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With the increasing complexity of autonomous vehicle (AV) networks, ensuring enhanced cybersecurity has become a critical challenge. Traditional security techniques often struggle to adapt dynamically to evolving threats. This study proposes a novel domain ontology to assess its coherence and effectiveness in structuring knowledge about AV security threats, intrusion characteristics, and corresponding mitigation techniques. Developed using Protégé 4.3 and the Web Ontology Language (OWL), the ontology formalizes cybersecurity concepts without directly integrating with an Intrusion Detection System (IDS). By providing a semantic representation of attacks and countermeasures, the ontology enhances threat classification and supports automated decision-making in security frameworks. Experimental evaluation demonstrated its effectiveness in improving knowledge organization and reducing inconsistencies in security threat analysis. Future work will focus on integrating the ontology with real-time security monitoring and IDS frameworks to enhance adaptive intrusion response strategies.