DMGNN: Detecting and Mitigating Backdoor Attacks in Graph Neural Networks
Fuente:
arXiv
Saved in:
| Main Authors: | Sui, Hao, Chen, Bing, Zhang, Jiale, Zhu, Chengcheng, Wu, Di, Lu, Qinghua, Long, Guodong |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
BDPFL: Backdoor Defense for Personalized Federated Learning via Explainable Distillation
by: Zhu, Chengcheng, et al.
Published: (2025)
by: Zhu, Chengcheng, et al.
Published: (2025)
"No Matter What You Do": Purifying GNN Models via Backdoor Unlearning
by: Zhang, Jiale, et al.
Published: (2024)
by: Zhang, Jiale, et al.
Published: (2024)
Fine-tuning is Not Fine: Mitigating Backdoor Attacks in GNNs with Limited Clean Data
by: Zhang, Jiale, et al.
Published: (2025)
by: Zhang, Jiale, et al.
Published: (2025)
Infighting in the Dark: Multi-Label Backdoor Attack in Federated Learning
by: Li, Ye, et al.
Published: (2024)
by: Li, Ye, et al.
Published: (2024)
Awakening the Hydra: Stabilizing Multi-Concept Backdoor Injection in Text-to-Image Diffusion Models
by: Wang, Kai, et al.
Published: (2026)
by: Wang, Kai, et al.
Published: (2026)
Backdoor Attack on Vertical Federated Graph Neural Network Learning
by: Yang, Jirui, et al.
Published: (2024)
by: Yang, Jirui, et al.
Published: (2024)
Defending against Backdoor Attack on Deep Neural Networks
by: Cheng, Hao, et al.
Published: (2020)
by: Cheng, Hao, et al.
Published: (2020)
PiDAn: A Coherence Optimization Approach for Backdoor Attack Detection and Mitigation in Deep Neural Networks
by: Wang, Yue, et al.
Published: (2022)
by: Wang, Yue, et al.
Published: (2022)
Adaptive Backdoor Attacks with Reasonable Constraints on Graph Neural Networks
by: Dong, Xuewen, et al.
Published: (2025)
by: Dong, Xuewen, et al.
Published: (2025)
SPA: Towards More Stealth and Persistent Backdoor Attacks in Federated Learning
by: Zhu, Chengcheng, et al.
Published: (2025)
by: Zhu, Chengcheng, et al.
Published: (2025)
Diff-Cleanse: Identifying and Mitigating Backdoor Attacks in Diffusion Models
by: Hao, Jiang, et al.
Published: (2024)
by: Hao, Jiang, et al.
Published: (2024)
BadRSSD: Backdoor Attacks on Regularized Self-Supervised Diffusion Models
by: Wang, Jiayao, et al.
Published: (2026)
by: Wang, Jiayao, et al.
Published: (2026)
Provable Robustness of (Graph) Neural Networks Against Data Poisoning and Backdoor Attacks
by: Gosch, Lukas, et al.
Published: (2024)
by: Gosch, Lukas, et al.
Published: (2024)
Unsupervised Backdoor Detection and Mitigation for Spiking Neural Networks
by: Li, Jiachen, et al.
Published: (2025)
by: Li, Jiachen, et al.
Published: (2025)
BDFirewall: Towards Effective and Expeditiously Black-Box Backdoor Defense in MLaaS
by: Li, Ye, et al.
Published: (2025)
by: Li, Ye, et al.
Published: (2025)
Stealthy Yet Effective: Distribution-Preserving Backdoor Attacks on Graph Classification
by: Wang, Xiaobao, et al.
Published: (2025)
by: Wang, Xiaobao, et al.
Published: (2025)
More is Better (Mostly): On the Backdoor Attacks in Federated Graph Neural Networks
by: Xu, Jing, et al.
Published: (2022)
by: Xu, Jing, et al.
Published: (2022)
Beyond Dataset Watermarking: Model-Level Copyright Protection for Code Summarization Models
by: Zhang, Jiale, et al.
Published: (2024)
by: Zhang, Jiale, et al.
Published: (2024)
Heterogeneous Graph Backdoor Attack
by: Chen, Jiawei, et al.
Published: (2025)
by: Chen, Jiawei, et al.
Published: (2025)
Backdoor Attacks on Discrete Graph Diffusion Models
by: Wang, Jiawen, et al.
Published: (2025)
by: Wang, Jiawen, et al.
Published: (2025)
Rethinking Graph Backdoor Attacks: A Distribution-Preserving Perspective
by: Zhang, Zhiwei, et al.
Published: (2024)
by: Zhang, Zhiwei, et al.
