Inverting Gradients -- How easy is it to break privacy in federated learning?

31 March 2020

Papers citing "Inverting Gradients -- How easy is it to break privacy in federated learning?"

50 / 229 papers shown

Title
A Survey on Gradient Inversion: Attacks, Defenses and Future Directions Rui Zhang Song Guo Junxiao Wang Xin Xie Dacheng Tao 35 36 0 15 Jun 2022
Deep Leakage from Model in Federated Learning Zihao Zhao Mengen Luo Wenbo Ding FedML 26 14 0 10 Jun 2022
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 34 8 0 07 Jun 2022
Subject Membership Inference Attacks in Federated Learning Anshuman Suri Pallika H. Kanani Virendra J. Marathe Daniel W. Peterson 30 25 0 07 Jun 2022
Private Federated Submodel Learning with Sparsification Sajani Vithana S. Ulukus FedML 26 10 0 31 May 2022
Secure Federated Clustering Songze Li Sizai Hou Baturalp Buyukates A. Avestimehr FedML 23 9 0 31 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
FLAD: Adaptive Federated Learning for DDoS Attack Detection Roberto Doriguzzi-Corin Domenico Siracusa FedML 42 61 0 13 May 2022
On Conditioning the Input Noise for Controlled Image Generation with Diffusion Models Vedant Singh Surgan Jandial Ayush Chopra Siddharth Ramesh Balaji Krishnamurthy V. Balasubramanian DiffM 32 16 0 08 May 2022
Training Mixed-Domain Translation Models via Federated Learning Peyman Passban Tanya Roosta Rahul Gupta Ankit R. Chadha Clement Chung FedML AI4CE 29 18 0 03 May 2022
AGIC: Approximate Gradient Inversion Attack on Federated Learning Jin Xu Chi Hong Jiyue Huang L. Chen Jérémie Decouchant AAML FedML 31 21 0 28 Apr 2022
IOP-FL: Inside-Outside Personalization for Federated Medical Image Segmentation Meirui Jiang Hongzheng Yang Chen Cheng Qianming Dou 37 32 0 16 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 27 88 0 11 Apr 2022
HBFL: A Hierarchical Blockchain-based Federated Learning Framework for a Collaborative IoT Intrusion Detection Mohanad Sarhan Wai Weng Lo S. Layeghy Marius Portmann 26 59 0 08 Apr 2022
Multi-Task Distributed Learning using Vision Transformer with Random Patch Permutation Sangjoon Park Jong Chul Ye FedML MedIm 44 19 0 07 Apr 2022
SwiftAgg+: Achieving Asymptotically Optimal Communication Loads in Secure Aggregation for Federated Learning Tayyebeh Jahani-Nezhad M. Maddah-ali Songze Li Giuseppe Caire FedML 34 45 0 24 Mar 2022
Adaptive Aggregation For Federated Learning K.R. Jayaram Vinod Muthusamy Gegi Thomas Ashish Verma Mark Purcell FedML 33 16 0 23 Mar 2022
Closing the Generalization Gap of Cross-silo Federated Medical Image Segmentation An Xu Wenqi Li Pengfei Guo Dong Yang H. Roth Ali Hatamizadeh Can Zhao Daguang Xu Heng-Chiao Huang Ziyue Xu FedML 38 51 0 18 Mar 2022
Auto-FedRL: Federated Hyperparameter Optimization for Multi-institutional Medical Image Segmentation Pengfei Guo Dong Yang Ali Hatamizadeh An Xu Ziyue Xu ... F. Patella Elvira Stellato G. Carrafiello Vishal M. Patel H. Roth OOD FedML 28 32 0 12 Mar 2022
No Free Lunch Theorem for Security and Utility in Federated Learning Xiaojin Zhang Hanlin Gu Lixin Fan Kai Chen Qiang Yang FedML 24 64 0 11 Mar 2022
Acceleration of Federated Learning with Alleviated Forgetting in Local Training Chencheng Xu Zhiwei Hong Minlie Huang Tao Jiang FedML 29 46 0 05 Mar 2022
Privacy Leakage of Adversarial Training Models in Federated Learning Systems Jingyang Zhang Yiran Chen Hai Helen Li FedML PICV 35 15 0 21 Feb 2022
LAMP: Extracting Text from Gradients with Language Model Priors Mislav Balunović Dimitar I. Dimitrov Nikola Jovanović Martin Vechev 27 57 0 17 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
Differentially Private Graph Classification with GNNs Tamara T. Mueller Johannes C. Paetzold Chinmay Prabhakar Dmitrii Usynin Daniel Rueckert Georgios Kaissis 52 18 0 05 Feb 2022
