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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Title
Distributed Learning in Wireless Networks: Recent Progress and Future Challenges Mingzhe Chen Deniz Gündüz Kaibin Huang Walid Saad M. Bennis Aneta Vulgarakis Feljan H. Vincent Poor 45 402 0 05 Apr 2021
Knowledge Distillation For Wireless Edge Learning Ahmed P. Mohamed Abu Shafin Mohammad Mahdee Jameel Aly El Gamal FedML 29 2 0 03 Apr 2021
Game Theory Based Privacy Preserving Approach for Collaborative Deep Learning in IoT Deepti Gupta Smriti Bhatt Paras Bhatt Maanak Gupta A. Tosun 20 15 0 28 Mar 2021
Graph Unlearning Min Chen Zhikun Zhang Tianhao Wang Michael Backes Mathias Humbert Yang Zhang MU 19 139 0 27 Mar 2021
Prior-Independent Auctions for the Demand Side of Federated Learning Andreas A. Haupt Vaikkunth Mugunthan FedML 14 0 0 26 Mar 2021
SoK: Privacy-Preserving Collaborative Tree-based Model Learning Sylvain Chatel Apostolos Pyrgelis J. Troncoso-Pastoriza Jean-Pierre Hubaux 17 14 0 16 Mar 2021
Membership Inference Attacks on Machine Learning: A Survey Hongsheng Hu Z. Salcic Lichao Sun Gillian Dobbie Philip S. Yu Xuyun Zhang MIACV 35 412 0 14 Mar 2021
On the (In)Feasibility of Attribute Inference Attacks on Machine Learning Models Benjamin Zi Hao Zhao Aviral Agrawal Catisha Coburn Hassan Jameel Asghar Raghav Bhaskar M. Kâafar Darren Webb Peter Dickinson MIACV 31 38 0 12 Mar 2021
TAG: Gradient Attack on Transformer-based Language Models Jieren Deng Yijue Wang Ji Li Chao Shang Hang Liu Sanguthevar Rajasekaran Caiwen Ding FedML PILM 16 73 0 11 Mar 2021
A Study of Face Obfuscation in ImageNet Kaiyu Yang Jacqueline Yau Li Fei-Fei Jia Deng Olga Russakovsky PICV CVBM 34 144 0 10 Mar 2021
Privacy Amplification for Federated Learning via User Sampling and Wireless Aggregation Mohamed Seif Wei-Ting Chang Ravi Tandon FedML 26 45 0 02 Mar 2021
PFA: Privacy-preserving Federated Adaptation for Effective Model Personalization Bingyan Liu Yao Guo Xiangqun Chen FedML 18 81 0 02 Mar 2021
FjORD: Fair and Accurate Federated Learning under heterogeneous targets with Ordered Dropout Samuel Horváth Stefanos Laskaridis Mario Almeida Ilias Leondiadis Stylianos I. Venieris Nicholas D. Lane 189 268 0 26 Feb 2021
Learner-Private Convex Optimization Jiaming Xu Kuang Xu Dana Yang FedML 19 2 0 23 Feb 2021
Obfuscation of Images via Differential Privacy: From Facial Images to General Images W. Croft Jörg-Rüdiger Sack W. Shi PICV 28 22 0 19 Feb 2021
Machine Learning Based Cyber Attacks Targeting on Controlled Information: A Survey Yuantian Miao Chao Chen Lei Pan Qing-Long Han Jun Zhang Yang Xiang AAML 49 68 0 16 Feb 2021
On the Impact of Device and Behavioral Heterogeneity in Federated Learning A. Abdelmoniem Chen-Yu Ho Pantelis Papageorgiou Muhammad Bilal Marco Canini FedML 11 18 0 15 Feb 2021
The Distributed Discrete Gaussian Mechanism for Federated Learning with Secure Aggregation Peter Kairouz Ziyu Liu Thomas Steinke FedML 44 232 0 12 Feb 2021
Meta Federated Learning Omid Aramoon Pin-Yu Chen Gang Qu Yuan Tian AAML FedML 15 13 0 10 Feb 2021
Node-Level Membership Inference Attacks Against Graph Neural Networks Xinlei He Rui Wen Yixin Wu Michael Backes Yun Shen Yang Zhang 21 93 0 10 Feb 2021
Quantifying and Mitigating Privacy Risks of Contrastive Learning Xinlei He Yang Zhang 21 51 0 08 Feb 2021
ML-Doctor: Holistic Risk Assessment of Inference Attacks Against Machine Learning Models Yugeng Liu Rui Wen Xinlei He A. Salem Zhikun Zhang Michael Backes Emiliano De Cristofaro Mario Fritz Yang Zhang AAML 17 125 0 04 Feb 2021
Provably Secure Federated Learning against Malicious Clients Xiaoyu Cao Jinyuan Jia Neil Zhenqiang Gong FedML 21 134 0 03 Feb 2021
Applications of Federated Learning in Smart Cities: Recent Advances, Taxonomy, and Open Challenges Zhaohua Zheng Yize Zhou Yilong Sun Zhang Wang Boyi Liu Keqiu Li 28 102 0 02 Feb 2021
Gain without Pain: Offsetting DP-injected Nosies Stealthily in Cross-device Federated Learning Wenzhuo Yang Yipeng Zhou Maio Hu Di Wu J. Zheng Hui Wang Song Guo FedML 16 11 0 31 Jan 2021