Published: (2024)
STEP: Detecting Audio Backdoor Attacks via Stability-based Trigger Exposure Profiling
by: Wang, Kun, et al.
Published: (2026)
by: Wang, Kun, et al.
Published: (2026)
TEN-GUARD: Tensor Decomposition for Backdoor Attack Detection in Deep Neural Networks
by: Hossain, Khondoker Murad, et al.
Published: (2024)
by: Hossain, Khondoker Murad, et al.
Published: (2024)
DeepSweep: An Evaluation Framework for Mitigating DNN Backdoor Attacks using Data Augmentation
by: Qiu, Han, et al.
Published: (2020)
by: Qiu, Han, et al.
Published: (2020)
Attack by Unlearning: Unlearning-Induced Adversarial Attacks on Graph Neural Networks
by: Zhang, Jiahao, et al.
Published: (2026)
by: Zhang, Jiahao, et al.
Published: (2026)
Are You Using Reliable Graph Prompts? Trojan Prompt Attacks on Graph Neural Networks
by: Lin, Minhua, et al.
Published: (2024)
by: Lin, Minhua, et al.
Published: (2024)
Backdoor Attacks against Hybrid Classical-Quantum Neural Networks
by: Guo, Ji, et al.
Published: (2024)
by: Guo, Ji, et al.
Published: (2024)
Gradient Shaping: Enhancing Backdoor Attack Against Reverse Engineering
by: Zhu, Rui, et al.
Published: (2023)
by: Zhu, Rui, et al.
Published: (2023)
Link Stealing Attacks Against Inductive Graph Neural Networks
by: Wu, Yixin, et al.
Published: (2024)
by: Wu, Yixin, et al.
Published: (2024)
Countering Backdoor Attacks in Image Recognition: A Survey and Evaluation of Mitigation Strategies
by: Dunnett, Kealan, et al.
Published: (2024)
by: Dunnett, Kealan, et al.
Published: (2024)
Revisiting Edge Perturbation for Graph Neural Network in Graph Data Augmentation and Attack
by: Liu, Xin, et al.
Published: (2024)
by: Liu, Xin, et al.
Published: (2024)
Few Edges Are Enough: Few-Shot Network Attack Detection with Graph Neural Networks
by: Bilot, Tristan, et al.
Published: (2025)
by: Bilot, Tristan, et al.
Published: (2025)
Memory Backdoor Attacks on Neural Networks
by: Luzon, Eden, et al.
Published: (2024)
by: Luzon, Eden, et al.
Published: (2024)
DisDet: Exploring Detectability of Backdoor Attack on Diffusion Models
by: Sui, Yang, et al.
Published: (2024)
by: Sui, Yang, et al.
Published: (2024)
Krait: A Backdoor Attack Against Graph Prompt Tuning
by: Song, Ying, et al.
Published: (2024)
by: Song, Ying, et al.
Published: (2024)
Cross-Paradigm Graph Backdoor Attacks with Promptable Subgraph Triggers
by: Liu, Dongyi, et al.
Published: (2025)
by: Liu, Dongyi, et al.
Published: (2025)
ICLShield: Exploring and Mitigating In-Context Learning Backdoor Attacks
by: Ren, Zhiyao, et al.
Published: (2025)
by: Ren, Zhiyao, et al.
Published: (2025)
Mitigating the Backdoor Effect for Multi-Task Model Merging via Safety-Aware Subspace
by: Yang, Jinluan, et al.
Published: (2024)
by: Yang, Jinluan, et al.
Published: (2024)
Safeguarding Graph Neural Networks against Topology Inference Attacks
by: Fu, Jie, et al.
Published: (2025)
by: Fu, Jie, et al.
Published: (2025)
Detecting Backdoor Attacks via Similarity in Semantic Communication Systems
by: Wei, Ziyang, et al.
Published: (2025)
by: Wei, Ziyang, et al.
Published: (2025)
Similar Items
-
BDPFL: Backdoor Defense for Personalized Federated Learning via Explainable Distillation
by: Zhu, Chengcheng, et al.
Published: (2025) -
"No Matter What You Do": Purifying GNN Models via Backdoor Unlearning
by: Zhang, Jiale, et al.
Published: (2024) -
Fine-tuning is Not Fine: Mitigating Backdoor Attacks in GNNs with Limited Clean Data
by: Zhang, Jiale, et al.
Published: (2025) -
Infighting in the Dark: Multi-Label Backdoor Attack in Federated Learning
by: Li, Ye, et al.
Published: (2024) -
Awakening the Hydra: Stabilizing Multi-Concept Backdoor Injection in Text-to-Image Diffusion Models
by: Wang, Kai, et al.
Published: (2026)