Comparative assessment of federated and centralized machine learning Ibrahim Abdul Majeed Sagar Kaushik Aniruddha Bardhan Venkata Siva Kumar Tadi Hwang-Ki Min K. Kumaraguru Rajasekhara Reddy Duvvuru Muni FedML 31 6 0 03 Feb 2022
Fishing for User Data in Large-Batch Federated Learning via Gradient Magnification Yuxin Wen Jonas Geiping Liam H. Fowl Micah Goldblum Tom Goldstein FedML 92 93 0 01 Feb 2022
Variational Model Inversion Attacks Kuan-Chieh Jackson Wang Yanzhe Fu Ke Li Ashish Khisti R. Zemel Alireza Makhzani MIACV 25 95 0 26 Jan 2022
TOFU: Towards Obfuscated Federated Updates by Encoding Weight Updates into Gradients from Proxy Data Isha Garg M. Nagaraj Kaushik Roy FedML 31 1 0 21 Jan 2022
Survey on Federated Learning Threats: concepts, taxonomy on attacks and defences, experimental study and challenges Nuria Rodríguez-Barroso Daniel Jiménez López M. V. Luzón Francisco Herrera Eugenio Martínez-Cámara FedML 37 212 0 20 Jan 2022
Reconstructing Training Data with Informed Adversaries Borja Balle Giovanni Cherubin Jamie Hayes MIACV AAML 50 159 0 13 Jan 2022
When Machine Learning Meets Spectrum Sharing Security: Methodologies and Challenges Qun Wang Haijian Sun R. Hu Arupjyoti Bhuyan 31 23 0 12 Jan 2022
Data-Free Knowledge Transfer: A Survey Yuang Liu Wei Zhang Jun Wang Jianyong Wang 37 48 0 31 Dec 2021
Challenges and Approaches for Mitigating Byzantine Attacks in Federated Learning Junyu Shi Wei Wan Shengshan Hu Jianrong Lu L. Zhang AAML 42 74 0 29 Dec 2021
Gradient Leakage Attack Resilient Deep Learning Wenqi Wei Ling Liu SILM PILM AAML 27 47 0 25 Dec 2021
Sparsified Secure Aggregation for Privacy-Preserving Federated Learning Irem Ergun Hasin Us Sami Başak Güler FedML 41 26 0 23 Dec 2021
HarmoFL: Harmonizing Local and Global Drifts in Federated Learning on Heterogeneous Medical Images Meirui Jiang Zirui Wang Qi Dou FedML 33 123 0 20 Dec 2021
Robust and Privacy-Preserving Collaborative Learning: A Comprehensive Survey Shangwei Guo Xu Zhang Feiyu Yang Tianwei Zhang Yan Gan Tao Xiang Yang Liu FedML 31 9 0 19 Dec 2021
Location Leakage in Federated Signal Maps Evita Bakopoulou Justin Ley Jiang Zhang Konstantinos Psounis A. Markopoulou FedML 20 5 0 07 Dec 2021
Improving Differentially Private SGD via Randomly Sparsified Gradients Junyi Zhu Matthew B. Blaschko 30 5 0 01 Dec 2021
Evaluating Gradient Inversion Attacks and Defenses in Federated Learning Yangsibo Huang Samyak Gupta Zhao Song Kai Li Sanjeev Arora FedML AAML SILM 31 269 0 30 Nov 2021
Differentially Private Federated Learning on Heterogeneous Data Maxence Noble A. Bellet Aymeric Dieuleveut FedML 13 102 0 17 Nov 2021
Privacy-preserving Federated Learning for Residential Short Term Load Forecasting Joaquín Delgado Fernández Sergio Potenciano Menci Chul Min Lee Gilbert Fridgen 33 53 0 17 Nov 2021
FedCG: Leverage Conditional GAN for Protecting Privacy and Maintaining Competitive Performance in Federated Learning Yuezhou Wu Yan Kang Jiahuan Luo Yuanqin He Qiang Yang FedML AAML 19 69 0 16 Nov 2021
Federated Learning for Internet of Things: Applications, Challenges, and Opportunities Tuo Zhang Lei Gao Chaoyang He Mi Zhang Bhaskar Krishnamachari Salman Avestimehr FedML 19 168 0 15 Nov 2021
Bayesian Framework for Gradient Leakage Mislav Balunović Dimitar I. Dimitrov Robin Staab Martin Vechev FedML 27 41 0 08 Nov 2021
Privacy attacks for automatic speech recognition acoustic models in a federated learning framework N. Tomashenko Salima Mdhaffar Marc Tommasi Yannick Esteve J. Bonastre 38 25 0 06 Nov 2021
Confidential Machine Learning Computation in Untrusted Environments: A Systems Security Perspective Kha Dinh Duy Taehyun Noh Siwon Huh Hojoon Lee 56 9 0 05 Nov 2021
What Do We Mean by Generalization in Federated Learning? Honglin Yuan Warren Morningstar Lin Ning K. Singhal OOD FedML 41 71 0 27 Oct 2021