Covert Model Poisoning Against Federated Learning: Algorithm Design and Optimization Kang Wei Jun Li Ming Ding Chuan Ma Yo-Seb Jeon H. Vincent Poor FedML 37 8 0 28 Jan 2021
Property Inference From Poisoning Melissa Chase Esha Ghosh Saeed Mahloujifar MIACV 21 77 0 26 Jan 2021
Collaborative Federated Learning For Healthcare: Multi-Modal COVID-19 Diagnosis at the Edge A. Qayyum Kashif Ahmad Muhammad Ahtazaz Ahsan Ala I. Al-Fuqaha Junaid Qadir FedML 36 187 0 19 Jan 2021
Membership Inference Attack on Graph Neural Networks Iyiola E. Olatunji Wolfgang Nejdl Megha Khosla AAML 40 97 0 17 Jan 2021
Personalized Federated Deep Learning for Pain Estimation From Face Images Ognjen Rudovic Nicolas Tobis Sebastian Kaltwang Björn Schuller Daniel Rueckert Jeffrey F. Cohn Rosalind W. Picard CVBM FedML 17 24 0 12 Jan 2021
Adversary Instantiation: Lower Bounds for Differentially Private Machine Learning Milad Nasr Shuang Song Abhradeep Thakurta Nicolas Papernot Nicholas Carlini MIACV FedML 82 216 0 11 Jan 2021
Adversarially Robust and Explainable Model Compression with On-Device Personalization for Text Classification Yao Qiang Supriya Tumkur Suresh Kumar Marco Brocanelli D. Zhu AAML 28 0 0 10 Jan 2021
FLAME: Taming Backdoors in Federated Learning (Extended Version 1) T. D. Nguyen Phillip Rieger Huili Chen Hossein Yalame Helen Mollering ... Azalia Mirhoseini S. Zeitouni F. Koushanfar A. Sadeghi T. Schneider AAML 27 26 0 06 Jan 2021
PFL-MoE: Personalized Federated Learning Based on Mixture of Experts Binbin Guo Yuan Mei Danyang Xiao Weigang Wu Ye Yin Hongli Chang MoE 47 22 0 31 Dec 2020
Federated Unlearning Gaoyang Liu Xiaoqiang Ma Yang Yang Chen Wang Jiangchuan Liu MU 43 53 0 27 Dec 2020
Towards Scalable and Privacy-Preserving Deep Neural Network via Algorithmic-Cryptographic Co-design Jun Zhou Longfei Zheng Chaochao Chen Yan Wang Xiaolin Zheng Bingzhe Wu Cen Chen Li Wang Jianwei Yin FedML 38 3 0 17 Dec 2020
Multi-modal AsynDGAN: Learn From Distributed Medical Image Data without Sharing Private Information Qi Chang Zhennan Yan L. Baskaran Hui Qu Yikai Zhang Tong Zhang Shaoting Zhang Dimitris N. Metaxas MedIm 21 12 0 15 Dec 2020
Privacy-preserving Decentralized Aggregation for Federated Learning Beomyeol Jeon S. Ferdous Muntasir Raihan Rahman A. Walid FedML 28 52 0 13 Dec 2020
Achieving Security and Privacy in Federated Learning Systems: Survey, Research Challenges and Future Directions Alberto Blanco-Justicia J. Domingo-Ferrer Sergio Martínez David Sánchez Adrian Flanagan K. E. Tan FedML 26 110 0 12 Dec 2020
Communication-Computation Efficient Secure Aggregation for Federated Learning Beongjun Choi Jy-yong Sohn Dong-Jun Han Jaekyun Moon FedML 12 89 0 10 Dec 2020
Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective Jingwei Sun Ang Li Binghui Wang Huanrui Yang Hai Li Yiran Chen FedML 24 163 0 08 Dec 2020
Dynamic Clustering in Federated Learning Yeongwoo Kim Ezeddin Al Hakim Johan Haraldson Henrik Eriksson J. M. B. D. Silva Carlo Fischione 8 56 0 07 Dec 2020
Privacy and Robustness in Federated Learning: Attacks and Defenses Lingjuan Lyu Han Yu Xingjun Ma Chen Chen Lichao Sun Jun Zhao Qiang Yang Philip S. Yu FedML 183 355 0 07 Dec 2020
SoK: Training Machine Learning Models over Multiple Sources with Privacy Preservation Lushan Song Guopeng Lin Jiaxuan Wang Haoqi Wu Wenqiang Ruan Weili Han 34 9 0 06 Dec 2020
SSGD: A safe and efficient method of gradient descent Jinhuan Duan Xianxian Li Shiqi Gao Jinyan Wang Ziliang Zhong 12 4 0 03 Dec 2020
Privacy-preserving Collaborative Learning with Automatic Transformation Search Wei Gao Shangwei Guo Tianwei Zhang Han Qiu Yonggang Wen Yang Liu 47 46 0 25 Nov 2020
When Machine Learning Meets Privacy: A Survey and Outlook B. Liu Ming Ding Sina shaham W. Rahayu F. Farokhi Zihuai Lin 20 282 0 24 Nov 2020
Practical Privacy Attacks on Vertical Federated Learning Haiqin Weng Juntao Zhang Xingjun Ma Feng Xue Tao Wei S. Ji Zhiyuan Zong FedML 30 5 0 18 Nov 2020
Private Wireless Federated Learning with Anonymous Over-the-Air Computation Burak Hasircioglu Deniz Gunduz FedML 8 32 0 17 Nov 2020
A Theoretical Perspective on Differentially Private Federated Multi-task Learning Huiwen Wu Cen Chen Li Wang FedML 16 12 0 14 Nov 2020