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- Publisher Website: 10.1007/978-981-15-1922-2_1
- Scopus: eid_2-s2.0-85076971573
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Conference Paper: Automatic Analysis and Reasoning Based on Vulnerability Knowledge Graph
Title | Automatic Analysis and Reasoning Based on Vulnerability Knowledge Graph |
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Authors | |
Keywords | Cybersecurity Knowledge graph Vulnerability Knowledge graph reasoning Knowledge extraction |
Issue Date | 2019 |
Publisher | Springer. |
Citation | Cyberspace Congress 2019: International Conference on Cyberspace Data and Intelligence (CyberDI) & International Conference on Cyber-Living, Cyber-Syndrome and Cyber-Health (CyberLife), Beijing, China, 16-18 December 2019. In Ning, H (ed.). Cyberspace Data and Intelligence, and Cyber-Living, Syndrome, and Health: International 2019 Cyberspace Congress, CyberDI and CyberLife, Proceedings, pt.1, p. 3-19 How to Cite? |
Abstract | In the security community, it is valuable to extract and store the vulnerability knowledge. Many data sources record vulnerability in unstructured data and semi-structured data which are hard for machine-understanding and reuse. Security expert need to analyze the description, link to related knowledge and reason out the hidden connection among various weakness. It is necessary to analyze the vulnerability data automatically and manage knowledge in a more intelligent method. In this paper, we propose a model for automatic analysis and reasoning based on the vulnerability knowledge graph. The vulnerability knowledge graph is extracted from several widely used vulnerability databases and stored in the graph database. Natural language processing technique is used to process and analyze the latest vulnerability description. The extracted entity will be linked to the vulnerability knowledge graph and added as new knowledge. Reasoning function can find hidden relationships among weaknesses based on the knowledge graph. Finally, we present sample cases to demonstrate the practical usage of the model. |
Persistent Identifier | http://hdl.handle.net/10722/289176 |
ISBN | |
Series/Report no. | Communications in Computer and Information Science (CCIS); v. 1137 |
DC Field | Value | Language |
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dc.contributor.author | Qin, S | - |
dc.contributor.author | Chow, KP | - |
dc.date.accessioned | 2020-10-22T08:08:55Z | - |
dc.date.available | 2020-10-22T08:08:55Z | - |
dc.date.issued | 2019 | - |
dc.identifier.citation | Cyberspace Congress 2019: International Conference on Cyberspace Data and Intelligence (CyberDI) & International Conference on Cyber-Living, Cyber-Syndrome and Cyber-Health (CyberLife), Beijing, China, 16-18 December 2019. In Ning, H (ed.). Cyberspace Data and Intelligence, and Cyber-Living, Syndrome, and Health: International 2019 Cyberspace Congress, CyberDI and CyberLife, Proceedings, pt.1, p. 3-19 | - |
dc.identifier.isbn | 9789811519215 | - |
dc.identifier.uri | http://hdl.handle.net/10722/289176 | - |
dc.description.abstract | In the security community, it is valuable to extract and store the vulnerability knowledge. Many data sources record vulnerability in unstructured data and semi-structured data which are hard for machine-understanding and reuse. Security expert need to analyze the description, link to related knowledge and reason out the hidden connection among various weakness. It is necessary to analyze the vulnerability data automatically and manage knowledge in a more intelligent method. In this paper, we propose a model for automatic analysis and reasoning based on the vulnerability knowledge graph. The vulnerability knowledge graph is extracted from several widely used vulnerability databases and stored in the graph database. Natural language processing technique is used to process and analyze the latest vulnerability description. The extracted entity will be linked to the vulnerability knowledge graph and added as new knowledge. Reasoning function can find hidden relationships among weaknesses based on the knowledge graph. Finally, we present sample cases to demonstrate the practical usage of the model. | - |
dc.language | eng | - |
dc.publisher | Springer. | - |
dc.relation.ispartof | Cyberspace Data and Intelligence, and Cyber-Living, Syndrome, and Health: International 2019 Cyberspace Congress, CyberDI and CyberLife Proceedings | - |
dc.relation.ispartofseries | Communications in Computer and Information Science (CCIS); v. 1137 | - |
dc.subject | Cybersecurity | - |
dc.subject | Knowledge graph | - |
dc.subject | Vulnerability | - |
dc.subject | Knowledge graph reasoning | - |
dc.subject | Knowledge extraction | - |
dc.title | Automatic Analysis and Reasoning Based on Vulnerability Knowledge Graph | - |
dc.type | Conference_Paper | - |
dc.identifier.email | Chow, KP: chow@cs.hku.hk | - |
dc.identifier.authority | Chow, KP=rp00111 | - |
dc.identifier.doi | 10.1007/978-981-15-1922-2_1 | - |
dc.identifier.scopus | eid_2-s2.0-85076971573 | - |
dc.identifier.hkuros | 317104 | - |
dc.identifier.volume | pt.1 | - |
dc.identifier.spage | 3 | - |
dc.identifier.epage | 19 | - |
dc.publisher.place | Singapore | - |