Papers citing 'Exploiting Unintended Feature Leakage in Collaborative Learning'

Title
On the Impact of Device and Behavioral Heterogeneity in Federated Learning A. Abdelmoniem Chen-Yu Ho Pantelis Papageorgiou Muhammad Bilal Marco Canini FedML 144 18 0 15 Feb 2021
The Distributed Discrete Gaussian Mechanism for Federated Learning with Secure AggregationInternational Conference on Machine Learning (ICML), 2021 Peter Kairouz Ziyu Liu Thomas Steinke FedML 359 276 0 12 Feb 2021
Meta Federated Learning Omid Aramoon Pin-Yu Chen Gang Qu Yuan Tian AAML FedML 118 15 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 204 112 0 10 Feb 2021
Quantifying and Mitigating Privacy Risks of Contrastive LearningConference on Computer and Communications Security (CCS), 2021 Xinlei He Yang Zhang 239 58 0 08 Feb 2021
ML-Doctor: Holistic Risk Assessment of Inference Attacks Against Machine Learning ModelsUSENIX Security Symposium (USENIX Security), 2021 Yugeng Liu Rui Wen Xinlei He A. Salem Zhikun Zhang Michael Backes Emiliano De Cristofaro Mario Fritz Yang Zhang AAML 180 152 0 04 Feb 2021
Provably Secure Federated Learning against Malicious ClientsAAAI Conference on Artificial Intelligence (AAAI), 2021 Xiaoyu Cao Jinyuan Jia Neil Zhenqiang Gong FedML 239 151 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 164 128 0 02 Feb 2021
Gain without Pain: Offsetting DP-injected Nosies Stealthily in Cross-device Federated LearningIEEE Internet of Things Journal (IEEE IoT Journal), 2021 Wenzhuo Yang Yipeng Zhou Maio Hu Di Wu J. Zheng Hui Wang Song Guo FedML 125 14 0 31 Jan 2021
Covert Model Poisoning Against Federated Learning: Algorithm Design and OptimizationIEEE Transactions on Dependable and Secure Computing (IEEE TDSC), 2021 Kang Wei Jun Li Ming Ding Chuan Ma Yo-Seb Jeon H. Vincent Poor FedML 125 11 0 28 Jan 2021
Property Inference From PoisoningIEEE Symposium on Security and Privacy (IEEE S&P), 2021 Melissa Chase Esha Ghosh Saeed Mahloujifar MIACV 156 92 0 26 Jan 2021
Collaborative Federated Learning For Healthcare: Multi-Modal COVID-19 Diagnosis at the EdgeIEEE Open Journal of the Computer Society (JOCS), 2021 A. Qayyum Kashif Ahmad Muhammad Ahtazaz Ahsan Ala I. Al-Fuqaha Junaid Qadir FedML 225 236 0 19 Jan 2021
Membership Inference Attack on Graph Neural NetworksInternational Conference on Trust, Privacy and Security in Intelligent Systems and Applications (ICPSISA), 2021 Iyiola E. Olatunji Wolfgang Nejdl Megha Khosla AAML 285 126 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 139 27 0 12 Jan 2021
Adversary Instantiation: Lower Bounds for Differentially Private Machine LearningIEEE Symposium on Security and Privacy (IEEE S&P), 2021 Milad Nasr Shuang Song Abhradeep Thakurta Nicolas Papernot Nicholas Carlini MIACV FedML 319 261 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 103 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 271 23 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 246 28 0 31 Dec 2020
Federated Unlearning Gaoyang Liu Xiaoqiang Ma Yang Yang Chen Wang Jiangchuan Liu MU 288 69 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 139 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 172 13 0 15 Dec 2020
Privacy-preserving Decentralized Aggregation for Federated LearningConference on Computer Communications Workshops (INFOCOM Workshops), 2020 Beomyeol Jeon S. Ferdous Muntasir Raihan Rahman A. Walid FedML 344 69 0 13 Dec 2020
Achieving Security and Privacy in Federated Learning Systems: Survey, Research Challenges and Future DirectionsEngineering applications of artificial intelligence (EAAI), 2020 Alberto Blanco-Justicia J. Domingo-Ferrer Sergio Martínez David Sánchez Adrian Flanagan K. E. Tan FedML 143 131 0 12 Dec 2020
Communication-Computation Efficient Secure Aggregation for Federated Learning Beongjun Choi Jy-yong Sohn Dong-Jun Han Jaekyun Moon FedML 294 110 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 252 190 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 186 81 0 07 Dec 2020
