The Role and Applications of Airport Digital Twin in Cyberattack Protection during the Generative AI Era

Digital twins can simulate cyberattacks before they happen: The paper demonstrates that airports can use digital twin technology to model and test cyberattack scenarios in a safe, virtual environment, allowing security teams to identify vulnerabilities and strengthen defenses without risking actual airport operations.

AI can help detect threats faster and more accurately: By combining digital twins with machine learning and generative AI algorithms, airports can implement anomaly detection and threat hunting systems that identify suspicious activity more quickly than traditional methods, potentially stopping attacks before they cause damage.

Synthetic data generation improves security testing: The paper shows that generative AI can create realistic synthetic data within digital twin environments, enabling security teams to test their defensive systems against a wider variety of attack scenarios without needing to wait for real incidents to occur.

Explainable AI makes security training more effective: The integration of explainable AI (XAI) into digital twin platforms helps security staff understand why the system flagged a threat, improving human decision-making and enabling better training for airport personnel responsible for cybersecurity.

Digital twins support faster recovery and coordination: Beyond prevention, the paper highlights that digital twins can predict the impact of cyberattacks and help coordinate recovery efforts across airport stakeholders, reducing downtime and minimizing disruption to travelers and operations.