| Issue |
ITM Web Conf.
Volume 80, 2025
2025 2nd International Conference on Advanced Computer Applications and Artificial Intelligence (ACAAI 2025)
|
|
|---|---|---|
| Article Number | 04008 | |
| Number of page(s) | 8 | |
| Section | Applications in Industry, Finance & AI Ethics | |
| DOI | https://doi.org/10.1051/itmconf/20258004008 | |
| Published online | 16 December 2025 | |
Network Protocol Vulnerability Assessment: A Comparative Analysis of SMB Vulnerabilities in Windows Network Environments
College of Software, Beijing University of Aeronautics and Astronautics, Beijing, 430070, China
* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
This study explained the development of Server Message Block (SMB) and its composition and role as a communication protocol, and delved into the SMBGhost vulnerability (CVE-2020-0796) in Windows network environments. Through strictly controlled experimental variables, it systematically quantifies the exploit success rate under different configurations and evaluates the protective effectiveness of Microsoft’s KB4551762 patch. The experimental results indicate that the exploit success rate for unpatched systems reaches 90%, while applying the patch results in a 37% decline in file transfer performance. To balance security and performance, this paper proposes a lightweight Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM) hybrid detection model, which reduces the false positive rate by 63% compared to traditional Snort rules, achieves a detection accuracy of 96%, and has an inference latency of only 1.8 ms. Key findings include precise delineation of the memory corruption boundaries in the srv2.sys driver, as well as empirical validation of a worm propagation rate of 3.2 devices per second, providing an optimized solution for enterprise network defense that considers both security and performance.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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