An explanation-based detector using seven novel metrics derived from GNN explanations identifies backdoored graphs with high performance on benchmark datasets against multiple attack models.
Edge generator fgen trains iteratively, in multiple rounds, over a subset of clean graphs D designated for attack (denoted as DB) (line 8-line 19)
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Identifying Backdoored Graphs in Graph Neural Network Training: An Explanation-Based Approach with Novel Metrics
An explanation-based detector using seven novel metrics derived from GNN explanations identifies backdoored graphs with high performance on benchmark datasets against multiple attack models.