Model Stealing Attacks Against Inductive Graph Neural Networks

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 build powerful applications. In particular, the inductive GNNs, which can generalize to unseen data, become mainstream in th...

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Bibliographic Details

Published in:	Proceedings - IEEE Symposium on Security and Privacy pp. 1175 - 1192
Main Authors:	Shen, Yun, He, Xinlei, Han, Yufei, Zhang, Yang
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.05.2022
Subjects:	Benchmark testing Computational modeling Data models Graph neural networks Machine learning Privacy Reconstruction algorithms
ISSN:	2375-1207
Online Access:	Get full text
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