Utrecht – NL, February 17, 2020. WCC has developed a successful Proof-of-Concept for detecting and analyzing anomalous passenger data. When integrated into HERMES software, the capability to detect anomalies can play a valuable in  Passenger Screening.

In order to further enhance its Passenger Screening Solution HERMES, WCC has been carrying out ongoing research. As a result, we have developed a model for detecting anomalous patterns in big passenger data. Anomaly detection is a technique for identifying data points that do not follow the expected behavior of the full data set. Such anomalous data could therefore point to critical incidents or potential opportunities.

WCC HERMES is a unique solution for Passenger Screening that offers extensive investigation capabilities. Above all, HERMES enables border security experts to create custom rules for targeting specific suspicious patterns. For example, ‘male aged 30-55 traveling with multiple females with different surnames age <20’. Anomaly detection could hence be of great value in identifying out-of-the-ordinary passenger behaviors. Based for instance on parameters such as travel itinerary, payment method, and origin of travel.

During their research, WCC’s Data Science Department created a Proof-of-Concept using a data set including age, nationality, origin, destination and type of passenger. After training the model, it can be run against real passenger lists to identify anomalies for specific flights. The successful Proof-of-Concept means that new investigative capabilities for Passenger Screening can be added to WCC HERMES.