Smarter, Faster, Safer: The Role of Graph Databases in Airport Custom Security
Bitnine Global Marketing team
Sat Jul 06 2024

Custom inspections at airports are a necessary step to ensure the safety and legality of imported goods. While this process can be long and tedious, it's essential for security reasons.
But why does it take so long in almost every airport?
This article explores the logistical challenges faced during customs inspections and how Graph Database technology can provide a solution.
Past Efforts and Challenges
Efforts to streamline customs inspections and reduce wait times have been made, but smugglers often outsmart these systems. Ingenious smuggling techniques, like using fellow travelers as proxies, bypass stringent checks. While comprehensive inspections can deter illegal activities, they are impractical due to the time and inconvenience they cause to all passengers.
Breaking Down the Challenges
Multiple Travelers Under One Reservation: It is easier to scrutinize travelers under the same reservation number, but it gets complex when individuals are under different reservations
High Crime Areas with Short Travel Distances: Detecting smugglers on short-distance flights is challenging due to insufficient time for analysis, especially in high-crime areas
Solutions Using Deep Analysis of Big Data
A Graph-based deep-analysis platform can identify smugglers and their associates. The database constructs a comprehensive graph representation of the target network, depicting smugglers and associates as 'nodes' and illustrating their connections as 'edges'.
Integrated Analytical System
This specialized database stores diverse traveler information in a structured graph format, allowing real-time analysis of travel companions. Potential smugglers are precisely categorized and identified efficiently.
Definition of Risk Companion (F.A.C.T Analysis)
Fellow Traveler: Travels with potential smuggler on the same flight
Acquaintance: Accomplice of potential smugglers, often in the same group booking or with frequent past trips together
Conspirator: Co-conspirators with similar travel patterns
Trafficker: Smugglers bringing in prohibited or unreported goods

Figure 1. Detection of Relationship Between Offender and Hidden Companion
[Node - Name (nationality, age, gender),
Edge - Number of flights (number of group reservations)]
PostgreSQL Compatibility
The Bitnine Global's graph database seamlessly integrates with relational databases, particularly PostgreSQL, through its extension that enhances it with powerful graph capabilities. This compatibility empowers airports to effortlessly incorporate unstructured data into their existing database systems.
Additionally, our graph-as-an-extension model facilitates straightforward data visualization, allowing efficient storage, management, and analysis of diverse data within a graph structure.

Figure 2. Graph Modeling Concept
Conclusion
The challenges faced by customs inspections at airports are significant, but with the advent of Graph Database technology and data-driven network association analysis, a new era in customs inspection is here. By constructing a comprehensive graph representation of traveler networks and categorizing potential smugglers and their companions, this technology offers a streamlined solution.
The deep analysis of big data, integrated analytical systems, and PostgreSQL compatibility make it possible to swiftly and accurately identify concealed smugglers and their collaborators. Through this innovative approach, airports can enhance security, expedite customs processes, and ensure the safety and legality of imported goods.
If you are interested in applying these technologies in your field, contact us today to learn more about applications in different industries and to get a head-start on new deep-analysis to combat potential frauds!