Quantifying the Significance and Relevance of Cyber-Security Text Through Textual Similarity and Cyber-Security Knowledge Graph-Reference-Cited by-同舟云学术

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Quantifying the Significance and Relevance of Cyber-Security Text Through Textual Similarity and Cyber-Security Knowledge Graph

Published:2020 Issue: Volume:8 Page:177041-177052
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Mendsaikhan Otgonpurev^ORCID,Hasegawa Hirokazu,Yamaguchi Yukiko,Shimada Hajime

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/6287639/8948470/09207885.pdf?arnumber=9207885

Cited by 14 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Knowledge Graphs and Semantic Web Tools in Cyber Threat Intelligence: A Systematic Literature Review;Journal of Cybersecurity and Privacy;2024-08-01

2. Blockchain-Enabled Cybersecurity Provision for Scalable Heterogeneous Network: A Comprehensive Survey;Computer Modeling in Engineering & Sciences;2024

3. Deep Learning-based Knowledge Graph and Digital Twin Relationship Mining and Prediction Modeling;Applied Mathematics and Nonlinear Sciences;2024-01-01

4. An Overview of Cybersecurity Knowledge Graphs Mapped to the MITRE ATT&CK Framework Domains;2023 IEEE International Conference on Intelligence and Security Informatics (ISI);2023-10-02

5. Impact of Information Leakage and Conserving Digital Privacy;Malware Analysis and Intrusion Detection in Cyber-Physical Systems;2023-09-26

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