Work

Structuring Security: A Survey of Cybersecurity Ontologies, Semantic Log Processing, and LLMs Application

Year: 2025

Type: preprint

Abstract: 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.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.2510.16610

Authors: Lourenço, Bruno, Adão, Pedro, Ferreira, João F., Marques, Mario Monteiro, Vaz, Cátia

Institutions: Instituto de Engenharia de Sistemas e Computadores Investigação e Desenvolvimento, Universidade do Porto

Language: English

Topic: Semantic Web and Ontologies

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funder: Fundação para a Ciência e a Tecnologia

Awards: G1740015287, Instituto de Engenharia de Sistemas e Computadores, Investigação e Desenvolvimento em Lisboa

OpenAlex ID: W4415955403

Cites: 6

Cited by: 8

Related to: 10