Exploring the impact of how criminals interact with cyber-networks—a mathematical modeling approach

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dc.contributor.authorChikore, Tichaona
dc.contributor.authorNyirenda-Kayuni, Mwawi
dc.contributor.authorChukwudum, Queensley C.
dc.contributor.authorChazuka, Zviiteyi
dc.contributor.authorMwaonanji, John
dc.contributor.authorNdlovu, Meshach
dc.contributor.authorZhangazha, Moster
dc.contributor.authorMhlabane, Fezile
dc.contributor.authorOsman, Shaibu
dc.contributor.authorNyabadza, Farai
dc.contributor.authorWhite, K. A. Jane
dc.contributor.authorShang, Yilun
dc.date.accessioned2024-03-07T09:25:36Z
dc.date.available2024-03-07T09:25:36Z
dc.date.issued2024-01-11
dc.description.abstractThere is a growing interest in using mathematical models to understand crime dynamics, crime pre-vention, and detection. The past decade has experienced a relative reduction in conventional crimes, but this has been replaced by significant increases in cybercrime. In this paper, we use deterministic modelling to describe the spread of cybercrime across a cyber-network by describing the hetero-geneity of interactions between individuals using a nonlinear interaction between individuals in the network, and we allow criminals to operate either internally or externally to the cyber-network. We are able to determine the impact of the location of the criminal relative to the cyber-network which is being attacked. The model structure incorporates key elements of a social network structure thereby allowing for limited rates of victimisation. Both model structure and our observations are novel and provide a new contribution to the theoretical discussion of cybercrime dynamics, offering potential avenues to consider control strategies. Using steady-state analysis and extensive numerical simu-lations, we find that the location of criminals relative to the network does not impact the system qualitatively, although there are quantitative differences. Cyber-networks that are more clustered are likely to experience greater levels of cybercrime, but there is also a saturation effect that limits the level of victimisation as the number of criminals attempting to undertake crimes on given network increases. We discuss model limitations and describe how the model might be used with datasets to translate the theoretical findings into a useful tool in the fight to detect and eradicate cybercrime activity.en_US
dc.description.sponsorshipThe work was supported by the UK Research and Innovation [EP/T00410X/1].en_US
dc.identifier.citationTichaona Chikore, Mwawi Nyirenda-Kayuni, Queensley C. Chukwudum, Zviiteyi Chazuka, John Mwaonanji, Meshach Ndlovu, Moster Zhangazha, Fezile Mhlabane, Shaibu Osman, Farai Nyabadza & K.A.jane White | Yilun Shang (Reviewing editor:) (2024) Exploring the impact of how criminals interact with cyber-networks—a mathematical modeling approach, Research in Mathematics, 11:1, DOI: 10.1080/27684830.2023.2295059en_US
dc.identifier.urihttps://doi.org/10.1080/27684830.2023.2295059
dc.identifier.urihttp://ir.gsu.ac.zw:8080/xmlui/handle/123456789/343
dc.language.isoenen_US
dc.publisherTaylor & Francisen_US
dc.relation.ispartofseriesResearch in Mathematics;Volume 11, 2024 - Issue 1
dc.subjectmathematical model; cybercrime; victims; criminals; steady-state analysis.en_US
dc.titleExploring the impact of how criminals interact with cyber-networks—a mathematical modeling approachen_US
dc.title.alternativeApplied & Interdisciplinary Mathematicsen_US
dc.typeArticleen_US

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