LAUSR

Scalable attack on graph data by injecting vicious nodes

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1 Published in 2020 at "Data Mining and Knowledge Discovery"

DOI: 10.1007/s10618-020-00696-7

Abstract: Recent studies have shown that graph convolution networks (GCNs) are vulnerable to carefully designed attacks, which aim to cause misclassification of a specific node on the graph with unnoticeable perturbations. However, a vast majority of… read more here.

Keywords: attack; injecting vicious; attack graph; scalable attack ... See more keywords