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XG-BoT: An Explainable Deep Graph Neural Network for Botnet Detection and Forensics. (arXiv:2207.09088v4 [cs.CR] UPDATED)
Nov. 28, 2022, 2:10 a.m. | Wai Weng Lo, Gayan K. Kulatilleke, Mohanad Sarhan, Siamak Layeghy, Marius Portmann
cs.CR updates on arXiv.org arxiv.org
In this paper, we propose XG-BoT, an explainable deep graph neural network
model, for botnet node detection. The proposed model is composed of a botnet
detector and an explainer for automatic forensics. The XG-BoT detector can
effectively detect malicious botnet nodes under large-scale networks.
Specifically, it utilises a grouped reversible residual connection with a graph
isomorphism network to learn expressive node representations from the botnet
communication graphs. The explainer, which is based on the GNNExplainer and
saliency map in XG-BoT, …
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