An Ontology-Based Approach for Context-Aware Automotive Security
Teena Kumari, Abdur Rakib, Arkady Zaslavsky, Hesamaldin Jadidbonab, Valeh Moghaddam · 2025
The use of ontologies in context-aware systems has been widely recognised across various applications and domains. However, their potential for enhancing cybersecurity in the automotive domain remains underexplored. Understanding how semantic knowledge can be acquired, structured, and leveraged to support security-related decision-making is a critical area of research. While artificial intelligence, and machine learning-based approaches are commonly employed, the advantages of semantic knowledge-based models, particularly ontologies, require attention and practical implementation. This paper emphasises the significance of utilising context-aware ontologies for automotive cybersecurity. Specifically, it explores the development of ontology-based models enriched with contextual information and demonstrates their potential to enhance automotive security measures.