A survey of adversarial learning on graphs
L Chen, J Li, J Peng, T ** Against Adversarial Attacks on Graph Neural Networks
Graph Neural Networks (GNNs) have achieved impressive performance in many tasks on
graph data. Recent studies show that they are vulnerable to adversarial attacks. Deliberate …
graph data. Recent studies show that they are vulnerable to adversarial attacks. Deliberate …
Explainability-based adversarial attack on graphs through edge perturbation
Despite the success of graph neural networks (GNNs) in various domains, they exhibit
susceptibility to adversarial attacks. Understanding these vulnerabilities is crucial for …
susceptibility to adversarial attacks. Understanding these vulnerabilities is crucial for …
Detecting Targets of Graph Adversarial Attacks With Edge and Feature Perturbations
B Lee, JY Jhang, LY Yeh, MY Chang… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
Graph neural networks (GNNs) enable many novel applications and achieve excellent
performance. However, their performance may be significantly degraded by the graph …
performance. However, their performance may be significantly degraded by the graph …