Evaluation of International Cybersecurity Policy Effectiveness and Pathway Optimization Based on PCA-Entropy Weight Method

With the rapid development of the digital era, the widespread adoption of the internet has been accompanied by a surge in cybersecurity threats. This study proposes a practical theoretical framework supported by data-driven analysis to enhance national cybersecurity governance.Task 1: Utilizing datasets from ITU, INTERPOL, and VCDB, preprocessed data (with outliers removed) were visualized through heatmaps to analyze the global distribution of cyber threats. Clustered bar charts and stacked histograms further dissected regional variations in cybersecurity incident success rates, prevention rates, prosecution rates, and reporting rates. Results reveal that the distribution of cyber threats correlates with a nation’s economic development level and cybersecurity infrastructure robustness.Task 2: The Global Cybersecurity Index (GCI) was employed to evaluate national cybersecurity capabilities. Missing values in GCI’s five pillars were addressed via Lagrangian interpolation. Principal Component Analysis (PCA) identified six countries with the highest contribution rates, while the entropy weight method optimized the pillars into two core dimensions: collaboration and technology. Incorporating policy time lag effects, this framework pinpointed effective policies for mitigating cybersecurity incidents.Task 3: A multivariate linear regression model quantified the impact of demographic factors (e.g., internet penetration rate and education level) on cyber threat distribution. Finally, a neural network-based multivariate time series model predicted the theoretical impact of policy interventions on threat dynamics, complemented by sensitivity analysis to objectively assess the framework’s strengths and limitations.