Abstract
Many people draw close parallels between malware propagating through a network and an epidemic spreading through a population. Epidemics are often modeled by a Susceptible-Infected-Recovered (SIR) model, in which a similar system of equations can model the spread of a virus through a computer network, and can be simplified when making assumptions about the network itself and its fixed number of nodes and edges. In this instance, malware propagating in a network also should reflect the network it is propagating through, in which the dynamical system will factor in the nodes of the network and their properties. The system itself does not behave too differently from the original SIR model, and there are several mathematical techniques applied to the model, both towards the dynamical system and the graph, that can be replicated through practical methods of how to configure secure computers and networks.
Faculty Advisor/Mentor
Chris Shenefiel
Document Type
Paper
Disciplines
Cybersecurity | Discrete Mathematics and Combinatorics | Dynamic Systems | Information Security | Ordinary Differential Equations and Applied Dynamics | OS and Networks
DOI
10.25776/2dzk-hr66
Publication Date
11-18-2024
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Included in
Cybersecurity Commons, Discrete Mathematics and Combinatorics Commons, Dynamic Systems Commons, Information Security Commons, Ordinary Differential Equations and Applied Dynamics Commons, OS and Networks Commons
A Dynamical Systems Approach for Modeling Malware Propagating Through a Network and Potential Solutions Towards Mitigating Spread
Many people draw close parallels between malware propagating through a network and an epidemic spreading through a population. Epidemics are often modeled by a Susceptible-Infected-Recovered (SIR) model, in which a similar system of equations can model the spread of a virus through a computer network, and can be simplified when making assumptions about the network itself and its fixed number of nodes and edges. In this instance, malware propagating in a network also should reflect the network it is propagating through, in which the dynamical system will factor in the nodes of the network and their properties. The system itself does not behave too differently from the original SIR model, and there are several mathematical techniques applied to the model, both towards the dynamical system and the graph, that can be replicated through practical methods of how to configure secure computers and networks.