Research on Network Security in the Context of Big Data
Keywords:
Big data background, Network security, Strategies and technologiesAbstract
In the context of big data, research on network security is becoming increasingly important. With the surge in data volume, the risks of information leakage, hacker attacks, and network fraud have significantly increased. This article focuses on the challenges and response strategies of network security in the big data environment, including measures such as data encryption, access control, security auditing, and intelligent security protection systems. Through comprehensive analysis and practice, the aim is to enhance the security protection capabilities in big data applications, ensure the security and privacy of data assets, and safeguard the development of informatization.
References
Zhu, Y., Yu, W., & Li, R. (2025). SAGCN: A spatiotemporal attention-weighted graph convolutional network with IoT integration for adolescent tennis motion analysis. Alexandria Engineering Journal, 128, 652-662.
Zhang, X. (2024). Research on Dynamic Adaptation of Supply and Demand of Power Emergency Materials based on Cohesive Hierarchical Clustering. Innovation & Technology Advances, 2(2), 59–75. https://doi.org/10.61187/ita.v2i2.135
Zhou, J., & Cen, W. (2024). Investigating the Effect of ChatGPT-like New Generation AI Technology on User Entrepreneurial Activities. Innovation & Technology Advances, 2(2), 1–20. https://doi.org/10.61187/ita.v2i2.124
Yang, J., Wang, Z., & Chen, C. (2024). GCN-MF: A graph convolutional network based on matrix factorization for recommendation. Innovation & Technology Advances, 2(1), 14–26. https://doi.org/10.61187/ita.v2i1.30
Chen, J., Zhang, X., Wu, Y., Ghosh, S., Natarajan, P., Chang, S. F., & Allebach, J. (2022). One-stage object referring with gaze estimation. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 5021-5030).
Wu, W., Bi, S., Zhan, Y., & Gu, X. (2025). Supply chain digitalization and energy efficiency (gas and oil): How do they contribute to achieving carbon neutrality targets?. Energy Economics, 142, 108140.
Peng, Qucheng, Ce Zheng, and Chen Chen. "Source-free domain adaptive human pose estimation." Proceedings of the IEEE/CVF International Conference on Computer Vision. 2023.
Peng, Qucheng, et al. "RAIN: regularization on input and network for black-box domain adaptation." Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence. 2023.
Guo, Y., & Tao, D. (2025). Modeling and Simulation Analysis of Robot Environmental Interaction. Artificial Intelligence Technology Research, 2(8).
We, X., Lin, S., Pruś, K., Zhu, X., Jia, X., & Du, R. (2025). Towards Intelligent Monitoring of Anesthesia Depth by Leveraging Multimodal Physiological Data. International Journal of Advance in Clinical Science Research, 4, 26–37. Retrieved from https://www.h-tsp.com/index.php/ijacsr/article/view/158
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