Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning

24 February 2017

Papers citing "Deep Models Under the GAN: Information Leakage from Collaborative Deep Learning"

50 / 354 papers shown

Title
Free-rider Attacks on Model Aggregation in Federated Learning Yann Fraboni Richard Vidal Marco Lorenzi FedML 14 124 0 21 Jun 2020
Topology-aware Differential Privacy for Decentralized Image Classification Shangwei Guo Tianwei Zhang Guowen Xu Hanzhou Yu Tao Xiang Yang Liu 22 18 0 14 Jun 2020
ARIANN: Low-Interaction Privacy-Preserving Deep Learning via Function Secret Sharing T. Ryffel Pierre Tholoniat D. Pointcheval Francis R. Bach FedML 28 94 0 08 Jun 2020
Two-Phase Multi-Party Computation Enabled Privacy-Preserving Federated Learning Renuga Kanagavelu Zengxiang Li J. Samsudin Yechao Yang Feng Yang Rick Siow Mong Goh Mervyn Cheah Praewpiraya Wiwatphonthana K. Akkarajitsakul Shangguang Wang FedML 12 88 0 25 May 2020
An Overview of Privacy in Machine Learning Emiliano De Cristofaro SILM 30 83 0 18 May 2020
Federated Generative Adversarial Learning Chenyou Fan Ping Liu GAN FedML 34 40 0 07 May 2020
Exploiting Defenses against GAN-Based Feature Inference Attacks in Federated Learning Xinjian Luo Xiangqi Zhu FedML 73 25 0 27 Apr 2020
A Framework for Evaluating Gradient Leakage Attacks in Federated Learning Wenqi Wei Ling Liu Margaret Loper Ka-Ho Chow Mehmet Emre Gursoy Stacey Truex Yanzhao Wu FedML 23 146 0 22 Apr 2020
Local Differential Privacy based Federated Learning for Internet of Things Yang Zhao Jun Zhao Mengmeng Yang Teng Wang Ning Wang Lingjuan Lyu Dusit Niyato Kwok-Yan Lam 25 292 0 19 Apr 2020
An Overview of Federated Deep Learning Privacy Attacks and Defensive Strategies David Enthoven Zaid Al-Ars FedML 60 50 0 01 Apr 2020
Semi-Federated Learning Zhikun Chen Daofeng Li Mingde Zhao Sihai Zhang Jinkang Zhu FedML 10 18 0 28 Mar 2020
Systematic Evaluation of Privacy Risks of Machine Learning Models Liwei Song Prateek Mittal MIACV 196 359 0 24 Mar 2020
Dynamic Backdoor Attacks Against Machine Learning Models A. Salem Rui Wen Michael Backes Shiqing Ma Yang Zhang AAML 45 271 0 07 Mar 2020
Forgetting Outside the Box: Scrubbing Deep Networks of Information Accessible from Input-Output Observations Aditya Golatkar Alessandro Achille Stefano Soatto MU OOD 22 189 0 05 Mar 2020
Threats to Federated Learning: A Survey Lingjuan Lyu Han Yu Qiang Yang FedML 204 436 0 04 Mar 2020
User-Level Privacy-Preserving Federated Learning: Analysis and Performance Optimization Kang Wei Jun Li Ming Ding Chuan Ma Hang Su Bo-Wen Zhang H. Vincent Poor FedML 25 11 0 29 Feb 2020
Classifying the classifier: dissecting the weight space of neural networks Gabriel Eilertsen Daniel Jonsson Timo Ropinski Jonas Unger Anders Ynnerman 6 53 0 13 Feb 2020
Federated machine learning with Anonymous Random Hybridization (FeARH) on medical records Jianfei Cui He Zhu Hao Deng Ziwei Chen Dianbo Liu 23 33 0 25 Dec 2019
Assessing differentially private deep learning with Membership Inference Daniel Bernau Philip-William Grassal J. Robl Florian Kerschbaum MIACV FedML 26 23 0 24 Dec 2019
Asynchronous Federated Learning with Differential Privacy for Edge Intelligence Yanan Li Shusen Yang Xuebin Ren Cong Zhao FedML 19 33 0 17 Dec 2019
Federated Learning with Bayesian Differential Privacy Aleksei Triastcyn Boi Faltings FedML 19 174 0 22 Nov 2019
Revocable Federated Learning: A Benchmark of Federated Forest Yang Liu Zhuo Ma Ximeng Liu Zhuzhu Wang Siqi Ma Ken Ren FedML MU 27 10 0 08 Nov 2019
Communication-Efficient Local Decentralized SGD Methods Xiang Li Wenhao Yang Shusen Wang Zhihua Zhang 30 53 0 21 Oct 2019
PPGAN: Privacy-preserving Generative Adversarial Network Yi Liu Jialiang Peng James J. Q. Yu Yi Wu 32 70 0 04 Oct 2019
Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraints Felix Sattler K. Müller Wojciech Samek FedML 71 969 0 04 Oct 2019
Privacy-Preserving Tensor Factorization for Collaborative Health Data Analysis Jing Ma Qiuchen Zhang Jian Lou Joyce C. Ho Li Xiong Xiaoqian Jiang 30 44 0 26 Aug 2019
A Federated Learning Approach for Mobile Packet Classification Evita Bakopoulou Bálint Tillman A. Markopoulou 21 30 0 30 Jul 2019
On the Convergence of FedAvg on Non-IID Data Xiang Li Kaixuan Huang Wenhao Yang Shusen Wang Zhihua Zhang FedML 106 2,286 0 04 Jul 2019
Deep Leakage from Gradients Ligeng Zhu Zhijian Liu Song Han FedML 40 2,160 0 21 Jun 2019
Robust or Private? Adversarial Training Makes Models More Vulnerable to Privacy Attacks Felipe A. Mejia Paul Gamble Z. Hampel-Arias M. Lomnitz Nina Lopatina Lucas Tindall M. Barrios SILM 27 18 0 15 Jun 2019
AutoGAN-based Dimension Reduction for Privacy Preservation Hung Nguyen Di Zhuang Pei-Yuan Wu Jerome Chang 22 33 0 27 Feb 2019
Adversarial Neural Network Inversion via Auxiliary Knowledge Alignment Ziqi Yang E. Chang Zhenkai Liang MLAU 33 60 0 22 Feb 2019
XONN: XNOR-based Oblivious Deep Neural Network Inference M. Riazi Mohammad Samragh Hao Chen Kim Laine Kristin E. Lauter F. Koushanfar FedML GNN BDL 22 280 0 19 Feb 2019
On Lightweight Privacy-Preserving Collaborative Learning for IoT Objects Linshan Jiang Rui Tan Xin Lou Guosheng Lin 16 45 0 13 Feb 2019
Contamination Attacks and Mitigation in Multi-Party Machine Learning Jamie Hayes O. Ohrimenko AAML FedML 19 74 0 08 Jan 2019
Stochastic Distributed Optimization for Machine Learning from Decentralized Features Yaochen Hu Di Niu Jianming Yang Shengping Zhou 11 5 0 16 Dec 2018
Secure Federated Transfer Learning Yang Liu Yan Kang Chaoping Xing Tianjian Chen Qiang Yang FedML 6 119 0 08 Dec 2018
No Peek: A Survey of private distributed deep learning Praneeth Vepakomma Tristan Swedish Ramesh Raskar O. Gupta Abhimanyu Dubey SyDa FedML 30 100 0 08 Dec 2018
Three Tools for Practical Differential Privacy K. V. D. Veen Ruben Seggers Peter Bloem Giorgio Patrini 19 39 0 07 Dec 2018
Differentially Private Data Generative Models Qingrong Chen Chong Xiang Minhui Xue Bo-wen Li Nikita Borisov Dali Kaafar Haojin Zhu SyDa AAML 15 79 0 06 Dec 2018
Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference Attacks against Centralized and Federated Learning Milad Nasr Reza Shokri Amir Houmansadr FedML MIACV AAML 13 244 0 03 Dec 2018
Beyond Inferring Class Representatives: User-Level Privacy Leakage From Federated Learning Peng Kuang Mengkai Song Zhifei Zhang Yang Song Qian Wang Hairong Qi FedML 28 776 0 03 Dec 2018
Private Model Compression via Knowledge Distillation Ji Wang Weidong Bao Lichao Sun Xiaomin Zhu Bokai Cao Philip S. Yu FedML 6 116 0 13 Nov 2018
Deep Learning Towards Mobile Applications Ji Wang Bokai Cao Philip S. Yu Lichao Sun Weidong Bao Xiaomin Zhu HAI 32 98 0 10 Sep 2018
Mitigating Sybils in Federated Learning Poisoning Clement Fung Chris J. M. Yoon Ivan Beschastnikh AAML 15 497 0 14 Aug 2018
Performing Co-Membership Attacks Against Deep Generative Models Kin Sum Liu Chaowei Xiao Bo-wen Li Jie Gao AAML MIACV 21 58 0 24 May 2018
Towards Robust and Privacy-preserving Text Representations Yitong Li Timothy Baldwin Trevor Cohn 12 165 0 16 May 2018
Gradient-Leaks: Understanding and Controlling Deanonymization in Federated Learning Tribhuvanesh Orekondy Seong Joon Oh Yang Zhang Bernt Schiele Mario Fritz PICV FedML 359 37 0 15 May 2018
Exploiting Unintended Feature Leakage in Collaborative Learning Luca Melis Congzheng Song Emiliano De Cristofaro Vitaly Shmatikov FedML 81 1,455 0 10 May 2018
Deep Learning in Mobile and Wireless Networking: A Survey Chaoyun Zhang P. Patras Hamed Haddadi 45 1,306 0 12 Mar 2018