An integrated graph data privacy attack framework based on graph neural networks in IoT
Xiaoran Zhao,
Changgen Peng,
Hongfa Ding
et al.
Abstract:SummaryKnowledge graphs contain a large amount of entity and relational data, and graph neural networks, as a class of efficient graph representation techniques based on deep learning, excel in knowledge graph modeling. However, previous neural network architectures for the most part only learn node representations and do not fully consider the heterogeneity of data. In this article, we innovatively propose a privacy attack framework based on IoT, PAFI, which is able to classify entities and relations, learn e… Show more
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