2025/10/18 by Bruno Octávio Horta Lourenço, Pedro Adão, Lourenço, Bruno +7
Computer Science · #Advanced Graph Neural Networks #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Information and Cyber Security #Network Security and Intrusion Detection
paper · pdf · doi:10.48550/arxiv.2510.16610
openalex publication_date 2025/10/18 · openalex created_date 2025/10/22 · openalex updated_date 2026/07/28
This survey investigates how ontologies, semantic log processing, and Large Language Models (LLMs) enhance cybersecurity. Ontologies structure domain knowledge, enabling interoperability, data integration, and advanced threat analysis. Security logs, though critical, are often unstructured and complex. To address this, automated construction of Knowledge Graphs (KGs) from raw logs is emerging as a key strategy for organizing and reasoning over security data. LLMs enrich this process by providing contextual understanding and extracting insights from unstructured content. This work aligns with European Union (EU) efforts such as NIS 2 and the Cybersecurity Taxonomy, highlighting challenges and opportunities in intelligent ontology-driven cyber defense.