 15 Dec 2022
Holistic risk assessment of inference attacks in machine learning Yang Yang SILM AAML MIACV 25 2 0 15 Dec 2022
Deep leakage from gradients Yaqiong Mu FedML 9 0 0 15 Dec 2022
White-box Inference Attacks against Centralized Machine Learning and Federated Learning Jing Ge FedML 14 0 0 15 Dec 2022
Dissecting Distribution Inference Anshuman Suri Yifu Lu Yanjin Chen David Evans 30 14 0 15 Dec 2022
Skellam Mixture Mechanism: a Novel Approach to Federated Learning with Differential Privacy Ergute Bao Yizheng Zhu X. Xiao Yifan Yang Beng Chin Ooi B. Tan Khin Mi Mi Aung FedML 31 19 0 08 Dec 2022
Vicious Classifiers: Data Reconstruction Attack at Inference Time Mohammad Malekzadeh Deniz Gunduz AAML MIACV 16 0 0 08 Dec 2022
HashVFL: Defending Against Data Reconstruction Attacks in Vertical Federated Learning Pengyu Qiu Xuhong Zhang S. Ji Chong Fu Xing Yang Ting Wang FedML AAML 30 12 0 01 Dec 2022
Decentralized Matrix Factorization with Heterogeneous Differential Privacy Wentao Hu Hui Fang 19 0 0 01 Dec 2022
Adap DP-FL: Differentially Private Federated Learning with Adaptive Noise Jie Fu Zhili Chen Xiao Han FedML 25 28 0 29 Nov 2022
Federated Learning Attacks and Defenses: A Survey Yao Chen Yijie Gui Hong Lin Wensheng Gan Yongdong Wu FedML 44 29 0 27 Nov 2022
Data Origin Inference in Machine Learning Mingxue Xu Xiang-Yang Li 27 3 0 24 Nov 2022
DPD-fVAE: Synthetic Data Generation Using Federated Variational Autoencoders With Differentially-Private Decoder Bjarne Pfitzner B. Arnrich FedML 33 19 0 21 Nov 2022
SA-DPSGD: Differentially Private Stochastic Gradient Descent based on Simulated Annealing Jie Fu Zhili Chen Xinpeng Ling 27 0 0 14 Nov 2022
Inferring Class Label Distribution of Training Data from Classifiers: An Accuracy-Augmented Meta-Classifier Attack Raksha Ramakrishna Gyorgy Dán 25 2 0 08 Nov 2022
On the Vulnerability of Data Points under Multiple Membership Inference Attacks and Target Models Mauro Conti Jiaxin Li S. Picek MIALM 32 2 0 28 Oct 2022
Local Model Reconstruction Attacks in Federated Learning and their Uses Ilias Driouich Chuan Xu Giovanni Neglia F. Giroire Eoin Thomas AAML FedML 36 2 0 28 Oct 2022
Mixed Precision Quantization to Tackle Gradient Leakage Attacks in Federated Learning Pretom Roy Ovi Emon Dey Nirmalya Roy A. Gangopadhyay FedML 26 4 0 22 Oct 2022
New data poison attacks on machine learning classifiers for mobile exfiltration M. A. Ramírez Sangyoung Yoon Ernesto Damiani H. A. Hamadi C. Ardagna Nicola Bena Young-Ji Byon Tae-Yeon Kim C. Cho C. Yeun AAML 33 4 0 20 Oct 2022
How Does a Deep Learning Model Architecture Impact Its Privacy? A Comprehensive Study of Privacy Attacks on CNNs and Transformers Guangsheng Zhang B. Liu Huan Tian Tianqing Zhu Ming Ding Wanlei Zhou PILM MIACV 20 5 0 20 Oct 2022
DPIS: An Enhanced Mechanism for Differentially Private SGD with Importance Sampling Jianxin Wei Ergute Bao X. Xiao Yifan Yang 46 20 0 18 Oct 2022