Local and Central Differential Privacy for Robustness and Privacy in Federated Learning

8 September 2020

Mohammad Naseri

Jamie Hayes

Emiliano De Cristofaro

FedML

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Papers citing "Local and Central Differential Privacy for Robustness and Privacy in Federated Learning"

22 / 22 papers shown

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
Gradient Purification: Defense Against Poisoning Attack in Decentralized Federated Learning Bin Li Xiaoye Miao Yongheng Shang Xinkui Zhao AAML 44 0 0 08 Jan 2025
Universally Harmonizing Differential Privacy Mechanisms for Federated Learning: Boosting Accuracy and Convergence Shuya Feng Meisam Mohammady Hanbin Hong Shenao Yan Ashish Kundu Binghui Wang Yuan Hong FedML 36 3 0 20 Jul 2024
Partner in Crime: Boosting Targeted Poisoning Attacks against Federated Learning Shihua Sun Shridatt Sugrim Angelos Stavrou Haining Wang AAML 47 1 0 13 Jul 2024
A Systematic Review of Federated Generative Models Ashkan Vedadi Gargary Emiliano De Cristofaro AI4CE 36 2 0 26 May 2024
State-of-the-Art Approaches to Enhancing Privacy Preservation of Machine Learning Datasets: A Survey Chaoyu Zhang Shaoyu Li AILaw 48 3 0 25 Feb 2024
Clients Collaborate: Flexible Differentially Private Federated Learning with Guaranteed Improvement of Utility-Privacy Trade-off Yuecheng Li Lele Fu Tong Wang Jian Lou Bin Chen Lei Yang Zibin Zheng Zibin Zheng Chuan Chen FedML 65 4 0 10 Feb 2024
Federated learning with differential privacy and an untrusted aggregator Kunlong Liu Trinabh Gupta 37 0 0 17 Dec 2023
Avoid Adversarial Adaption in Federated Learning by Multi-Metric Investigations T. Krauß Alexandra Dmitrienko AAML 16 4 0 06 Jun 2023
BadVFL: Backdoor Attacks in Vertical Federated Learning Mohammad Naseri Yufei Han Emiliano De Cristofaro FedML AAML 24 11 0 18 Apr 2023
FederatedTrust: A Solution for Trustworthy Federated Learning Pedro Miguel Sánchez Sánchez Alberto Huertas Celdrán Ning Xie Gérome Bovet Gregorio Martínez Pérez Burkhard Stiller 28 21 0 20 Feb 2023
BayBFed: Bayesian Backdoor Defense for Federated Learning Kavita Kumari Phillip Rieger Hossein Fereidooni Murtuza Jadliwala A. Sadeghi AAML FedML 21 31 0 23 Jan 2023
Unraveling the Connections between Privacy and Certified Robustness in Federated Learning Against Poisoning Attacks Chulin Xie Yunhui Long Pin-Yu Chen Qinbin Li Arash Nourian Sanmi Koyejo Bo Li FedML 35 13 0 08 Sep 2022
Cerberus: Exploring Federated Prediction of Security Events Mohammad Naseri Yufei Han Enrico Mariconti Yun Shen Gianluca Stringhini Emiliano De Cristofaro FedML 45 14 0 07 Sep 2022
Joint Privacy Enhancement and Quantization in Federated Learning Natalie Lang Elad Sofer Tomer Shaked Nir Shlezinger FedML 27 46 0 23 Aug 2022
Enhanced Security and Privacy via Fragmented Federated Learning N. Jebreel J. Domingo-Ferrer Alberto Blanco-Justicia David Sánchez FedML 13 26 0 13 Jul 2022
Fine-grained Poisoning Attack to Local Differential Privacy Protocols for Mean and Variance Estimation Xiaoguang Li Ninghui Li Wenhai Sun Neil Zhenqiang Gong Hui Li AAML 56 15 0 24 May 2022
Scatterbrained: A flexible and expandable pattern for decentralized machine learning Miller Wilt Jordan K Matelsky A. Gearhart FedML OOD 19 4 0 14 Dec 2021
A Distributed Privacy-Preserving Learning Dynamics in General Social Networks Youming Tao Shuzhen Chen Feng Li Dongxiao Yu Jiguo Yu Hao Sheng FedML 11 3 0 15 Nov 2020
Backdooring and Poisoning Neural Networks with Image-Scaling Attacks Erwin Quiring Konrad Rieck AAML 46 70 0 19 Mar 2020
Threats to Federated Learning: A Survey Lingjuan Lyu Han Yu Qiang Yang FedML 191 434 0 04 Mar 2020
Analyzing Federated Learning through an Adversarial Lens A. Bhagoji Supriyo Chakraborty Prateek Mittal S. Calo FedML 177 1,032 0 29 Nov 2018