Survey on Federated Learning Threats: concepts, taxonomy on attacks and defences, experimental study and challenges

20 January 2022

Nuria Rodríguez-Barroso

Daniel Jiménez López

M. V. Luzón

Francisco Herrera

Eugenio Martínez-Cámara

FedML

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Papers citing "Survey on Federated Learning Threats: concepts, taxonomy on attacks and defences, experimental study and challenges"

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Title
Decoding FL Defenses: Systemization, Pitfalls, and Remedies M. A. Khan Virat Shejwalkar Yasra Chandio Amir Houmansadr Fatima M. Anwar AAML 38 0 0 03 Feb 2025
Privacy-preserving datasets by capturing feature distributions with Conditional VAEs Francesco Di Salvo David Tafler Sebastian Doerrich Christian Ledig CML 34 0 0 01 Aug 2024
DART: A Solution for Decentralized Federated Learning Model Robustness Analysis Chao Feng Alberto Huertas Celdrán Jan von der Assen Enrique Tomás Martínez Beltrán Gérome Bovet Burkhard Stiller OOD AAML 54 8 0 11 Jul 2024
Federated Learning with Flexible Architectures Jong-Ik Park Carlee Joe-Wong FedML 39 3 0 14 Jun 2024
Data Quality in Edge Machine Learning: A State-of-the-Art Survey M. D. Belgoumri Mohamed Reda Bouadjenek Sunil Aryal Hakim Hacid 41 1 0 01 Jun 2024
A Systematic Review of Federated Generative Models Ashkan Vedadi Gargary Emiliano De Cristofaro AI4CE 38 2 0 26 May 2024
Federated Learning for 6G: Paradigms, Taxonomy, Recent Advances and Insights Maryam Ben Driss Essaid Sabir H. Elbiaze Walid Saad 30 7 0 07 Dec 2023
FBChain: A Blockchain-based Federated Learning Model with Efficiency and Secure Communication Yang Li Chunhe Xia Wei Liu 35 0 0 21 Nov 2023
A Survey of What to Share in Federated Learning: Perspectives on Model Utility, Privacy Leakage, and Communication Efficiency Jiawei Shao Zijian Li Wenqiang Sun Tailin Zhou Yuchang Sun Lumin Liu Zehong Lin Yuyi Mao Jun Zhang FedML 43 23 0 20 Jul 2023
Attacks on Robust Distributed Learning Schemes via Sensitivity Curve Maximization Christian A. Schroth Stefan Vlaski A. Zoubir FedML 55 1 0 27 Apr 2023
Protecting Federated Learning from Extreme Model Poisoning Attacks via Multidimensional Time Series Anomaly Detection Edoardo Gabrielli Dimitri Belli Vittorio Miori Gabriele Tolomei AAML 13 4 0 29 Mar 2023
A Survey of Trustworthy Federated Learning with Perspectives on Security, Robustness, and Privacy Yifei Zhang Dun Zeng Jinglong Luo Zenglin Xu Irwin King FedML 84 47 0 21 Feb 2023
Poisoning Attacks and Defenses in Federated Learning: A Survey S. Sagar Chang-Sun Li S. W. Loke Jinho D. Choi OOD FedML 18 9 0 14 Jan 2023
New Challenges in Reinforcement Learning: A Survey of Security and Privacy Yunjiao Lei Dayong Ye Sheng Shen Yulei Sui Tianqing Zhu Wanlei Zhou 33 18 0 31 Dec 2022
Decentralized Federated Learning: Fundamentals, State of the Art, Frameworks, Trends, and Challenges Enrique Tomás Martínez Beltrán Mario Quiles Pérez Pedro Miguel Sánchez Sánchez Sergio López Bernal Gérome Bovet M. Pérez Gregorio Martínez Pérez Alberto Huertas Celdrán FedML 26 221 0 15 Nov 2022
Edge Security: Challenges and Issues Xin Jin Charalampos Katsis Fan Sang Jiahao Sun A. Kundu Ramana Rao Kompella 47 8 0 14 Jun 2022
Differential Privacy: What is all the noise about? Roxana Dánger Mercaderes 35 3 0 19 May 2022
Studying the Robustness of Anti-adversarial Federated Learning Models Detecting Cyberattacks in IoT Spectrum Sensors Pedro Miguel Sánchez Sánchez Alberto Huertas Celdrán T. Schenk A. Iten Gérome Bovet Gregorio Martínez Pérez Burkhard Stiller AAML 17 18 0 31 Jan 2022
DeSMP: Differential Privacy-exploited Stealthy Model Poisoning Attacks in Federated Learning Md Tamjid Hossain Shafkat Islam S. Badsha Haoting Shen AAML 50 41 0 21 Sep 2021
GRNN: Generative Regression Neural Network -- A Data Leakage Attack for Federated Learning Hanchi Ren Jingjing Deng Xianghua Xie SILM AAML FedML 53 100 0 02 May 2021
Turning Federated Learning Systems Into Covert Channels Gabriele Costa Fabio Pinelli S. Soderi Gabriele Tolomei FedML 37 10 0 21 Apr 2021
Towards Personalized Federated Learning A. Tan Han Yu Li-zhen Cui Qiang Yang FedML AI4CE 209 840 0 01 Mar 2021
Label Leakage and Protection in Two-party Split Learning Oscar Li Jiankai Sun Xin Yang Weihao Gao Hongyi Zhang Junyuan Xie Virginia Smith Chong-Jun Wang FedML 124 139 0 17 Feb 2021
Privacy and Robustness in Federated Learning: Attacks and Defenses Lingjuan Lyu Han Yu Xingjun Ma Chen Chen Lichao Sun Jun Zhao Qiang Yang Philip S. Yu FedML 183 355 0 07 Dec 2020
Analyzing Federated Learning through an Adversarial Lens A. Bhagoji Supriyo Chakraborty Prateek Mittal S. Calo FedML 182 1,032 0 29 Nov 2018