<![CDATA[Airport security is a vital component in maintaining the stability of air transportation systems. Although scanning technologies and access control systems have significantly advanced, the potential threat posed by internal actors remains an unresolved vulnerability. This study aims to examine the feasibility of integrating artificial intelligence (AI) technologies to detect threat intentions through gesture and body temperature analysis, with a specific focus on the apron zone a highly vulnerable area of the airport. Utilizing a hypothetical scenario based on the Red Team method, this study maps potential breach pathways conducted by individuals with authorized access. The findings suggest that the integration of computer vision, thermal imaging, and behavioral profiling has the potential to identify anomalous behaviors indicative of malicious intent. This research highlights the importance of combining technological approaches with human-centered security strategies to develop a more adaptive and accurate predictive security system.]]>
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