OST: an AI enabled one-stop station platform for cyber security incident reporting

Al Rashdi, Alwaleed and Li, Shancang 2025. OST: an AI enabled one-stop station platform for cyber security incident reporting. Presented at: EAI Broadnets 2024, Cardiff, UK, 15 December 2024.

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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 (Paper)
Status:	In Press
Schools:	Schools > Computer Science & Informatics
Date of First Compliant Deposit:	23 May 2025
Last Modified:	12 Aug 2025 11:16
URI:	https://orca.cardiff.ac.uk/id/eprint/177330

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