More is Better (Mostly): On the Backdoor Attacks in Federated Graph
Neural Networks

More is Better (Mostly): On the Backdoor Attacks in Federated Graph Neural Networks

7 February 2022

Stefanos Koffas

Papers citing "More is Better (Mostly): On the Backdoor Attacks in Federated Graph Neural Networks"

14 / 14 papers shown

Title
XBreaking: Explainable Artificial Intelligence for Jailbreaking LLMs Marco Arazzi Vignesh Kumar Kembu Antonino Nocera V. P. 80 0 0 30 Apr 2025
Privacy Preserving and Robust Aggregation for Cross-Silo Federated Learning in Non-IID Settings Marco Arazzi Mert Cihangiroglu Antonino Nocera FedML 74 0 0 06 Mar 2025
Backdoor Attack on Vertical Federated Graph Neural Network Learning Jirui Yang Peng Chen Zhihui Lu Ruijun Deng Qiang Duan Jianping Zeng AAML FedML 99 0 0 15 Oct 2024
Adversarially Guided Stateful Defense Against Backdoor Attacks in Federated Deep Learning Hassan Ali Surya Nepal S. Kanhere S. Jha AAML FedML 24 1 0 15 Oct 2024
Distributed Backdoor Attacks on Federated Graph Learning and Certified Defenses Yuxin Yang Qiang Li Jinyuan Jia Yuan Hong Binghui Wang AAML FedML 49 11 0 12 Jul 2024
Let's Focus: Focused Backdoor Attack against Federated Transfer Learning Marco Arazzi Stefanos Koffas Antonino Nocera S. Picek AAML FedML 24 3 0 30 Apr 2024
Data and Model Poisoning Backdoor Attacks on Wireless Federated Learning, and the Defense Mechanisms: A Comprehensive Survey Yichen Wan Youyang Qu Wei Ni Yong Xiang Longxiang Gao Ekram Hossain AAML 45 33 0 14 Dec 2023
FreqFed: A Frequency Analysis-Based Approach for Mitigating Poisoning Attacks in Federated Learning Hossein Fereidooni Alessandro Pegoraro Phillip Rieger Alexandra Dmitrienko Ahmad-Reza Sadeghi AAML 13 12 0 07 Dec 2023
Bkd-FedGNN: A Benchmark for Classification Backdoor Attacks on Federated Graph Neural Network F. Liu Siqi Lai Yansong NING Hao Liu AAML FedML 27 3 0 17 Jun 2023
Federated Graph Machine Learning: A Survey of Concepts, Techniques, and Applications Xingbo Fu Binchi Zhang Yushun Dong Chen Chen Jundong Li FedML OOD AI4CE 21 35 0 24 Jul 2022
A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability Enyan Dai Tianxiang Zhao Huaisheng Zhu Jun Xu Zhimeng Guo Hui Liu Jiliang Tang Suhang Wang 29 131 0 18 Apr 2022
FLAME: Taming Backdoors in Federated Learning (Extended Version 1) T. D. Nguyen Phillip Rieger Huili Chen Hossein Yalame Helen Mollering ... Azalia Mirhoseini S. Zeitouni F. Koushanfar A. Sadeghi T. Schneider AAML 19 26 0 06 Jan 2021
FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping Xiaoyu Cao Minghong Fang Jia Liu Neil Zhenqiang Gong FedML 106 611 0 27 Dec 2020
Analyzing Federated Learning through an Adversarial Lens A. Bhagoji Supriyo Chakraborty Prateek Mittal S. Calo FedML 177 1,032 0 29 Nov 2018