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
Gradient Obfuscation Gives a False Sense of Security in Federated Learning Kai Yue Richeng Jin Chau-Wai Wong D. Baron H. Dai FedML 36 46 0 08 Jun 2022
Rate Distortion Tradeoff in Private Read Update Write in Federated Submodel Learning Sajani Vithana S. Ulukus FedML 36 8 0 07 Jun 2022
Towards Practical Differential Privacy in Data Analysis: Understanding the Effect of Epsilon on Utility in Private ERM Yuzhe Li Yong Liu Bo-wen Li Weiping Wang Nannan Liu 13 9 0 06 Jun 2022
On the Privacy Properties of GAN-generated Samples Zinan Lin Vyas Sekar Giulia Fanti PICV 24 26 0 03 Jun 2022
Edge Learning for B5G Networks with Distributed Signal Processing: Semantic Communication, Edge Computing, and Wireless Sensing Wei Xu Zhaohui Yang Derrick Wing Kwan Ng Marco Levorato Yonina C. Eldar Mérouane Debbah 36 399 0 01 Jun 2022
Privacy for Free: How does Dataset Condensation Help Privacy? Tian Dong Bo Zhao Lingjuan Lyu DD 26 113 0 01 Jun 2022
Private Federated Submodel Learning with Sparsification Sajani Vithana S. Ulukus FedML 28 10 0 31 May 2022
Can Foundation Models Help Us Achieve Perfect Secrecy? Simran Arora Christopher Ré FedML 24 6 0 27 May 2022
PerDoor: Persistent Non-Uniform Backdoors in Federated Learning using Adversarial Perturbations Manaar Alam Esha Sarkar Michail Maniatakos AAML FedML 29 8 0 26 May 2022
DPSNN: A Differentially Private Spiking Neural Network with Temporal Enhanced Pooling Jihang Wang Dongcheng Zhao Guobin Shen Qian Zhang Yingda Zeng 40 2 0 24 May 2022
Lessons Learned: Defending Against Property Inference Attacks Joshua Stock Jens Wettlaufer Daniel Demmler Hannes Federrath AAML 41 1 0 18 May 2022
Recovering Private Text in Federated Learning of Language Models Samyak Gupta Yangsibo Huang Zexuan Zhong Tianyu Gao Kai Li Danqi Chen FedML 40 75 0 17 May 2022
On the (In)security of Peer-to-Peer Decentralized Machine Learning Dario Pasquini Mathilde Raynal Carmela Troncoso OOD FedML 43 19 0 17 May 2022
Collaborative Drug Discovery: Inference-level Data Protection Perspective Balázs Pejó Mina Remeli Adam Arany M. Galtier G. Ács 33 3 0 13 May 2022
l-Leaks: Membership Inference Attacks with Logits Shuhao Li Yajie Wang Yuan-zhang Li Yu-an Tan MIACV MIALM 33 2 0 13 May 2022
How to Combine Membership-Inference Attacks on Multiple Updated Models Matthew Jagielski Stanley Wu Alina Oprea Jonathan R. Ullman Roxana Geambasu 29 10 0 12 May 2022
Protecting Data from all Parties: Combining FHE and DP in Federated Learning Arnaud Grivet Sébert Renaud Sirdey Oana Stan Cédric Gouy-Pailler FedML 21 0 0 09 May 2022
Decentralized Stochastic Optimization with Inherent Privacy Protection Yongqiang Wang H. Vincent Poor 29 37 0 08 May 2022
Defending against Reconstruction Attacks through Differentially Private Federated Learning for Classification of Heterogeneous Chest X-Ray Data Joceline Ziegler Bjarne Pfitzner H. Schulz A. Saalbach B. Arnrich FedML 27 14 0 06 May 2022
Byzantine Fault Tolerance in Distributed Machine Learning : a Survey Djamila Bouhata Hamouma Moumen Moumen Hamouma Ahcène Bounceur AI4CE 31 7 0 05 May 2022
Privacy Amplification via Random Participation in Federated Learning Burak Hasircioglu Deniz Gunduz FedML 27 1 0 03 May 2022
Symbolic analysis meets federated learning to enhance malware identifier Khanh-Huu-The Dam Charles-Henry Bertrand Van Ouytsel Axel Legay FedML 29 5 0 29 Apr 2022
AGIC: Approximate Gradient Inversion Attack on Federated Learning Jin Xu Chi Hong Jiyue Huang L. Chen Jérémie Decouchant AAML FedML 34 21 0 28 Apr 2022
A review of Federated Learning in Intrusion Detection Systems for IoT Aitor Belenguer J. Navaridas J. A. Pascual 28 15 0 26 Apr 2022
Enhancing Privacy against Inversion Attacks in Federated Learning by using Mixing Gradients Strategies Shaltiel Eloul Fran Silavong Sanket Kamthe Antonios Georgiadis Sean J. Moran FedML 20 5 0 26 Apr 2022
