Al Rashdi, Alwaleed and Li, Shancang
2026.
OST: An AI enabled one-stop station platform for cyber security incident reporting.
Presented at: EAI Broadnets 2024,
Cardiff, UK,
15 December 2024.
Published in: Li, Shancang, Zhao, Shanshan and Iqbal, Muddesar eds.
Broadband Communications, Networks, and Systems.
Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineerin
, vol.674
Cham, Switzerland:
Springer,
pp. 136-147.
10.1007/978-3-032-14350-1_10
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Abstract
This paper proposes a “One Stop Station” (OST) with an AI-powered “CyberBot” to streamline incident reporting and management. The OST tackles inefficiencies by offering a unified platform that streamlines threat reporting, delivers real-time threat intelligence, and enhances user interaction with an intuitive interface. Leveraging AI like GPT-3.5 and Rasa, the OST automates responses, generates detailed reports, and integrates with existing tools like VirusTotal. This demonstrably improves response speed and accuracy. Testing results show a potential 600% reduction in reporting time. The OST empowers both cyber security professionals and less technical users, reducing workload and enhancing overall incident management. This project highlights the potential of AI in cyber security and positions the OST as a pioneer. It reinforces discussions on leveraging AI to fortify digital defences and integrate AI into daily life.
| Item Type: | Conference or Workshop Item - published (Paper) |
|---|---|
| Date Type: | Published Online |
| Status: | Published |
| Schools: | Schools > Computer Science & Informatics |
| Publisher: | Springer |
| ISBN: | 9783032143495 |
| Date of First Compliant Deposit: | 23 May 2025 |
| Last Modified: | 29 Jan 2026 11:42 |
| URI: | https://orca.cardiff.ac.uk/id/eprint/177330 |
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