Analysis of the Architecture, Technology and Advantages of AI-based Web Application Firewall
Keywords:
AI technology, Web application, Firewall systemAbstract
The static defense mode of traditional firewalls is difficult to cope with rapidly changing attack methods. However, the AI-powered WAF can automatically learn traffic patterns and attack characteristics by analyzing a large amount of network data in real time, enabling dynamic policy adjustment. It can more accurately distinguish legitimate requests from malicious attacks, significantly reduce false positives and false negatives, and quickly respond to large-scale network attacks, timely block the attack link, reduce the impact of attacks on Web applications, and ensure the continuity and stability of services. By analyzing the limitations of traditional Web application firewalls, comparing the advantages of combining AI technology with traditional technology, and explaining its system architecture and key technologies, this paper aims to improve Web application security and provide a reference for building an advanced security protection system.
References
Meng, L. (2023). Research on the Evaluation System of Green Cabling of Cables Based on Neural Network. Innovation & Technology Advances, 1(2), 25–31. https://doi.org/10.61187/ita.v1i2.37
Junxi, Y., 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
Gao, H., Zhao, W., Chen, W., Liu, J., Peng, W., & Zhou, S. (2026). Experimental study and geomechanical modelling of hard and soft rock masses including fault zones. Environmental Earth Sciences, 85(1), 7.
Han, J., Zhong, P. & Sun, L. Dual-scale model collaborative reasoning with multi-feature fusion for robust AI-generated image detection. Multimedia Systems 32, 363 (2026). https://doi.org/10.1007/s00530-026-02425-4
Ya, L. (2025). EDA Technology in Digital Circuit Design: A Study on Application Methodologies. International Journal of Advance in Applied Science Research, 4(12), 6-10.
Sun, Lingxin. "Designing Inclusive Interfaces: Accessibility Challenges and Solutions in Digital Products." Proceedings of the 2025 International Conference on Artificial Intelligence and Sustainable Development. 2025.
Zhang, X. (2026, March). A Hybrid LSTM-GARCH Model Integrating Volatility Factors from the US Financial Markets. In Proceedings of the 2026 International Conference on AI Decision-Making and Management (pp. 183-189).
Ding, G. (2025). Development and Validation of a Multispectral Vision System for In-Situ Detection of Pesticide Residues on Agricultural Produce. International Journal of Advance in Applied Science Research, 4(8), 98-102.
Luo, R. (2026). The Integration Analysis of Computer Application Technology and Information Management. International Journal of Advance in Applied Science Research, 5(2), 27-30.
Shen, Zepeng, et al. "Research on Application of Whale Optimization Algorithm in Financial Payment Fraud Detection." 2025 4th International Conference on Artificial Intelligence, Internet and Digital Economy (ICAID). IEEE, 2025.
Wang, J. (2026). Research on the Application of Computer Science and Technology in the Context of Big Data. International Journal of Advance in Applied Science Research, 5(1), 72-77.
Ma, J. (2025). A Unified Framework for Congestion Diagnosis and Dynamic Mitigation in Complex Networks. International Journal of Advance in Applied Science Research, 4(11), 36-41.
Jin, L. (2025). Optimization of Order Allocation Algorithms for Industrial Internet Platforms. International Journal of Advance in Applied Science Research, 4(12), 44-48.
Zhou, Z. (2025, November). Digital precision distribution strategy for social media content on private domain platforms in the automotive industry: a collaborative filtering model based on user behavior. In Proceedings of the 2025 International Conference on Digital Society and Intelligent Computing (pp. 516-521).
YUAN, Mengwei, et al. TA-Mem: Tool-Augmented Autonomous Memory Retrieval for LLM in Long-Term Conversational QA. In: 2026 9th International Conference on Advanced Algorithms and Control Engineering (ICAACE). IEEE, 2026. p. 2684-2688.
Li, G., Yuan, H., Chen, S., Hu, Q., Wang, J., & Jiang, K. (2026). MFT: Memory-Aware Fine-Tuning of SAM2 for Efficient Long-Sequence Video Object Segmentation. IEEE Signal Processing Letters.
Shan, X., Xu, Y., Xia, T., & Lin, Y. S. (2025, October). Rethinking Wine Tasting for Chinese Consumers: A Service Design Approach Enhanced by Multimodal Personalization. In 2025 International Conference on Content-Based Multimedia Indexing (CBMI) (pp. 1-5). IEEE.
Liu, Y. (2025). The Deep Learning Paradigm for Plant Image Classification: A Systematic Evaluation of Architectural Efficacy. International Journal of Advance in Applied Science Research, 4(8), 73-79.
Miao, J. (2026). Big Data Technologies for Enhanced Network Security Analysis: Applications and Approaches. International Journal of Advance in Applied Science Research, 5(4), 16-20.
Wang, J. (2025). Multi-Scale Feature-Enhanced YOLOv8 for Object Detection in Photovoltaic Farm Panoramic Imagery. International Journal of Advance in Applied Science Research, 4(10), 7-11.
Liu, X. (2025). Research on the Application of GPU Parallel Computing in Image Processing. International Journal of Advance in Applied Science Research, 4(2), 1-7.
Lu, J., Chen, J., Chen, Z., Zhang, L., & Fang, J. (2025). Flame Detection Based on Faster R-CNN Model. International Journal of Advance in Applied Science Research, 4(7), 41-45.
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.
Peng, Qucheng, Ce Zheng, and Chen Chen. "A Dual-Augmentor Framework for Domain Generalization in 3D Human Pose Estimation." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2024.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Zhou Yan

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
