Photo Tagging
Summary
Concerns
Despite this technical and legal arsenal designed to protect data, citizens, and their anonymity, critical voices have still been raised.
Grigory Bakunov in Russia has invented a solution to escape proper face detection and confuse face detection devices. He has developed an algorithm that creates special makeup to fool the software. However, he has chosen not to bring his product to market after realizing how easily criminals could use it.
In Germany, Berlin artist Adam Harvey has come up with a similar device known as CV Dazzle. He is now working on clothing featuring patterns to prevent detection. The hyperface camouflage includes patterns in fabric, such as eyes and mouths, to fool the face recognition system.
In late 2017, a Vietnamese company successfully used a mask to hack the Face ID face recognition function of Apple's iPhone X. However, the hack is too complicated to implement for large-scale exploitation.
Around the same time, researchers from a German company revealed a hack that allowed them to bypass the facial authentication of Windows 10 Hello by printing a facial image in infrared.
Forbes announced in an article from May 2018 that researchers from the University of Toronto have developed an algorithm to disrupt facial recognition software (aka privacy filter).
In August 2020, the Verge detailed a "cloaking" app named Fawkes. The software imperceptibly distorts your selfies and other pics you may leave on social media. The tool is coming from the University of Chicago’s Sand Lab.
In November 2020, a tool named Anonymizer was made available by Generated Media. The software creates a series of synthetic portraits from a picture you can upload. The images are mathematically similar to your face and look like you but will trick facial recognition software, according to tnw website. It could be an interesting solution to fool systems like Clearview AI that are scrapping millions of faces from social media (learn more on the Clearview AI controversy).