| Title | A Method to Construct Vulnerability Knowledge Graph Based on Heterogeneous Data |
| Publication Type | Conference Paper |
| Year of Publication | 2020 |
| Authors | Sun, Yizhen, Lin, Dandan, Song, Hong, Yan, Minjia, Cao, Linjing |
| Conference Name | 2020 16th International Conference on Mobility, Sensing and Networking (MSN) |
| Keywords | composability, computer security, Cyberspace, Databases, Error analysis, Knowledge engineering, Metrics, multi-source heterogeneous databases, Ontologies, power grid vulnerability, power grid vulnerability analysis, pubcrawl, Resiliency, Sensors, vulnerability knowledge graph, vulnerability ontology |
| Abstract | In recent years, there are more and more attacks and exploitation aiming at network security vulnerabilities. It is effective for us to prevent criminals from exploiting vulnerabilities for attacks and help security analysts maintain equipment security that knows vulnerabilities and threats on time. With the knowledge graph, we can organize, manage, and utilize the massive information effectively in cyberspace. In this paper we construct the vulnerability ontology after analyzing multi-source heterogeneous databases. And the vulnerability knowledge graph is established. Experimental results show that the accuracy of entity recognition for extracting vendor names reaches 89.76%. The more rules used in entity recognition, the higher the accuracy and the lower the error rate. |
| DOI | 10.1109/MSN50589.2020.00126 |
| Citation Key | sun_method_2020 |
A Method to Construct Vulnerability Knowledge Graph Based on Heterogeneous Data