Adversarial attack and defense on graph neural networks: a survey

Abstract

For the numerous existing adversarial attack and defense methods on GNN, the main adversarial attack and defense algorithms of GNN were reviewed comprehensively, as well as robustness analysis techniques. Besides, the commonly used benchmark datasets and evaluation metrics in the security research of GNN were introduced. In conclusion, some insights on the future research direction of adversarial attacks and the trend of development were put forward.

Keywords

• graph neural networks
• adversarial attack
• defense algorithms
• robustness analysis