Black-Box Adversarial Attacks on Graph Neural Networks with Limited Node Access

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Other Links: arxiv.org

Abstract:

We study the black-box attacks on graph neural networks (GNNs) under a novel and realistic constraint: attackers have access to only a subset of nodes in the network, and they can only attack a small number of them. A node selection step is essential under this setup. We demonstrate that the structural inductive biases of GNN models can...More

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