Membership inference attack on graph neural networks
Graph Neural Networks (GNNs), which generalize traditional deep neural networks on
graph data, have achieved state-of-the-art performance on several graph analytical tasks …
graph data, have achieved state-of-the-art performance on several graph analytical tasks …
[PDF][PDF] Membership Inference Attack on Graph Neural Networks
IE Olatunji, W Nejdl, M Khosla - 2021 - academia.edu
ABSTRACT Graph Neural Networks (GNNs), which generalize traditional deep neural
networks or graph data, have achieved state of the art performance on several graph …
networks or graph data, have achieved state of the art performance on several graph …
Membership Inference Attack on Graph Neural Networks
IE Olatunji, W Nejdl, M Khosla - arXiv preprint arXiv:2101.06570, 2021 - arxiv.org
Graph Neural Networks (GNNs), which generalize traditional deep neural networks on
graph data, have achieved state-of-the-art performance on several graph analytical tasks …
graph data, have achieved state-of-the-art performance on several graph analytical tasks …
Membership Inference Attack on Graph Neural Networks
IE Olatunji, W Nejdl, M Khosla - … on Trust, Privacy and Security in …, 2021 - computer.org
Abstract Graph Neural Networks (GNNs), which generalize traditional deep neural networks
on graph data, have achieved state-of-the-art performance on several graph analytical tasks …
on graph data, have achieved state-of-the-art performance on several graph analytical tasks …
[引用][C] Membership Inference Attack on Graph Neural Networks
IE Olatunji, W Nejdl, M Khosla - … on Trust, Privacy and Security in …, 2021 - research.tudelft.nl
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[PDF][PDF] Membership Inference Attack on Graph Neural Networks
IE Olatunji, W Nejdl, M Khosla - researchgate.net
Graph Neural Networks (GNNs), which generalize traditional deep neural networks on
graph data, have achieved state-of-the-art performance on several graph analytical tasks …
graph data, have achieved state-of-the-art performance on several graph analytical tasks …
Membership Inference Attack on Graph Neural Networks
IE Olatunji, W Nejdl, M Khosla - arXiv e-prints, 2021 - ui.adsabs.harvard.edu
Abstract Graph Neural Networks (GNNs), which generalize traditional deep neural networks
on graph data, have achieved state-of-the-art performance on several graph analytical tasks …
on graph data, have achieved state-of-the-art performance on several graph analytical tasks …
[PDF][PDF] MEMBERSHIP INFERENCE ATTACK ON GRAPH NEURAL NETWORKS
IE Olatunji, W Nejdl, M Khosla - dp-ml.github.io
We focus on how trained Graph Neural Network (GNN) models could leak information about
the member nodes that they were trained on. We introduce two realistic inductive settings for …
the member nodes that they were trained on. We introduce two realistic inductive settings for …