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The Frontiers of Society, Science and Technology, 2025, 7(7); doi: 10.25236/FSST.2025.070701.

Research on the Effectiveness of Network Security Policies Based on Interrupt Time Series and Natural Language Processing

Author(s)

Shuyuan You, Yichen Zhong, Jiajin Du, Guorui Zhao

Corresponding Author:
Guorui Zhao
Affiliation(s)

School of Computer Science and Engineering, Guangdong Ocean University, Yangjiang, China

Abstract

With the evolution of The Times, cybercrime has also spread rapidly around the world. An in-depth exploration of the effectiveness of cybersecurity policies is of great significance for all countries to formulate scientific prevention and control strategies. Most existing studies have conducted qualitative research from the perspectives of transnational governance and legal frameworks, lacking quantitative research and text mining on global policies. Given that traditional time series prediction is vulnerable to trend interference, this study selected the interrupted time series model. By analyzing the natural trends before and after policy intervention, the inhibitory effects of 145 policies in 137 countries on cybercrime were quantified. Subsequently, NLP technology was used to conduct TF-IDF modeling and word cloud analysis on the policy text, and core factors such as "international cooperation" were extracted. Research has found that effective policies usually focus on cross-regional collaboration, technological innovation and institutional construction, etc., and the differences in policy effects are closely related to the implementation background and the intensity of enforcement. Based on the above results, this paper constructs a data-driven policy analysis framework for cyber security, emphasizing the equal importance of dynamic assessment and multi-dimensional governance. It suggests establishing a continuous assessment mechanism, strengthening global collaboration, and coordinating technical means and institutional guarantees.

Keywords

Cybersecurity Policy, Policy Effectiveness, Interrupt Time Series Analysis, Natural Language Processing, TF-IDF Model

Cite This Paper

Shuyuan You, Yichen Zhong, Jiajin Du, Guorui Zhao. Research on the Effectiveness of Network Security Policies Based on Interrupt Time Series and Natural Language Processing. The Frontiers of Society, Science and Technology (2025), Vol. 7, Issue 7: 1-8. https://doi.org/10.25236/FSST.2025.070701.

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