VCGERG: Vulnerability Classification With Graph Embedding Algorithm on Vulnerability Report Graphs

Yashu Liu, Xiaoyi Zhao, Xiaohua Qiu and Han-Bing Yan
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Yashu Liu: Beijing University of Civil Engineering and Architecture, China
Xiaoyi Zhao: Beijing University of Civil Engineering and Architecture, China
Xiaohua Qiu: Beijing University of Civil Engineering and Architecture, China
Han-Bing Yan: National Computer Network Emergency Response Technical Team, China

International Journal of Information Security and Privacy (IJISP), 2024, vol. 18, issue 1, 1-21

Abstract: Vulnerability can lead to data loss, privacy leakage and financial loss. Accurate detection and identification of vulnerabilities is essential to prevent information leakage and APT attacks. This paper explores the possibility of digging the valuable information in vulnerability reports deeply. We propose a new model, VCGERG, which products a graph using key information from vulnerability reports and embeds the graph into the vector space using a keywords-LINE graph embedding algorithm based on the attention of neighboring nodes. VCGERG model uses the OVR random forest algorithm to classify vulnerabilities. Our model can get the complicated local and global information of the graph in large-scale dataset and achieve better results. In order to verify the effectiveness of our model, it is evaluated on many experiments. Compared with other models, our method has a higher accuracy rate of 0.975.

Date: 2024
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