I-GCN: Robust Graph Convolutional Network via Influence Mechanism

Understand

Deep learning models for graphs, especially Graph Convolutional Networks (GCNs), have achieved remarkable performance in the task of semi-supervised node classification.

• However, recent studies show that GCNs suffer from adversarial perturbations.
• Such vulnerability to adversarial attacks significantly decreases the stability of GCNs when being applied to security-critical applications.
• Defense methods such as preprocessing, attention mechanism and adversarial training have been discussed by various studies.