Modelling spatio-temporal progression of cyberattacks in data networks

Awan, Malik Shahzad Kaleem, Knight, Vince ORCID: https://orcid.org/0000-0002-4245-0638, Rana, Omer ORCID: https://orcid.org/0000-0003-3597-2646 and Burnap, Pete ORCID: https://orcid.org/0000-0003-0396-633X 2025. Modelling spatio-temporal progression of cyberattacks in data networks. Presented at: 2025 7th International Conference on Blockchain Computing and Applications (BCCA), Dubrovnic, Croatia, 14-17 October 2025. 2025 7th International Conference on Blockchain Computing and Applications (BCCA). IEEE, pp. 882-888. 10.1109/BCCA66705.2025.11229708

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Abstract

University data networks comprise numerous devices connected to the network on an ad-hoc basis. Measuring the risk of cyberattacks and identifying the most recent modus-operandi of cyber criminals on such networks can be difficult due to the wide range of services and applications running within the network, the multiple vulnerabilities associated with each application, the severity associated with each vulnerability, and the ever-changing attack vector of cyber criminals. We propose a spatiotemporal modelling framework to represent these features, enabling real-time network enumeration and traffic analysis, to produce quantified measures of risk at specific points in time. We validate the approach using data from a University network, with a data collection consisting of 460 K instances representing threats measured over a 144 hour period. Our analysis can be generalise to a variety of other contexts.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Published Online
Status:	Published
Schools:	Schools > Computer Science & Informatics
Publisher:	IEEE
ISBN:	9798331502966
Funders:	EPSRC
Date of First Compliant Deposit:	15 November 2025
Date of Acceptance:	20 September 2025
Last Modified:	17 Nov 2025 11:15
URI:	https://orca.cardiff.ac.uk/id/eprint/182432

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