Dynamic Malware Mitigation Strategies for IoT Networks: A Mathematical Epidemiology Approach

Roberto Casado-Vara (), Marcos Severt, Antonio Díaz-Longueira, Ángel Martín del Rey and Jose Luis Calvo-Rolle
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Roberto Casado-Vara: Grupo de Inteligencia Computacional Aplicada (GICAP), Departamento de Matemáticas y Computación, Escuela Politécnica Superior, Universidad de Burgos, Av. Cantabria s/n, 09006 Burgos, Spain
Marcos Severt: Department of Computer Sciences, Universidad de Salamanca, 37007 Salamanca, Spain
Antonio Díaz-Longueira: Department of Industrial Engineering, CTC, CITIC, University of A Coruña, Rúa Mendizábal, s/n, 15403 Ferrol, Spain
Ángel Martín del Rey: Department of Applied Mathematics, Universidad de Salamanca, 37007 Salamanca, Spain
Jose Luis Calvo-Rolle: Department of Industrial Engineering, CTC, CITIC, University of A Coruña, Rúa Mendizábal, s/n, 15403 Ferrol, Spain

Mathematics, 2024, vol. 12, issue 2, 1-24

Abstract: With the progress and evolution of the IoT, which has resulted in a rise in both the number of devices and their applications, there is a growing number of malware attacks with higher complexity. Countering the spread of malware in IoT networks is a vital aspect of cybersecurity, where mathematical modeling has proven to be a potent tool. In this study, we suggest an approach to enhance IoT security by installing security updates on IoT nodes. The proposed method employs a physically informed neural network to estimate parameters related to malware propagation. A numerical case study is conducted to evaluate the effectiveness of the mitigation strategy, and novel metrics are presented to test its efficacy. The findings suggest that the mitigation tactic involving the selection of nodes based on network characteristics is more effective than random node selection.

Keywords: malware propagation; individual-based SIR model; PINN; Inverse problem; malware mitigation; IoT networks (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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