GAIM: Attacking Graph Neural Networks via Adversarial Influence Maximization
Fuente:
arXiv
Saved in:
| Main Authors: | Yang, Xiaodong, Li, Xiaoting, Chen, Huiyuan, Cai, Yiwei |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Enhancing Distribution and Label Consistency for Graph Out-of-Distribution Generalization
by: Wang, Song, et al.
Published: (2025)
by: Wang, Song, et al.
Published: (2025)
GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks
by: Cui, Canyixing, et al.
Published: (2026)
by: Cui, Canyixing, et al.
Published: (2026)
Unifying Adversarial Perturbation for Graph Neural Networks
by: Yang, Jinluan, et al.
Published: (2025)
by: Yang, Jinluan, et al.
Published: (2025)
Influence Maximization via Graph Neural Bandits
by: Feng, Yuting, et al.
Published: (2024)
by: Feng, Yuting, et al.
Published: (2024)
Online Adversarial Knowledge Distillation for Graph Neural Networks
by: Wang, Can, et al.
Published: (2021)
by: Wang, Can, et al.
Published: (2021)
Gradient Inversion Attack on Graph Neural Networks
by: Sinha, Divya Anand, et al.
Published: (2024)
by: Sinha, Divya Anand, et al.
Published: (2024)
Factor Graph-based Interpretable Neural Networks
by: Li, Yicong, et al.
Published: (2025)
by: Li, Yicong, et al.
Published: (2025)
On the Robustness of Bayesian Neural Networks to Adversarial Attacks
by: Bortolussi, Luca, et al.
Published: (2022)
by: Bortolussi, Luca, et al.
Published: (2022)
Adversarial Attacks to Latent Representations of Distributed Neural Networks in Split Computing
by: Zhang, Milin, et al.
Published: (2023)
by: Zhang, Milin, et al.
Published: (2023)
Optimal Transport-Guided Adversarial Attacks on Graph Neural Network-Based Bot Detection
by: Mukherjee, Kunal, et al.
Published: (2026)
by: Mukherjee, Kunal, et al.
Published: (2026)
Adversarial Attacks on Hyperbolic Networks
by: van Spengler, Max, et al.
Published: (2024)
by: van Spengler, Max, et al.
Published: (2024)
Exploring Consistency in Graph Representations:from Graph Kernels to Graph Neural Networks
by: Liu, Xuyuan, et al.
Published: (2024)
by: Liu, Xuyuan, et al.
Published: (2024)
ADEdgeDrop: Adversarial Edge Dropping for Robust Graph Neural Networks
by: Chen, Zhaoliang, et al.
Published: (2024)
by: Chen, Zhaoliang, et al.
Published: (2024)
Backdoor Attack on Vertical Federated Graph Neural Network Learning
by: Yang, Jirui, et al.
Published: (2024)
by: Yang, Jirui, et al.
Published: (2024)
Black-box Gradient Attack on Graph Neural Networks: Deeper Insights in Graph-based Attack and Defense
by: Zhan, Haoxi, et al.
Published: (2021)
by: Zhan, Haoxi, et al.
Published: (2021)
ReEval: Automatic Hallucination Evaluation for Retrieval-Augmented Large Language Models via Transferable Adversarial Attacks
by: Yu, Xiaodong, et al.
Published: (2023)
by: Yu, Xiaodong, et al.
Published: (2023)
AGSOA:Graph Neural Network Targeted Attack Based on Average Gradient and Structure Optimization
by: Chen, Yang, et al.
Published: (2024)
by: Chen, Yang, et al.
Published: (2024)
LiSA: Leveraging Link Recommender to Attack Graph Neural Networks via Subgraph Injection
by: Zhang, Wenlun, et al.
Published: (2025)
by: Zhang, Wenlun, et al.
Published: (2025)
Combinatorial Optimization with Automated Graph Neural Networks
by: Liu, Yang, et al.
Published: (2024)
by: Liu, Yang, et al.
Published: (2024)
Hide and Find: A Distributed Adversarial Attack on Federated Graph Learning
by: Liu, Jinshan, et al.
Published: (2026)
by: Liu, Jinshan, et al.
Published: (2026)
Towards Interpretable Adversarial Examples via Sparse Adversarial Attack
by: Lin, Fudong, et al.
Published: (2025)
by: Lin, Fudong, et al.
Published: (2025)
Graph-Level Label-Only Membership Inference Attack against Graph Neural Networks
by: Dai, Jiazhu, et al.
