Outwitting image recognition

Last year, engineers at ZeroFOX, a security startup, noticed something odd about a fake social-media profile they’d found of a well-known public figure. Its profile photo had tiny white dots across the face, like a dusting of digital snow. The company’s engineers weren’t certain, but it looked like the dots were placed to trick a content filter, the kind used by social networks like Facebook to flag celebrity imitations.

They believed the photo was an example of a new kind of digital camouflage, in which a picture is altered in ways that leave it looking normal to the human eye but cause an image-recognition system to misclassify the image.

Such tricks could pose a security risk in the global rush among businesses and governments to use image-recognition technology.