Turning Federated Learning Systems Into Covert Channels

21 April 2021

Gabriele Tolomei

Papers citing "Turning Federated Learning Systems Into Covert Channels"

44 / 44 papers shown

Title
FedComm: Federated Learning as a Medium for Covert Communication Dorjan Hitaj Giulio Pagnotta Briland Hitaj Fernando Perez-Cruz L. Mancini FedML 39 10 0 21 Jan 2022
Dataset Security for Machine Learning: Data Poisoning, Backdoor Attacks, and Defenses Micah Goldblum Dimitris Tsipras Chulin Xie Xinyun Chen Avi Schwarzschild D. Song Aleksander Madry Yue Liu Tom Goldstein SILM 56 274 0 18 Dec 2020
VenoMave: Targeted Poisoning Against Speech Recognition H. Aghakhani Lea Schonherr Thorsten Eisenhofer D. Kolossa Thorsten Holz Christopher Kruegel Giovanni Vigna AAML 18 17 0 21 Oct 2020
Data Poisoning Attacks Against Federated Learning Systems Vale Tolpegin Stacey Truex Mehmet Emre Gursoy Ling Liu FedML 97 646 0 16 Jul 2020
Data Poisoning Attacks on Federated Machine Learning Gan Sun Yang Cong Jiahua Dong Qiang Wang Ji Liu FedML AAML 31 205 0 19 Apr 2020
Threats to Federated Learning: A Survey Lingjuan Lyu Han Yu Qiang Yang FedML 256 437 0 04 Mar 2020
Personalized Federated Learning for Intelligent IoT Applications: A Cloud-Edge based Framework Qiong Wu Kaiwen He Xu Chen 41 282 0 25 Feb 2020
Advances and Open Problems in Federated Learning Peter Kairouz H. B. McMahan Brendan Avent A. Bellet M. Bennis ... Zheng Xu Qiang Yang Felix X. Yu Han Yu Sen Zhao FedML AI4CE 98 6,177 0 10 Dec 2019
PyTorch: An Imperative Style, High-Performance Deep Learning Library Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury ... Sasank Chilamkurthy Benoit Steiner Lu Fang Junjie Bai Soumith Chintala ODL 211 42,038 0 03 Dec 2019
Local Model Poisoning Attacks to Byzantine-Robust Federated Learning Minghong Fang Xiaoyu Cao Jinyuan Jia Neil Zhenqiang Gong AAML OOD FedML 92 1,093 0 26 Nov 2019
Federated Learning with Differential Privacy: Algorithms and Performance Analysis Kang Wei Jun Li Ming Ding Chuan Ma Heng Yang Farokhi Farhad Shi Jin Tony Q.S. Quek H. Vincent Poor FedML 84 1,589 0 01 Nov 2019
FedHealth: A Federated Transfer Learning Framework for Wearable Healthcare Yiqiang Chen Jindong Wang Chaohui Yu Wen Gao Xin Qin FedML 58 710 0 22 Jul 2019
Transferable Clean-Label Poisoning Attacks on Deep Neural Nets Chen Zhu Wenjie Huang Ali Shafahi Hengduo Li Gavin Taylor Christoph Studer Tom Goldstein 59 284 0 15 May 2019
Backdooring Convolutional Neural Networks via Targeted Weight Perturbations Jacob Dumford Walter J. Scheirer AAML 39 117 0 07 Dec 2018
Applied Federated Learning: Improving Google Keyboard Query Suggestions Timothy Yang Galen Andrew Hubert Eichner Haicheng Sun Wei Li Nicholas Kong Daniel Ramage F. Beaufays FedML 66 624 0 07 Dec 2018
Model-Reuse Attacks on Deep Learning Systems Yujie Ji Xinyang Zhang S. Ji Xiapu Luo Ting Wang SILM AAML 166 186 0 02 Dec 2018
Analyzing Federated Learning through an Adversarial Lens A. Bhagoji Supriyo Chakraborty Prateek Mittal S. Calo FedML 244 1,044 0 29 Nov 2018
Exploring Adversarial Examples in Malware Detection Octavian Suciu Scott E. Coull Jeffrey Johns AAML 37 190 0 18 Oct 2018
Morpho-MNIST: Quantitative Assessment and Diagnostics for Representation Learning Daniel Coelho De Castro Jeremy Tan Bernhard Kainz E. Konukoglu Ben Glocker DRL 22 70 0 27 Sep 2018
Poisoning Attacks to Graph-Based Recommender Systems Minghong Fang Guolei Yang Neil Zhenqiang Gong Jia-Wei Liu AAML 49 204 0 11 Sep 2018
