Cybersecurity Assessment Based on Dynamic Panel Data Modeling

Abstract

The purpose of this paper is to assess the state of cybersecurity by constructing a dynamic panel data model. First, the study analyzes the characteristics of the global distribution of cybercrime and finds that its concentration area and related factors have a significant impact on its pattern, and that the success rate of cybercrime is related to many aspects. Second, given that cybercrime is affected by the dynamics of multiple factors, the study introduces hidden indicators such as law and technology, and after processing missing values and standardized data, the study combines the dynamic panel data model with the SIR infectious disease model to assess the effect of policies, and the results show that capacity building has the best effect on reducing cybercrime. Finally, the accuracy of the model was verified by sensitivity analysis. This study provides a theoretical basis for countries to formulate cybercrime prevention and control policies.