Cutting Through Privacy: A Hyperplane-Based Data Reconstruction Attack in Federated Learning

Cutting Through Privacy: A Hyperplane-Based Data Reconstruction Attack in Federated Learning

15 May 2025

Francesco Diana

Giovanni Neglia

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Papers citing "Cutting Through Privacy: A Hyperplane-Based Data Reconstruction Attack in Federated Learning"

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Title
Attribute Inference Attacks for Federated Regression Tasks Francesco Diana Othmane Marfoq Chuan Xu Giovanni Neglia F. Giroire Eoin Thomas AAML 589 1 0 19 Nov 2024
TabLeak: Tabular Data Leakage in Federated Learning Mark Vero Mislav Balunović Dimitar I. Dimitrov Martin Vechev FedML 58 8 0 04 Oct 2022
Cocktail Party Attack: Breaking Aggregation-Based Privacy in Federated Learning using Independent Component Analysis Sanjay Kariyappa Chuan Guo Kiwan Maeng Wenjie Xiong G. E. Suh Moinuddin K. Qureshi Hsien-Hsin S. Lee FedML 81 29 0 12 Sep 2022
Verifying the Union of Manifolds Hypothesis for Image Data Bradley Brown Anthony L. Caterini Brendan Leigh Ross Jesse C. Cresswell Gabriel Loaiza-Ganem 101 43 0 06 Jul 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 188 97 0 01 Feb 2022
APRIL: Finding the Achilles' Heel on Privacy for Vision Transformers Jiahao Lu Xi Sheryl Zhang Tianli Zhao Xiangyu He Jian Cheng ViT PILM 57 23 0 28 Dec 2021
When the Curious Abandon Honesty: Federated Learning Is Not Private Franziska Boenisch Adam Dziedzic R. Schuster Ali Shahin Shamsabadi Ilia Shumailov Nicolas Papernot FedML AAML 97 186 0 06 Dec 2021
The Intrinsic Dimension of Images and Its Impact on Learning Phillip E. Pope Chen Zhu Ahmed Abdelkader Micah Goldblum Tom Goldstein 231 273 0 18 Apr 2021
Label-Only Membership Inference Attacks Christopher A. Choquette-Choo Florian Tramèr Nicholas Carlini Nicolas Papernot MIACV MIALM 96 516 0 28 Jul 2020
Inverting Gradients -- How easy is it to break privacy in federated learning? Jonas Geiping Hartmut Bauermeister Hannah Dröge Michael Moeller FedML 109 1,235 0 31 Mar 2020
iDLG: Improved Deep Leakage from Gradients Bo Zhao Konda Reddy Mopuri Hakan Bilen FedML 69 643 0 08 Jan 2020
Exploiting Unintended Feature Leakage in Collaborative Learning Luca Melis Congzheng Song Emiliano De Cristofaro Vitaly Shmatikov FedML 155 1,481 0 10 May 2018
Revisiting Distributed Synchronous SGD Jianmin Chen Xinghao Pan R. Monga Samy Bengio Rafal Jozefowicz 87 801 0 04 Apr 2016
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 406 17,593 0 17 Feb 2016
ImageNet Large Scale Visual Recognition Challenge Olga Russakovsky Jia Deng Hao Su J. Krause S. Satheesh ... A. Karpathy A. Khosla Michael S. Bernstein Alexander C. Berg Li Fei-Fei VLM ObjD 1.7K 39,595 0 01 Sep 2014