This Week in Security: That Time ENHANCE Actually Worked

ENHANCE!

The scene is all too familiar: a pivotal case against a suspected child predator is being analyzed by digital forensic experts, and it has all come down to a single grainy JPEG image. Cybersecurity experts and law enforcement officers pack a room filled with aerodynamically-crafted desks, custom-made quad-LCD screens and other futuristic gear, scanning the image for any clue that could blow the case wide open.

After a few tense moments, the team notices the tell-tale orange cylinder of a prescription bottle in the background of the image. The team becomes excited, shouts commands to the voice-recognition software. “Zoom,” they say, and the software snap-focuses on the prescription bottle. The software goes through cycles of Gaussian edge detection, and suddenly, the potato-camera image is replaced with an image whose details a $75,000 Hasselblad camera owner could only dream of capturing. A partial name and address is exposed, and agents begin scrambling to piece the new info together.

One agent points to the side of the now-crisp image, at the suspect’s hand. “Enhance,” he commands, and the image recognition software seemingly bends physics, logic, time, and space as it isolates the ridges of the suspect’s skin, revealing their fingerprints. In seconds, a fingerprint is extracted by the software and scanned into the CODIS database, exposing the perp and pulling up his home address. The team high-fives and celebrates yet another job well done.

Apparently, the Department of Homeland Security (DHS) made this scene actually happen. Whether or not futuristic office supplies were involved is still up for debate; however, the mad scientists and research engineers of DHS Science and Technology (S&T) have now developed new algorithms for analyzing low resolution digital images for crucial forensic data.

This software provides the team with new and unique ways to extract identifiable details (Read more...)

This is a Security Bloggers Network syndicated blog post authored by Cylance Research and Intelligence Team. Read the original post at: Cylance Blog