Vulnerability assessment and decision analysis of airport unlawful interference emergency disposal based on complex network in China: Take regional airports for example

Since airports are vulnerable to unlawful interference, it is necessary to conduct a model-based vulnerability analysis to quantify the robustness and failure resilience of airport security systems. Therefore, this work establishes a fusion model that combines attack-defense games with complex networks to systematically analyze the airport emergency disposal network. Firstly, an attack-defense game model is constructed based on emergency disposal process of unlawful interference incidents. Introducing cost-benefit analysis to broaden the game model. Then the complex network of airport unlawful interference emergency disposal is constructed based on the attack-defense relationship. The method proposed in this study is applicable to regional airports. A simulation analysis is conducted using Zhangjiajie Hehua International Airport in China as an example. Through in-depth analyses of the network topology and vulnerability, this study finds that the airport unlawful interference emergency disposal network has small-world network characteristics, which ensures efficient information dissemination and resource allocation during emergency disposal. Airport security plays a key intermediary role in the defense network, and the strategy sets of public police form a tight sub-network. These characteristics enhance the overall emergency disposal capability of the network. The results of the vulnerability assessment show that although the network is able to withstand random attacks, it is highly vulnerable to deliberate attacks. Therefore, it is necessary to enhance the resilience of the emergency disposal network. Optimize the network based on the results of the vulnerability assessment. The results showed that the resilience of the network increased by 10.98 %. It will help airport security to respond more effectively to incidents of unlawful interference, thus contributing to the broader understanding of decision-making under risk and uncertainty in complex socio-economic systems.