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cs.CR2021
Model Stealing Attacks Against Inductive Graph Neural Networks
Yun Shen, Xinlei He, Yufei Han +1
Many real-world data come in the form of graphs. Graph neural networks (GNNs), a new family of machine learning (ML) models, have been proposed to fully leverage graph data to buil…
cs.LG2021
Attack Transferability Characterization for Adversarially Robust Multi-label Classification
Zhuo Yang, Yufei Han, Xiangliang Zhang
Despite of the pervasive existence of multi-label evasion attack, it is an open yet essential problem to characterize the origin of the adversarial vulnerability of a multi-label l…