Web: http://arxiv.org/abs/2103.16329

Jan. 10, 2022, 2:20 a.m. | Wai Weng Lo, Siamak Layeghy, Mohanad Sarhan, Marcus Gallagher, Marius Portmann

cs.CR updates on arXiv.org arxiv.org

This paper presents a new Network Intrusion Detection System (NIDS) based on
Graph Neural Networks (GNNs). GNNs are a relatively new sub-field of deep
neural networks, which can leverage the inherent structure of graph-based data.
Training and evaluation data for NIDSs are typically represented as flow
records, which can naturally be represented in a graph format. In this paper,
we propose E-GraphSAGE, a GNN approach that allows capturing both the edge
features of a graph as well as the topological …

detection intrusion detection iot network neural network system

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