FederatedScope: A Flexible Federated Learning Platform for Heterogeneity Yuexiang Xie Zhen Wang Dawei Gao Daoyuan Chen Liuyi Yao Weirui Kuang Yaliang Li Bolin Ding Jingren Zhou FedML 32 88 0 11 Apr 2022
User-Level Differential Privacy against Attribute Inference Attack of Speech Emotion Recognition in Federated Learning Tiantian Feng Raghuveer Peri Shrikanth Narayanan FedML 20 28 0 05 Apr 2022
Truth Serum: Poisoning Machine Learning Models to Reveal Their Secrets Florian Tramèr Reza Shokri Ayrton San Joaquin Hoang Minh Le Matthew Jagielski Sanghyun Hong Nicholas Carlini MIACV 51 109 0 31 Mar 2022
Privacy-Preserving Aggregation in Federated Learning: A Survey Ziyao Liu Jiale Guo Wenzhuo Yang Jiani Fan Kwok-Yan Lam Jun Zhao FedML 34 87 0 31 Mar 2022
Perfectly Accurate Membership Inference by a Dishonest Central Server in Federated Learning Georg Pichler Marco Romanelli L. Rey Vega Pablo Piantanida FedML 36 10 0 30 Mar 2022
Auditing Privacy Defenses in Federated Learning via Generative Gradient Leakage Zhuohang Li Jiaxin Zhang Lu Liu Jian-Dong Liu FedML 38 115 0 29 Mar 2022
SPRITE: A Scalable Privacy-Preserving and Verifiable Collaborative Learning for Industrial IoT Jayasree Sengupta Sushmita Ruj Sipra Das Bit 19 4 0 22 Mar 2022
GradViT: Gradient Inversion of Vision Transformers Ali Hatamizadeh Hongxu Yin H. Roth Wenqi Li Jan Kautz Daguang Xu Pavlo Molchanov ViT 25 63 0 22 Mar 2022
Training a Tokenizer for Free with Private Federated Learning Eugene Bagdasaryan Congzheng Song Rogier van Dalen M. Seigel Áine Cahill FedML 27 5 0 15 Mar 2022
Privatized Graph Federated Learning Elsa Rizk Stefan Vlaski Ali H. Sayed FedML 25 4 0 14 Mar 2022
Label-only Model Inversion Attack: The Attack that Requires the Least Information Dayong Ye Tianqing Zhu Shuai Zhou B. Liu Wanlei Zhou 27 4 0 13 Mar 2022
Similarity-based Label Inference Attack against Training and Inference of Split Learning Junlin Liu Xinchen Lyu Qimei Cui Xiaofeng Tao FedML 35 26 0 10 Mar 2022
The Fundamental Price of Secure Aggregation in Differentially Private Federated Learning Wei-Ning Chen Christopher A. Choquette-Choo Peter Kairouz A. Suresh FedML 42 63 0 07 Mar 2022
Training privacy-preserving video analytics pipelines by suppressing features that reveal information about private attributes C. Li Andrea Cavallaro PICV 24 0 0 05 Mar 2022
Label-Only Model Inversion Attacks via Boundary Repulsion Mostafa Kahla Si-An Chen H. Just R. Jia 35 74 0 03 Mar 2022
Beyond Gradients: Exploiting Adversarial Priors in Model Inversion Attacks Dmitrii Usynin Daniel Rueckert Georgios Kaissis SILM AAML 33 17 0 01 Mar 2022
Differentially Private Estimation of Heterogeneous Causal Effects Fengshi Niu Harsha Nori B. Quistorff R. Caruana Donald Ngwe A. Kannan CML 25 13 0 22 Feb 2022
Poisoning Attacks and Defenses on Artificial Intelligence: A Survey M. A. Ramírez Song-Kyoo Kim H. A. Hamadi Ernesto Damiani Young-Ji Byon Tae-Yeon Kim C. Cho C. Yeun AAML 25 37 0 21 Feb 2022
Trusted AI in Multi-agent Systems: An Overview of Privacy and Security for Distributed Learning Chuan Ma Jun Li Kang Wei Bo Liu Ming Ding Long Yuan Zhu Han H. Vincent Poor 61 43 0 18 Feb 2022
PPA: Preference Profiling Attack Against Federated Learning Chunyi Zhou Yansong Gao Anmin Fu Kai Chen Zhiyang Dai Zhi-Li Zhang Minhui Xue Yuqing Zhang AAML 25 22 0 10 Feb 2022
Practical Challenges in Differentially-Private Federated Survival Analysis of Medical Data Shadi Rahimian Raouf Kerkouche I. Kurth Mario Fritz FedML 22 11 0 08 Feb 2022
Private Read Update Write (PRUW) with Storage Constrained Databases Sajani Vithana S. Ulukus 29 13 0 07 Feb 2022
Efficient Privacy Preserving Logistic Regression for Horizontally Distributed Data G. Miao 18 0 0 05 Feb 2022
Dikaios: Privacy Auditing of Algorithmic Fairness via Attribute Inference Attacks Jan Aalmoes Vasisht Duddu A. Boutet 26 10 0 04 Feb 2022
Aggregation Service for Federated Learning: An Efficient, Secure, and More Resilient Realization Yifeng Zheng Shangqi Lai Yi Liu Xingliang Yuan X. Yi Cong Wang FedML 27 84 0 04 Feb 2022