Cybercrime And Policy Insights Based on Time-Series Forecasting and Multiple Regression

Abstract

With the rapid development of global information technology and the internet, cybercrime has become increasingly rampant, posing severe threats to the economy, society, and national security of various countries. This study aims to construct mathematical models to analyze the global distribution and influencing factors of cybercrime and evaluate the effectiveness of national cybersecurity policies. We utilized data visualization techniques to illustrate the frequency of cybercrime and its economic impact across countries. Additionally, a time-series forecasting model predicts a steady rise in cybercrime frequency over the next three years(2023-2025), underscoring the importance of continuously enhancing cybersecurity policies. Moreover, a  decision tree model identified internet penetration and per capita GDP as the most crucial statistical variables in explaining variations in cybercrime rates.