A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability. (arXiv:2204.08570v1 [cs.LG])

Graph Neural Networks (GNNs) have made rapid developments in the recent
years. Due to their great ability in modeling graph-structured data, GNNs are
vastly used in various applications, including high-stakes scenarios such as
financial analysis, traffic predictions, and drug discovery. Despite their
great potential in benefiting humans in the real world, recent study shows that
GNNs can leak private information, are vulnerable to adversarial attacks, can
inherit and magnify societal bias from training data and lack interpretability,
which have risk …

fairness lg networks privacy survey