Privacy and Robustness in Federated Learning: Attacks and Defenses Lingjuan Lyu Han Yu Jiabo He Chen Chen Lichao Sun Jun Zhao Qiang Yang Philip S. Yu FedML 507 460 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 331 9 0 06 Dec 2020
SSGD: A safe and efficient method of gradient descent Jinhuan Duan Xianxian Li Shiqi Gao Jinyan Wang Ziliang Zhong 111 4 0 03 Dec 2020
Privacy-preserving Collaborative Learning with Automatic Transformation SearchComputer Vision and Pattern Recognition (CVPR), 2020 Wei Gao Shangwei Guo Tianwei Zhang Han Qiu Yonggang Wen Yang Liu 251 58 0 25 Nov 2020
When Machine Learning Meets Privacy: A Survey and OutlookACM Computing Surveys (ACM CSUR), 2020 B. Liu Ming Ding Sina shaham W. Rahayu F. Farokhi Zihuai Lin 252 318 0 24 Nov 2020
Practical Privacy Attacks on Vertical Federated Learning Haiqin Weng Juntao Zhang Jiabo He Feng Xue Tao Wei S. Ji Zhiyuan Zong FedML 134 8 0 18 Nov 2020
Private Wireless Federated Learning with Anonymous Over-the-Air ComputationIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2020 Burak Hasircioglu Deniz Gunduz FedML 165 37 0 17 Nov 2020
A Theoretical Perspective on Differentially Private Federated Multi-task Learning Huiwen Wu Cen Chen Li Wang FedML 110 15 0 14 Nov 2020
An Exploratory Analysis on Users' Contributions in Federated LearningInternational Conference on Trust, Privacy and Security in Intelligent Systems and Applications (ICPSISA), 2020 Jiyue Huang Rania Talbi Zilong Zhao S. Bouchenak L. Chen Stefanie Roos FedML 220 37 0 13 Nov 2020
Privacy Preservation in Federated Learning: An insightful survey from the GDPR Perspective N. Truong Kai Sun Siyao Wang Florian Guitton Wenhan Luo FedML 289 10 0 10 Nov 2020
FederBoost: Private Federated Learning for GBDT Zhihua Tian Rui Zhang Xiaoyang Hou Jian Liu K. Ren Jian Liu Kui Ren FedML AI4CE 355 77 0 05 Nov 2020
BaFFLe: Backdoor detection via Feedback-based Federated Learning Sébastien Andreina G. Marson Helen Möllering Ghassan O. Karame FedML 229 162 0 04 Nov 2020
Revolutionizing Medical Data Sharing Using Advanced Privacy Enhancing Technologies: Technical, Legal and Ethical SynthesisJournal of Medical Internet Research (JMIR), 2020 J. Scheibner J. Raisaro J. Troncoso-Pastoriza M. Ienca J. Fellay E. Vayena Jean-Pierre Hubaux 86 93 0 27 Oct 2020
FaceLeaks: Inference Attacks against Transfer Learning Models via Black-box Queries Seng Pei Liew Tsubasa Takahashi MIACV FedML 157 10 0 27 Oct 2020
Robust and Verifiable Information Embedding Attacks to Deep Neural Networks via Error-Correcting CodesACM Asia Conference on Computer and Communications Security (AsiaCCS), 2020 Jinyuan Jia Binghui Wang Neil Zhenqiang Gong AAML 142 5 0 26 Oct 2020
Exploring the Security Boundary of Data Reconstruction via Neuron Exclusivity AnalysisUSENIX Security Symposium (USENIX Security), 2020 Xudong Pan Mi Zhang Yifan Yan Jiaming Zhu Zhemin Yang AAML 183 24 0 26 Oct 2020
DPD-InfoGAN: Differentially Private Distributed InfoGAN Vaikkunth Mugunthan V. Gokul Lalana Kagal Shlomo Dubnov 201 11 0 22 Oct 2020
Feature Inference Attack on Model Predictions in Vertical Federated LearningIEEE International Conference on Data Engineering (ICDE), 2020 Xinjian Luo Yuncheng Wu Xiaokui Xiao Beng Chin Ooi FedML AAML 207 267 0 20 Oct 2020
Image Obfuscation for Privacy-Preserving Machine Learning Mathilde Raynal R. Achanta Mathias Humbert 181 14 0 20 Oct 2020
From Distributed Machine Learning To Federated Learning: In The View Of Data Privacy And SecurityConcurrency and Computation (CCPE), 2020 Sheng Shen Tianqing Zhu Di Wu Wei Wang Wanlei Zhou FedML OOD 154 92 0 19 Oct 2020
Layer-wise Characterization of Latent Information Leakage in Federated Learning Fan Mo Anastasia Borovykh Mohammad Malekzadeh Hamed Haddadi Soteris Demetriou FedML 135 34 0 17 Oct 2020
Federated Learning in Adversarial Settings Raouf Kerkouche G. Ács C. Castelluccia FedML 111 16 0 15 Oct 2020
Knowledge-Enriched Distributional Model Inversion Attacks Si-An Chen Mostafa Kahla R. Jia Guo-Jun Qi 200 116 0 08 Oct 2020
HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous ClientsInternational Conference on Learning Representations (ICLR), 2020 Enmao Diao Jie Ding Vahid Tarokh FedML 446 659 0 03 Oct 2020