Universal Multi-Party Poisoning Attacks Saeed Mahloujifar Mohammad Mahmoody Ameer Mohammed AAML 34 44 0 10 Sep 2018
Mitigating Sybils in Federated Learning Poisoning Clement Fung Chris J. M. Yoon Ivan Beschastnikh AAML 30 498 0 14 Aug 2018
How To Backdoor Federated Learning Eugene Bagdasaryan Andreas Veit Yiqing Hua D. Estrin Vitaly Shmatikov SILM FedML 67 1,892 0 02 Jul 2018
Exploiting Unintended Feature Leakage in Collaborative Learning Luca Melis Congzheng Song Emiliano De Cristofaro Vitaly Shmatikov FedML 128 1,461 0 10 May 2018
Is feature selection secure against training data poisoning? Huang Xiao Battista Biggio Gavin Brown Giorgio Fumera Claudia Eckert Fabio Roli AAML SILM 36 423 0 21 Apr 2018
Poison Frogs! Targeted Clean-Label Poisoning Attacks on Neural Networks Ali Shafahi Wenjie Huang Mahyar Najibi Octavian Suciu Christoph Studer Tudor Dumitras Tom Goldstein AAML 73 1,080 0 03 Apr 2018
Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning Matthew Jagielski Alina Oprea Battista Biggio Chang-rui Liu Cristina Nita-Rotaru Yue Liu AAML 57 757 0 01 Apr 2018
Technical Report: When Does Machine Learning FAIL? Generalized Transferability for Evasion and Poisoning Attacks Octavian Suciu R. Marginean Yigitcan Kaya Hal Daumé Tudor Dumitras AAML 67 287 0 19 Mar 2018
Stealing Hyperparameters in Machine Learning Binghui Wang Neil Zhenqiang Gong AAML 121 461 0 14 Feb 2018
Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning Xinyun Chen Chang-rui Liu Yue Liu Kimberly Lu D. Song AAML SILM 78 1,822 0 15 Dec 2017
Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning Battista Biggio Fabio Roli AAML 85 1,401 0 08 Dec 2017
BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain Tianyu Gu Brendan Dolan-Gavitt S. Garg SILM 72 1,754 0 22 Aug 2017
Knock Knock, Who's There? Membership Inference on Aggregate Location Data Apostolos Pyrgelis Carmela Troncoso Emiliano De Cristofaro MIACV 90 269 0 21 Aug 2017
Evasion Attacks against Machine Learning at Test Time Battista Biggio Igino Corona Davide Maiorca B. Nelson Nedim Srndic Pavel Laskov Giorgio Giacinto Fabio Roli AAML 93 2,140 0 21 Aug 2017
Membership Inference Attacks against Machine Learning Models Reza Shokri M. Stronati Congzheng Song Vitaly Shmatikov SLR MIALM MIACV 200 4,075 0 18 Oct 2016
Stealing Machine Learning Models via Prediction APIs Florian Tramèr Fan Zhang Ari Juels Michael K. Reiter Thomas Ristenpart SILM MLAU 66 1,798 0 09 Sep 2016
Data Poisoning Attacks on Factorization-Based Collaborative Filtering Bo Li Yining Wang Aarti Singh Yevgeniy Vorobeychik AAML 53 341 0 29 Aug 2016
Towards Evaluating the Robustness of Neural Networks Nicholas Carlini D. Wagner OOD AAML 157 8,497 0 16 Aug 2016
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 226 17,235 0 17 Feb 2016
Practical Black-Box Attacks against Machine Learning Nicolas Papernot Patrick McDaniel Ian Goodfellow S. Jha Z. Berkay Celik A. Swami MLAU AAML 44 3,656 0 08 Feb 2016
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 775 99,991 0 04 Sep 2014
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 157 14,831 1 21 Dec 2013
Hacking Smart Machines with Smarter Ones: How to Extract Meaningful Data from Machine Learning Classifiers G. Ateniese G. Felici L. Mancini A. Spognardi Antonio Villani Domenico Vitali 57 458 0 19 Jun 2013
Poisoning Attacks against Support Vector Machines Battista Biggio B. Nelson Pavel Laskov AAML 77 1,580 0 27 Jun 2012