K-means Optimized Network Security Management in the Internet Context

Authors

  • Cuijuan Liu School of Information and Engineering, Hebei GEO University, Shijiazhuang, 050031, China
  • Liya Song School of Information and Engineering, Hebei GEO University, Shijiazhuang, 050031, China

DOI:

https://doi.org/10.13052/jcsm2245-1439.13611

Keywords:

Internet, K-means optimization, Network security management system, Three-way decision

Abstract

The rapid development of the Internet has had a broad and profound impact on humanity, making information acquisition and dissemination more convenient. It has also brought significant opportunities and benefits to business and the economy. However, there are some issues, such as personal factors and data security concerns. In order to solve the above problems, the K-means algorithm is optimized from the perspectives of K-value validity index, feature weighting and three-branch decision making. First, the optimal clustering results are determined according to K-value validity index, and the influence of different dimensional features on clustering is considered for feature weighting, and the uncertain objects in the three-branch decision deadlock class are divided into the boundary domain. The delay decision of the boundary domain data is carried out, and the K-means clustering optimization algorithm is improved by combining the above three aspects, and the intelligent network security management system is developed on this basis. The results showed that the K-means optimization algorithm achieved the highest average accuracy rate, adjusted Morandi index, and adjusted mutual information across various datasets, with values of 96.01%, 0.866, and 0.869, respectively. In practical network attack scenarios, the K-means optimization algorithm attained an attack threat recognition accuracy of 94.38%. Under unknown network attack types, its detection rate and false alarm rate were 94.63% and 1.32%, respectively. Surveys conducted post-implementation of the intelligent network security management system indicated that over 90% of users were satisfied with their experience of the system. In summary, the proposed method accurately identifies potential network threats in network data, fulfilling performance requirements for network security management systems and ensuring the security of network resources.

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Author Biographies

Cuijuan Liu, School of Information and Engineering, Hebei GEO University, Shijiazhuang, 050031, China

Cuijuan Liu obtained her Master’s degree in Computer Application Technology from North China Electric Power University (Baoding) in 2006. Currently, she serves as the Deputy Director of the Computer Department at the School of Information Engineering, Hebei GEO University. Her areas of interest include data mining, machine learning, network security, innovative thinking, and more.

Liya Song, School of Information and Engineering, Hebei GEO University, Shijiazhuang, 050031, China

Liya Song, graduated from Hebei University of Technology in 2006, majoring in test measurement technology and instruments, with a postgraduate degree. She later worked in the Electronic Communication Experimental Center of Hebei GEO University. She has published articles based on Optical Opbidimetry, and her main research interests are photoelectric detection, image processing and information processing.

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Published

2024-11-23

How to Cite

1.
Liu C, Song L. K-means Optimized Network Security Management in the Internet Context. JCSANDM [Internet]. 2024 Nov. 23 [cited 2024 Nov. 24];13(6):1467–1490. Available from: https://journals.riverpublishers.com/index.php/JCSANDM/article/view/25867

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Articles