A Review of the Application of Big Data Technology in Computer Network Information Security Management

Authors

  • Xiaofei Fang Greentown Technology Industry Service Group Co., Ltd., Hangzhou 310000, Zhejiang, China

Keywords:

Big data technology, Computer network information security, Security management

Abstract

This paper focuses on the application value of big data technology in network information security management, reviewing its core role in transforming security defense paradigms. Leveraging capabilities in massive data processing, high-speed analysis, and intelligent modeling, big data technology offers a new path for building proactive, intelligent, and collaborative network security defense systems. By systematically integrating multi-source heterogeneous security data and employing intelligent analysis methods, it significantly enhances the breadth and depth of threat situational awareness, enabling precise identification, real-time early warning, and efficient handling of security risks.

References

Xu, Haoran. "Sustainability Enhancement in Healthcare Facility Design: Structural and Functional Optimization Based on GCN." (2025).

Jiang, Gaozhe, et al. "Investment Advisory Robotics 2.0: Leveraging Deep Neural Networks for Personalized Financial Guidance." (2025).

Tu, T. (2025). Log2Learn: Intelligent Log Analysis for Real-Time Network Optimization.

Ma, Haowei, et al. "Maternal and cord blood levels of metals and fetal liver function." Environmental Pollution 363 (2024): 125305.

Yang, Wei, and Jincan Duan. "Knowledge Graph Construction for the US Stock Market: A Statistical Learning and Risk Management Approach." Journal of Computer Technology and Applied Mathematics 2.1 (2025): 1-7.

Lu, Jialang, et al. "DeepSPG: Exploring Deep Semantic Prior Guidance for Low-light Image Enhancement with Multimodal Learning." arXiv preprint arXiv:2504.19127 (2025).

Luo, H., Wei, J., Zhao, S., Liang, A., Xu, Z., & Jiang, R. (2024). Intelligent logistics management robot path planning algorithm integrating transformer and gcn network. IECE Transactions on Internet of Things, 2(4), 95-112.

Li, Huaxu, et al. "Enhancing Intelligent Recruitment With Generative Pretrained Transformer and Hierarchical Graph Neural Networks: Optimizing Resume-Job Matching With Deep Learning and Graph-Based Modeling." Journal of Organizational and End User Computing (JOEUC) 37.1 (2025): 1-24.

Wang, Meng, et al. "CPLOYO: A pulmonary nodule detection model with multi-scale feature fusion and nonlinear feature learning." Alexandria Engineering Journal 122 (2025): 578-587.

Shan, X., Xu, Y., Wang, Y., Lin, Y. S., & Bao, Y. (2024, June). Cross-Cultural Implications of Large Language Models: An Extended Comparative Analysis. In International Conference on Human-Computer Interaction (pp. 106-118). Cham: Springer Nature Switzerland.

Chew, J., Shen, Z., Hu, K., Wang, Y., & Wang, Z. (2025). Artificial Intelligence Optimizes the Accounting Data Integration and Financial Risk Assessment Model of the E-commerce Platform. International Journal of Management Science Research, 8(2), 7-17.

Saunders, E., Zhu, X., Wei, X., Mehta, R., Chew, J., & Wang, Z. (2025). The AI-Driven Smart Supply Chain: Pathways and Challenges to Enhancing Enterprise Operational Efficiency. Journal of Theory and Practice in Economics and Management, 2(2), 63–74. https://doi.org/10.5281/zenodo.15280568

Guo, Haocheng, Yaqiong Zhang, Lieyang Chen, and Arfat Ahmad Khan. "Research on Vehicle Detection Based on Improved YOLOv8 Network." Applied and Computational Engineering 116 (2025): 161-167.

Jin, Yuhui, Yaqiong Zhang, Zheyuan Xu, Wenqing Zhang, and Jingyu Xu. "Advanced object detection and pose estimation with hybrid task cascade and high-resolution networks." In 2024 International Conference on Image Processing, Computer Vision and Machine Learning (ICICML), pp. 1293-1297. IEEE, 2024.

Downloads

Published

2025-10-30

How to Cite

Fang, X. (2025). A Review of the Application of Big Data Technology in Computer Network Information Security Management. International Journal of Advance in Applied Science Research, 4(6), 9–13. Retrieved from https://h-tsp.com/index.php/ijaasr/article/view/95

Issue

Section

Articles