On the Impact of Device and Behavioral Heterogeneity in Federated
Learning

144

18

0

15 Feb 2021

The Distributed Discrete Gaussian Mechanism for Federated Learning with Secure AggregationInternational Conference on Machine Learning (ICML), 2021

359

276

0

12 Feb 2021

Meta Federated Learning

118

15

0

10 Feb 2021

Node-Level Membership Inference Attacks Against Graph Neural Networks

Michael Backes

204

112

0

10 Feb 2021

Quantifying and Mitigating Privacy Risks of Contrastive LearningConference on Computer and Communications Security (CCS), 2021

Xinlei He

Yang Zhang

239

58

0

08 Feb 2021

ML-Doctor: Holistic Risk Assessment of Inference Attacks Against Machine Learning ModelsUSENIX Security Symposium (USENIX Security), 2021

Michael Backes

Emiliano De Cristofaro

Mario Fritz

Yang Zhang

AAML

180

152

0

04 Feb 2021

Provably Secure Federated Learning against Malicious ClientsAAAI Conference on Artificial Intelligence (AAAI), 2021

239

151

0

03 Feb 2021

Applications of Federated Learning in Smart Cities: Recent Advances, Taxonomy, and Open Challenges

164

128

0

02 Feb 2021

Gain without Pain: Offsetting DP-injected Nosies Stealthily in Cross-device Federated LearningIEEE Internet of Things Journal (IEEE IoT Journal), 2021

125

14

0

31 Jan 2021

Covert Model Poisoning Against Federated Learning: Algorithm Design and OptimizationIEEE Transactions on Dependable and Secure Computing (IEEE TDSC), 2021

Ming Ding

125

11

0

28 Jan 2021

Property Inference From PoisoningIEEE Symposium on Security and Privacy (IEEE S&P), 2021

156

92

0

26 Jan 2021

Collaborative Federated Learning For Healthcare: Multi-Modal COVID-19 Diagnosis at the EdgeIEEE Open Journal of the Computer Society (JOCS), 2021

A. Qayyum

Kashif Ahmad

Muhammad Ahtazaz Ahsan

Ala I. Al-Fuqaha

Junaid Qadir

FedML

225

236

0

19 Jan 2021

Membership Inference Attack on Graph Neural NetworksInternational Conference on Trust, Privacy and Security in Intelligent Systems and Applications (ICPSISA), 2021

285

126

0

17 Jan 2021

Personalized Federated Deep Learning for Pain Estimation From Face Images

Björn Schuller

139

27

0

12 Jan 2021

Adversary Instantiation: Lower Bounds for Differentially Private Machine LearningIEEE Symposium on Security and Privacy (IEEE S&P), 2021

319

261

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

103

0

10 Jan 2021

FLAME: Taming Backdoors in Federated Learning (Extended Version 1)

Phillip Rieger

Hossein Yalame

...

271

23

0

06 Jan 2021

PFL-MoE: Personalized Federated Learning Based on Mixture of Experts

246

28

0

31 Dec 2020

288

69

0

27 Dec 2020

Towards Scalable and Privacy-Preserving Deep Neural Network via Algorithmic-Cryptographic Co-design

139

3

0

17 Dec 2020

Multi-modal AsynDGAN: Learn From Distributed Medical Image Data without Sharing Private Information

Yikai Zhang

Tong Zhang

Shaoting Zhang

Dimitris N. Metaxas

MedIm

172

13

0

15 Dec 2020

Privacy-preserving Decentralized Aggregation for Federated LearningConference on Computer Communications Workshops (INFOCOM Workshops), 2020

Beomyeol Jeon

S. Ferdous

Muntasir Raihan Rahman

A. Walid

FedML

344

69

0

13 Dec 2020

Achieving Security and Privacy in Federated Learning Systems: Survey, Research Challenges and Future DirectionsEngineering applications of artificial intelligence (EAAI), 2020

Alberto Blanco-Justicia

143

131

0

12 Dec 2020

Communication-Computation Efficient Secure Aggregation for Federated Learning

294

110

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

252

190

0

08 Dec 2020

Dynamic Clustering in Federated Learning

186

81

0

07 Dec 2020

Privacy and Robustness in Federated Learning: Attacks and Defenses

Lichao Sun

Jun Zhao

Qiang Yang

Philip S. Yu

FedML

507

460

0

07 Dec 2020

SoK: Training Machine Learning Models over Multiple Sources with Privacy Preservation

Haoqi Wu

331

9

0

06 Dec 2020

SSGD: A safe and efficient method of gradient descent

111

4

0

03 Dec 2020

Privacy-preserving Collaborative Learning with Automatic Transformation SearchComputer Vision and Pattern Recognition (CVPR), 2020

Yang Liu

251

58

0

25 Nov 2020

When Machine Learning Meets Privacy: A Survey and OutlookACM Computing Surveys (ACM CSUR), 2020

Ming Ding

252

318

0

24 Nov 2020

Practical Privacy Attacks on Vertical Federated Learning

Haiqin Weng

Tao Wei

134

8

0

18 Nov 2020

Private Wireless Federated Learning with Anonymous Over-the-Air ComputationIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2020

Burak Hasircioglu

Deniz Gunduz

FedML

165

37

0

17 Nov 2020

A Theoretical Perspective on Differentially Private Federated Multi-task Learning

110

15

0

14 Nov 2020

An Exploratory Analysis on Users' Contributions in Federated LearningInternational Conference on Trust, Privacy and Security in Intelligent Systems and Applications (ICPSISA), 2020

220

37

0

13 Nov 2020