Ontology Learning for Hybrid Threats

This report explores using advanced AI for mining Open Source Information in Hybrid Threat analysis. Rising tensions make Hybrid Threats more critical, posing technological challenges. Large Language Models show promise but suffer from hallucinations and biases. We propose using formal knowledge bases to correct these issues, reducing human effort via a methodology leveraging limited LLM abilities, aiming to improve Open Source Intelligence reliability.