Myoung-oh Choi1, Mincheol Shin1, Hyonjun Kang1, Ka Lok Man2, Mucheol Kim1,*
CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.3, pp. 3191-3212, 2025, DOI:10.32604/cmes.2025.068723
- 30 September 2025
Abstract The escalating complexity and heterogeneity of modern energy systems—particularly in smart grid and distributed energy infrastructures—has intensified the need for intelligent and scalable security vulnerability classification. To address this challenge, we propose Vulnerability2Vec, a graph-embedding-based framework designed to enhance the automated classification of security vulnerabilities that threaten energy system resilience. Vulnerability2Vec converts Common Vulnerabilities and Exposures (CVE) text explanations to semantic graphs, where nodes represent CVE IDs and key terms (nouns, verbs, and adjectives), and edges capture co-occurrence relationships. Then, it embeds the semantic graphs to a low-dimensional vector space with random-walk sampling and skip-gram More >