We’re all familiar with the morphing of faces from subject 1 to subject 2, in which there is an intermediate subject 1.5 that combines the features of both of them. But did you know that this simple trick can form the basis for fraudulent activity?
Back in the 20th century, morphing was primarily used for entertainment purposes. Nothing that would make you cry, even though there were shades of gray in the black or white representations of the morphed people.
But Godley, Creme, and Jackson weren’t trying to commit fraud. As I’ve previously noted, a morphed picture can be used for fraudulent activity. Let me illustrate this with a visual example. Take a look at the guy below.
Does this guy look familiar to you? Some of you may think he kinda sorta looks like one person, while others may think he kinda sorta looks like a different person.
The truth is, the person above does not exist. This is actually a face morph of two different people.
Now imagine a scenario in which a security camera is patrolling the entrance to the Bush ranch in Crawford, Texas. But instead of having Bush’s facial image in the database, someone has tampered with the database and inserted the “Obushama” image instead…and that image is similar enough to Barack Obama to allow Obama to fraudulently enter Bush’s ranch.
Or alternative, the “Obushama” image is used to create a new synthetic identity, unconnected to either of the two.
But what if you could detect that a particular facial image is not a true image of a person, but some type of morph attempt? NIST has a report on this:
“To address this issue, the National Institute of Standards and Technology (NIST) has released guidelines that can help organizations deploy and use modern detection methods designed to catch morph attacks before they succeed.”
The report, “NIST Interagency Report NISTIR 8584, Face Analysis Technology Evaluation (FATE) MORPH Part 4B: Considerations for Implementing Morph Detection in Operations,” is available in PDF form at https://doi.org/10.6028/NIST.IR.8584.
And a personal aside to anyone who worked for Safran in the early 2010s: we’re talking about MORPH detection, not MORPHO detection. I kept on mistyping the name as I wrote this.
Bredemarket 