2025
doi: 10.12720/jait.16.2.177-188
Advancing Cybersecurity through the Development of a Semantic Knowledge Base: Novel Methods and Schemes for Multi-source Data Integration
Yue Zhao1,2,3
,
Gang Xiong3 ,
Jincheng Guo4,* ,
Yi Ni5 ,
Bin Yang2 ,
Qi Zhao1,3
- 1National Key Laboratory of Security Communication, Chengdu, China
- 2School of Computer and Information Engineering, Chuzhou University, Chuzhou, China
- 3No. 30 Research Institute of China Electronics Technology Group Corporation, Chengdu, China
- 4China Communications Construction Company and Dalian University of Technology Institute of Communication Technology CO., LTD, Dalian, China
- 5Sichuan Aerospace 706 Information Technology Co Ltd, Chengdu, China
- Manuscript receivedAugust 28, 2024
- revisedSeptember 9, 2024
- acceptedOctober 9, 2024
- publishedFebruary 10, 2025
Abstract
The paper presents a novel method for constructing a multi-domain, multi-layer cybersecurity semantic knowledge base. Utilizing diverse cybersecurity data sources, the framework seamlessly integrates entity extraction, event extraction, and semantic relation extraction through sophisticated semantic parsing techniques, resulting in a highly accurate and comprehensive knowledge base. By employing Bi-directional Long Short-Term Memory (Bi-LSTM) models with attention mechanisms for precise entity extraction, a hierarchical strategy network for detailed event extraction, and pattern rule matching for elaborate semantic relation extraction, the proposed method demonstrates exceptional efficacy. Experimental results show entity extraction with 95.4% accuracy and 92.5% recall, event extraction with 93.3% accuracy and 90.8% recall, and semantic relation extraction with 90.7% accuracy and 88.6% recall. The constructed knowledge base achieves an average query response time of 0.5 s and a query accuracy of 92%. This innovative approach enhances the processing and understanding of complex cybersecurity data, providing reliable and precise semantic knowledge query and reasoning, crucial for dynamic threat response.
Keywords
- semantic knowledge base
- cybersecurity
- semantic parsing
- attention mechanism
- hierarchical policy networks
How to Cite
Yue Zhao, Gang Xiong, Jincheng Guo, Yi Ni, Bin Yang, and Qi Zhao, "Advancing Cybersecurity through the Development of a Semantic Knowledge Base: Novel Methods and Schemes for Multi-source Data Integration," Journal of Advances in Information Technology, vol. 16, no. 2, pp. 177-188, 2025. https://doi.org/10.12720/jait.16.2.177-188
Copyright & License
Copyright © 2025 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