Published: (2025)
by: Dai, Jiazhu, et al.
Published: (2025)
Untargeted Adversarial Attack on Knowledge Graph Embeddings
by: Zhao, Tianzhe, et al.
Published: (2024)
by: Zhao, Tianzhe, et al.
Published: (2024)
Robust Graph Learning Against Adversarial Evasion Attacks via Prior-Free Diffusion-Based Structure Purification
by: Luo, Jiayi, et al.
Published: (2025)
by: Luo, Jiayi, et al.
Published: (2025)
LGAN: An Efficient High-Order Graph Neural Network via the Line Graph Aggregation
by: Du, Lin, et al.
Published: (2025)
by: Du, Lin, et al.
Published: (2025)
Unlearning Inversion Attacks for Graph Neural Networks
by: Zhang, Jiahao, et al.
Published: (2025)
by: Zhang, Jiahao, et al.
Published: (2025)
Universal Prompt Tuning for Graph Neural Networks
by: Fang, Taoran, et al.
Published: (2022)
by: Fang, Taoran, et al.
Published: (2022)
Quantifying the Noise of Structural Perturbations on Graph Adversarial Attacks
by: Fang, Junyuan, et al.
Published: (2025)
by: Fang, Junyuan, et al.
Published: (2025)
Adversarial Robustness Unhardening via Backdoor Attacks in Federated Learning
by: Kim, Taejin, et al.
Published: (2023)
by: Kim, Taejin, et al.
Published: (2023)
Influence Functions for Edge Edits in Non-Convex Graph Neural Networks
by: Heo, Jaeseung, et al.
Published: (2025)
by: Heo, Jaeseung, et al.
Published: (2025)
Decision-focused Graph Neural Networks for Combinatorial Optimization
by: Liu, Yang, et al.
Published: (2024)
by: Liu, Yang, et al.
Published: (2024)
QuadEnhancer: Leveraging Quadratic Transformations to Enhance Deep Neural Networks
by: Chen, Qian, et al.
Published: (2025)
by: Chen, Qian, et al.
Published: (2025)
On Measuring Unnoticeability of Graph Adversarial Attacks: Observations, New Measure, and Applications
by: Jo, Hyeonsoo, et al.
Published: (2025)
by: Jo, Hyeonsoo, et al.
Published: (2025)
AnyAttack: Towards Large-scale Self-supervised Adversarial Attacks on Vision-language Models
by: Zhang, Jiaming, et al.
Published: (2024)
by: Zhang, Jiaming, et al.
Published: (2024)
GraphTOP: Graph Topology-Oriented Prompting for Graph Neural Networks
by: Fu, Xingbo, et al.
Published: (2025)
by: Fu, Xingbo, et al.
Published: (2025)
Rethinking the Intermediate Features in Adversarial Attacks: Misleading Robotic Models via Adversarial Distillation
by: Zhao, Ke, et al.
Published: (2024)
by: Zhao, Ke, et al.
Published: (2024)
Poisoning the Inner Prediction Logic of Graph Neural Networks for Clean-Label Backdoor Attacks
by: Zhang, Yuxiang, et al.
Published: (2026)
by: Zhang, Yuxiang, et al.
Published: (2026)
Accurate and Scalable Graph Neural Networks via Message Invariance
by: Shi, Zhihao, et al.
Published: (2025)
by: Shi, Zhihao, et al.
Published: (2025)
PAGE: Parametric Generative Explainer for Graph Neural Network
by: Qiu, Yang, et al.
Published: (2024)
by: Qiu, Yang, et al.
Published: (2024)
IoT-based Android Malware Detection Using Graph Neural Network With Adversarial Defense
by: Yumlembam, Rahul, et al.
Published: (2025)
by: Yumlembam, Rahul, et al.
Published: (2025)
Similar Items
-
Enhancing Distribution and Label Consistency for Graph Out-of-Distribution Generalization
by: Wang, Song, et al.
Published: (2025) -
GJDNet: Robust Graph Neural Networks via Joint Disentangled Learning Against Adversarial Attacks
by: Cui, Canyixing, et al.
Published: (2026) -
Unifying Adversarial Perturbation for Graph Neural Networks
by: Yang, Jinluan, et al.
Published: (2025) -
Influence Maximization via Graph Neural Bandits
by: Feng, Yuting, et al.
Published: (2024) -
Online Adversarial Knowledge Distillation for Graph Neural Networks
by: Wang, Can, et al.
Published: (2021)