Big Data in Practice

17 US IMMIGRATION AND CUSTOMS How Big Data Is Used To Keep Passengers Safe And Prevent Terrorism

Background

People move back and forward across US borders at a rate of nearly 100 million crossings a year. The Department of Homeland Security (DHS) have the unenviable task of screening each one of those crossings to make sure they aren’t being made with ill intentions, and pose no threat to national security.

Federal agencies have spent many millions of dollars since 11 September 2001, in the hope that they can prevent terrorists entering the country and carrying out further attacks on domestic soil. While formerly airport security measures focused on detecting the transportation of dangerous items such as drugs or bombs, the emphasis has shifted towards identifying bad people.

Working together with researchers at the University of Arizona, the DHS have developed a system which they call the Automated Virtual Agent for Truth Assessments in Real time – AVATAR.¹

What Problem Is Big Data Helping To Solve?

Since 9/11, the US has been increasingly aware that among the millions of people crossing its borders every year are some who are travelling with the intention of doing harm.

Security has been massively stepped up at airports and other points of entry, and generally this relies on one-to-one screening carried out by human agents, face-to-face with travellers.

This of course leaves the system open to human fallibility. Immigrations and Customs Service officers are highly trained ...