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XG-BoT: An Explainable Deep Graph Neural Network for Botnet Detection and Forensics. (arXiv:2207.09088v3 [cs.CR] UPDATED)
Nov. 14, 2022, 2:20 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 mainly 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 utilizes a grouped reversible residual connection with a graph
isomorphism network to learn expressive node representations from the botnet
communication graphs. The explainer in XG-BoT can perform automatic network
forensics by highlighting suspicious …
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