A Practical Botnet Traffic Detection System using GNN

Zhang, Bonan, Li, Jingjin, Chen, Chao, Lee, Kymungi, and Lee, Ickjai (2022) A Practical Botnet Traffic Detection System using GNN. In: Lecture Notes in Computer Science (13172) pp. 66-78. From: CSS 2021: Cyberspace Safety and Security, 9-11 November 2021, Virtual. (In Press)

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Abstract

Botnet attacks have now become a major source of cyber-attacks. How to detect botnet traffic quickly and efficiently is a current problem for most enterprises. To solve this, we have built a plug-and-play botnet detection system using graph neural network algorithms. The system performs very well in detecting botnets of different structures. The system is also made with a graphical interface to visualise which nodes are at risk of botnets. The system is also very efficient in identifying botnet traffic.

Item ID: 73112
Item Type: Conference Item (Research - E1)
ISBN: 978-3-030-94029-4
Copyright Information: © 2022 Springer Nature Switzerland AG
Date Deposited: 12 Sep 2022 02:40
FoR Codes: 46 INFORMATION AND COMPUTING SCIENCES > 4604 Cybersecurity and privacy > 460403 Data security and protection @ 100%
SEO Codes: 22 INFORMATION AND COMMUNICATION SERVICES > 2204 Information systems, technologies and services > 220405 Cybersecurity @ 100%
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