A Separation Principle for Adversarial Attacks and Defense of Graph Neural Networks

Farid Mafi, Saber Jafarpour, Mohammad Pirani

Adversarial attacks on graph neural networks (GNNs) have been studied as a model-centric optimization problem driven by gradients, learned policies, or meta-learning, with the grap…