A Paradigm for Modeling Infectious Diseases : Assessing Malware Spread in Early-Stage Outbreaks
Ginters, Egils (Riga Technology University)
Dumpis, Uga (University of Latvia)
Calvet Liñan, Laura (Universitat Autònoma de Barcelona. Departament de Telecomunicació i Enginyeria de Sistemes)
Piera, Miquel Àngel (Universitat Autònoma de Barcelona. Departament de Telecomunicació i Enginyeria de Sistemes)
Nazemi, Kawa (Darmstadt University of Applied Sciences)
Matvejevs, Andrejs (Riga Technology University)
Ruíz Estrada, Mario Arturo (University of Malaya)

Date:	2025
Abstract:	As digitalization and artificial intelligence advance, cybersecurity threats intensify, making malware-a type of software installed without authorization to harm users-an increasingly urgent concern. Due to malware's social and economic impacts, accurately modeling its spread has become essential. While diverse models exist for malware propagation, their selection tends to be intuitive, often overlooking the unique aspects of digital environments. Key model choices include deterministic vs. stochastic, planar vs. spatial, analytical vs. simulation-based, and compartment-based vs. individual state-tracking models. In this context, our study assesses fundamental infection spread models to determine those most applicable to malware propagation. It is organized in two parts: the first examines principles of deterministic and stochastic infection models, and the second provides a comparative analysis to evaluate model suitability. Key criteria include scalability, robustness, complexity, workload, transparency, and manageability. Using consistent initial conditions, control examples are analyzed through Python-based numerical methods and agent-based simulations in NetLogo. The findings yield practical insights and recommendations, offering valuable guidance for researchers and cybersecurity professionals in applying epidemiological models to malware spread.
Rights:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, la comunicació pública de l'obra i la creació d'obres derivades, fins i tot amb finalitats comercials, sempre i quan es reconegui l'autoria de l'obra original.
Language:	Anglès
Document:	Article ; recerca ; Versió publicada
Subject:	Epidemiological models ; Mathematical modeling ; Malware spread modeling ; Sociotechnical systems ; Simulation
Published in:	Mathematics, Vol. 13, Issue 1 (January 2025) , art. 91, ISSN 2227-7390

DOI: 10.3390/math13010091

35 p, 7.5 MB

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